User login
Addressing Maternal Mortality Through Education: The Mommies Methadone Program
From the UT Health Long School of Medicine San Antonio, Texas.
Abstract
Objective: To educate pregnant patients with opioid use disorder (OUD) about the effects of opioids in order to improve understanding and help achieve sustained abstinence.
Methods: The Center for Health Care Services and University Hospital System (UHS) in San Antonio, TX, jointly o
Results: Of 68 women enrolled in the program, 33 completed both the pre-survey and the post-survey (48.5%). Nearly half (48%) were very motivated to quit before pregnancy, but 85% were very motivated to quit once pregnant. All participants said learning more about the effects of opiates would increase motivation for sobriety. Prior to the educational intervention, 39% of participants knew it was safe to breastfeed on methadone, which improved to 97% in the post-survey, and 76% incorrectly thought they would be reported to authorities by their health care providers if they used illegal drugs during pregnancy, while in the post-survey, 100% knew they would not be reported for doing so.
Conclusion: Pregnancy and education about opioids increased patients’ motivation to quit. Patients also advanced their breastfeeding knowledge and learned about patient-provider confidentiality. Our greatest challenge was participant follow-up; however, this improved with the help of a full-time Mommies Program nurse. Our future aim is to increase project awareness and extend the educational research.
Keywords: pregnancy; addiction; opioids; OUD; counseling.
In 2012 more than 259 million prescriptions for opioids were written in the United States, which was a 200% increase since 1998.1 Since the early 2000s, admissions to opioid substance abuse programs and the death rate from opioids have quadrupled.2-4 Specifically, the rate of heroin use increased more than 300% from 2010 to 2014.5 Opioid use in pregnancy has also escalated in recent years, with a 3- to 4-fold increase from 2000 to 2009 and with 4 in 1000 deliveries being complicated by opioid use disorder (OUD) in 2011.6-8
Between 2000 and 2014, the maternal mortality rate in the United States increased 24%, making it the only industrialized nation with a maternal mortality rate that is rising rather than falling.9 The Texas Maternal Mortality and Morbidity Task Force found that between 2012 and 2015 drug overdose was the leading cause of maternal death in the period from delivery to 365 days postpartum, and it has increased dramatically since 2010.10,11
In addition, maternal mortality reviews in several states have identified substance use as a major risk factor for pregnancy-associated deaths.12,13 In Texas between 2012 and 2015, opioids were found in 58% of maternal drug overdoses.10 In 2007, 22.8% of women who were enrolled in Medicaid programs in 46 states filled an opioid prescription during pregnancy.14 Additionally, the rising prevalence of opioid use in pregnancy has led to a sharp increase in neonatal abstinence syndrome (NAS), rising from 1.5 cases per 1000 hospital births in 1999 to 6.0 per 1000 hospital births in 2013.15 Unsurprisingly, states with the highest rates of opioid prescribing also have the highest rates of NAS.16
Methadone combined with counseling and behavioral therapy has been the standard of care for the treatment of OUD in pregnancy since the 1970s. Methadone treatment prevents opioid withdrawal symptoms and increases adherence to prenatal care.17 One of the largest methadone treatment clinics in the San Antonio, TX, area is the Center for Health Care Services (CHCS). University Health System in San Antonio (UHS) has established a clinic called The Mommies Program, where mothers addicted to opioids can receive prenatal care by a dedicated physician, registered nurse, and a certified nurse midwife, who work in collaboration with the CHCS methadone clinic. Pregnant patients with OUD in pregnancy are concurrently enrolled in the Mommies Program and receive prenatal care through UHS and methadone treatment and counseling through CHCS. The continuity effort aims to increase prenatal care rates and adherence to methadone treatment.
Once mothers are off illicit opioids and on methadone, it is essential to discuss breastfeeding with them, as many mothers addicted to illicit opioids may have been told that they should not be breastfeeding. However, breastfeeding should be encouraged in women who are stable on methadone if they are not using illicit drugs and do not have other contraindications, regardless of maternal methadone dose, since the transfer of methadone into breast milk is minimal.18-20 Breastfeeding is beneficial in women taking methadone and has been associated with decreased severity of NAS symptoms, decreased need for pharmacotherapy, and a shorter hospital stay for the baby.21 In addition, breastfeeding contributes to the development of an attachment between mother and infant, while also providing the infant with natural immunity. Women should be counseled about the need to stop breastfeeding in the event of a relapse.22
Finally, the postpartum period represents a time of increased stressors, such as loss of sleep, child protective services involvement, and frustration with constant demands from new baby. For mothers with addiction, this is an especially sensitive time, as the stressors may be exacerbated by their new sobriety and a sudden end to the motivation they experienced from pregnancy.23 Therefore, early and frequent postpartum care with methadone dose evaluation is essential in order to decrease drug relapse and screen for postpartum depression in detail, since patients with a history of drug use are at increased risk of postpartum depression.
In 2017 medical students at UT Health Long School of Medicine in San Antonio created a project to educate women about OUD in pregnancy and provide motivational incentives for sustained abstinence; this project has continued each year since. Students provide education about methadone treatment and the dangers of using illicit opioids during and after pregnancy. Students especially focus on educating patients on the key problem areas in the literature, such as overdose, NAS, breastfeeding, postpartum substance use, and postpartum depression.
Methods
From October 2018 to February 2020, a total of 15 medical students volunteered between 1 and 20 times at the Mommies Program clinic, which was held once or twice per week from 8
The only inclusion criteria for participating in the educational intervention and survey was participants had to be 18 years of age or older and enrolled in the Mommies Program. Patients who met the inclusion criteria and agreed to participate completed a pre-survey administered by the students during the patient’s initial prenatal visit (Figure 2). This survey collected baseline information about the patient’s history with opioid use and their current knowledge of methadone treatment, NAS, legal aspects of drug use disclosure, and drug testing prior to the education portion of the encounter. After the pre-survey was administered, students spent 30 minutes reviewing the correct answers of the survey with the patients by utilizing the standardized handout to help patients understand details of methadone and opioid use in pregnancy (Figure 1). The post-survey was administered by a student once patients entered the third trimester to assess whether the education session increased patients’ knowledge of these topics.
At the time patients completed the post-survey, they received a Baby Bag as well as education regarding each item in the bag. The aim of distributing Baby Bags was to relieve some possible postnatal stressors and educate the patients about infant care. Items included in the bag were diapers, wipes, bottles, clothes, and swaddles. Prenatal vitamins were added in January 2020, as many patients struggle to afford vitamins if they are not currently covered by Medicaid or have other barriers. The Baby Bag items were purchased through a Community Service Learning grant through UT Health San Antonio.
Results
Of 68 women enrolled in the Mommies Program during the intervention period, 33 completed the pre-survey and the post-survey (48.5%). Even though all patients enrolled in the program met the inclusion criteria, patients were not included in the educational program for multiple reasons, including refusal to participate, poor clinic follow-up, or lack of students to collect surveys. However, all patients who completed the pre-survey did complete the post-survey. In the pre-survey, only 39% of participants knew it was safe to breastfeed while on methadone. In the post-survey, 97% knew it safe to breastfeed. Nearly half (48%) reported being very motivated to quit opioids before pregnancy, but 85% were very motivated to quit once pregnant. In the pre-survey, 76% incorrectly thought they would be reported to authorities by their health providers if they used illegal drugs during pregnancy, while in the post-survey, 100% knew they would not be reported for doing so. Also, all participants said learning more about the effects of opiates would increase motivation for sobriety.
Discussion
Questions assessed during the educational surveys revolved around patients’ knowledge of the intricacies, legally and physiologically, of methadone treatment for OUD, as well as beneficial aspects for patients and future child health, such as breastfeeding and motivation to quit and stay sober.
It was clear that there was a lack of knowledge and education about breastfeeding, as only 39% of the participants thought that it was safe to breastfeed while on methadone in the pre-survey; in the post survey, this improved to 97%. Students spent a large portion of the educational time going over the safety of breastfeeding for patients on methadone and the many benefits to mother and baby. Students also reviewed breastfeeding with patients every time patients came in for a visit and debunked any falsehoods about the negatives of breastfeeding while on methadone. This is another testament to the benefits of reinforcement around patient education.
The area of trust between provider and patient is essential in all provider-patient relationships. However, in the area of addiction, a trusting bond is especially important, as patients must feel confident and comfortable to disclose every aspect of their lives so the provider can give the best care. It was clear from our initial data that many patients did not feel this trust or understand the legal aspects regarding the provider-patient relationship in the terms of drug use, as the pre-survey shows 76% of patients originally thought they would be reported to authorities if they told their provider they used illegal drugs during pregnancy. This was an enormous issue in the clinic and something that needed to be addressed because, based on these data, we feared many patients would not be honest about using illegal drugs to supplement their methadone if they believed they would be reported to the authorities or even jailed. The medical student education team continually assured patients that their honesty about illegal drug use during pregnancy would not be revealed to the authorities, and also made it clear to patients that it was essential they were honest about illegal drug use so the optimal care could be provided by the team. These discussions were successful, as the post-survey showed that 100% of patients knew they would not be reported to the authorities if they used illegal drugs during the pregnancy. This showed an increase in knowledge, but also suggested an increase in confidence in the provider-patient relationship by patients, which we speculate allowed for a better patient experience, better patient outcomes, and less emotional stress for the patient and provider.
Last, we wanted to study and address the motivation to quit using drugs and stay sober through learning about the effects of opiates and how this motivation was related to pregnancy. A study by Mitchell et al makes clear that pregnancy is a motivation to seek treatment for drug use and to quit,24 and our survey data support these findings, with 48% of patients motivated to quit before they were pregnant and 85% motivated to quit once they knew they were pregnant. In addition, all patients attested on the pre- and post-survey that learning more about opioids would increase their motivation for sobriety. Therefore, we believe education about the use of opioids and other drugs is a strong motivation towards sobriety and should be further studied in methadone treatment and other drugs as well.
We will continue to focus on sobriety postpartum by using the education in pregnancy as a springboard to further postpartum education, as education seems to be very beneficial to future sobriety. In the future, we believe extending the educational program past pregnancy and discussing opioid use and addiction with patients at multiple follow-up visits will be beneficial to patients’ sobriety.
We faced 2 main challenges in implementing this intervention and survey: patients would often miss multiple appointments during their third trimester or would not attend their postpartum visit if they only had 1 prenatal visit; and many clinic sessions had low student attendance because students often had many other responsibilities in medical school and there were only 15 volunteers over the study time. These challenges decreased our post-survey completion rate. However, there has been improvement in follow-up as the project has continued. The Mommies Program now has a full-time registered nurse, and a larger number of medical student teachers have volunteered to attend the clinic. In the future, we aim to increase awareness of our project and the benefits of participation, expand advertising at our medical school to increase student participation, and increase follow-up education in the postpartum period.
Another future direction is to include local, free doula services, which are offered through Catholic Charities in San Antonio. Doulas provide antepartum, intrapartum, and postpartum services, which we believe will help our patients through advocacy and support for sobriety during this emotional and stressful time.
Conclusion
Counseled participants were receptive to learning about the effects of OUD and methadone on themselves and their newborn. Participants unanimously stated that learning more about OUD increased their motivation for sobriety. It was also clear that the increased motivation to be sober during pregnancy, as compared to before pregnancy, is an opportunity to help these women take steps to get sober. Patients also advanced their breastfeeding knowledge, as we helped debunk falsehoods surrounding breastfeeding while on methadone, and we anticipate this will lead to greater breastfeeding rates for our patients on methadone, although this was not specifically studied. Finally, patients learned about patient-provider confidentiality, which allowed for more open and clear communication with patients so they could be cared for to the greatest degree and trust could remain paramount.
Drug use is a common problem in the health care system, and exposure to patients with addiction is important for medical students in training. We believe that attending the Mommies Program allowed medical students to gain exposure and skills to better help patients with OUD.
Corresponding author: Nicholas Stansbury, MD, Nmstansbury85@gmail.com.
Financial disclosures: None.
1. Centers for Disease Control and Prevention. Opioid painkiller prescribing: where you live makes a difference. CDC website. www.cdc.gov/vitalsigns/opioid-prescribing. Accessed October 28, 2020.
2. Substance Abuse and Mental Health Services Administration. Drug Abuse Warning Network, 2011: national estimates of drug-related emergency department visits. HHS Publication No. (SMA) 13-4760, DAWN Series D-39. Rockville (MD): SAMHSA; 2013. www.samhsa.gov/data/sites/default/files/DAWN2k11ED/DAWN2k11ED/DAWN2k11ED.pdf. Accessed October 28, 2020.
3. Compton WM, Jones CM, Baldwin GT. Relationship between nonmedical prescription-opioid use and heroin use. N Engl J Med. 2016;374:154-63.
4. National Center for Health Statistics. NCHS data on drug-poisoning deaths. NCHS Factsheet. https://www.cdc.gov/nchs/data/factsheets/factsheet-drug-poisoning-H.pdf. Accessed October 28, 2020.
5. National Institute on Drug Abuse. America’s addiction to opioids: heroin and prescription drug abuse. Bethesda (MD): NIDA; 2014. www.drugabuse.gov/about-nida/legislative-activities/testimony-to-congress/2016/americas-addiction-to-opioids-heroin-prescription-drug-abuse. Accessed October 28, 2020.
6. Substance Abuse and Mental Health Services Administration (SAMHSA). Results from the 2010 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: SAMHSA, 2011 Contract No.: HHS Publication no. (SMA) 11–4658.
7. Maeda A, Bateman BT, Clancy CR, et al. Opioid abuse and dependence during pregnancy: temporal trends and obstetrical outcomes. Anesthesiology. 2014;121:1158-1165.
8. Whiteman VE, Salemi JL, Mogos MF, et al. Maternal opioid drug use during pregnancy and its impact on perinatal morbidity, mortality, and the costs of medical care in the United States. J Pregnancy. 2014;2014:1-8
9. Pregnancy Mortality Surveillance System. www.cdc.gov/reproductivehealth/maternal-mortality/pregnancy-mortality-surveillance-system.htm#trends. Accessed February 4, 2020.
10. Macdorman MF, Declercq E, Cabral H, Morton C. Recent increases in the U.S. maternal mortality rate. Obstet Gynecol. 2016;128:447-455.
11. Texas Health and Human Services. Maternal Mortality and Morbidity Task Force and Department of State Health Services Joint Biennial Report, September 2018. www.dshs.texas.gov/legislative/2018-Reports/MMMTFJointReport2018.pdf
12. Virginia Department of Health. Pregnancy-associated deaths from drug overdose in Virginia, 1999-2007: a report from the Virginia Maternal Mortality Review Team. Richmond, VA: VDH; 2015. www.vdh.virginia.gov/content/uploads/sites/18/2016/04/Final-Pregnancy-Associated-Deaths-Due-to-Drug-Overdose.pdf. Accessed October 28, 2020.
13. Maryland Department of Health and Mental Hygiene. Maryland maternal mortality review 2016 annual report. Baltimore: DHMH; 2016. https://phpa.health.maryland.gov/Documents/Maryland-Maternal-Mortality-Review-2016-Report.pdf. Accessed October 28, 2020.
14. Desai RJ, Hernandez-Diaz S, Bateman BT, Huybrechts KF. Increase in prescription opioid use during pregnancy among Medicaid-enrolled women. Obstet Gynecol. 2014;123:997-1002.
15. Reddy UM, Davis JM, Ren Z, et al. Opioid use in pregnancy, neonatal abstinence syndrome, and childhood outcomes. Obstet Gynecol Survey. 2017;72:703-705.
16. Patrick SW, Davis MM, Lehmann CU, Cooper WO. Increasing incidence and geographic distribution of neonatal abstinence syndrome: United States 2009 to 2012. J Perinatol. 2015;35:650-655.
17. Center for Substance Abuse Treatment. Medication-assisted treatment for opioid addiction during pregnancy. In: Medication-assisted treatment for opioid addiction in opioid treatment programs. Treatment Improvement Protocol (TIP) Series, No. 43. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2005:211-224.
18. Wojnar-Horton RE, Kristensen JH, Yapp P, et al. Methadone distribution and excretion into breast milk of clients in a methadone maintenance programme. Br J Clin Pharmacol. 1997;44:543-547.
19. Reece-Stremtan S, Marinelli KA. ABM clinical protocol #21: guidelines for breastfeeding and substance use or substance use disorder, revised 2015. Breastfeed Med. 2015;10:135-141.
20. Sachs HC. The transfer of drugs and therapeutics into human breast milk: an update on selected topics. Committee on Drugs. Pediatrics. 2013;132:e796-809.
21. Bagley SM, Wachman EM, Holland E, Brogly SB. Review of the assessment and management of neonatal abstinence syndrome. Addict Sci Clin Pract. 2014;9:19.
22. Opioid use and opioid use disorder in pregnancy. Committee Opinion No. 711. Obstet Gynecol. 2017;130:488-489.
23. Gopman S. Prenatal and postpartum care of women with substance use disorders. Obstet Gynecol Clin North Am. 2014;41:213-228.
24. Mitchell M, Severtson S, Latimer W. Pregnancy and race/ethnicity as predictors of motivation for drug treatment. Am J Drug Alcohol Abuse. 2008;34:397-404.
From the UT Health Long School of Medicine San Antonio, Texas.
Abstract
Objective: To educate pregnant patients with opioid use disorder (OUD) about the effects of opioids in order to improve understanding and help achieve sustained abstinence.
Methods: The Center for Health Care Services and University Hospital System (UHS) in San Antonio, TX, jointly o
Results: Of 68 women enrolled in the program, 33 completed both the pre-survey and the post-survey (48.5%). Nearly half (48%) were very motivated to quit before pregnancy, but 85% were very motivated to quit once pregnant. All participants said learning more about the effects of opiates would increase motivation for sobriety. Prior to the educational intervention, 39% of participants knew it was safe to breastfeed on methadone, which improved to 97% in the post-survey, and 76% incorrectly thought they would be reported to authorities by their health care providers if they used illegal drugs during pregnancy, while in the post-survey, 100% knew they would not be reported for doing so.
Conclusion: Pregnancy and education about opioids increased patients’ motivation to quit. Patients also advanced their breastfeeding knowledge and learned about patient-provider confidentiality. Our greatest challenge was participant follow-up; however, this improved with the help of a full-time Mommies Program nurse. Our future aim is to increase project awareness and extend the educational research.
Keywords: pregnancy; addiction; opioids; OUD; counseling.
In 2012 more than 259 million prescriptions for opioids were written in the United States, which was a 200% increase since 1998.1 Since the early 2000s, admissions to opioid substance abuse programs and the death rate from opioids have quadrupled.2-4 Specifically, the rate of heroin use increased more than 300% from 2010 to 2014.5 Opioid use in pregnancy has also escalated in recent years, with a 3- to 4-fold increase from 2000 to 2009 and with 4 in 1000 deliveries being complicated by opioid use disorder (OUD) in 2011.6-8
Between 2000 and 2014, the maternal mortality rate in the United States increased 24%, making it the only industrialized nation with a maternal mortality rate that is rising rather than falling.9 The Texas Maternal Mortality and Morbidity Task Force found that between 2012 and 2015 drug overdose was the leading cause of maternal death in the period from delivery to 365 days postpartum, and it has increased dramatically since 2010.10,11
In addition, maternal mortality reviews in several states have identified substance use as a major risk factor for pregnancy-associated deaths.12,13 In Texas between 2012 and 2015, opioids were found in 58% of maternal drug overdoses.10 In 2007, 22.8% of women who were enrolled in Medicaid programs in 46 states filled an opioid prescription during pregnancy.14 Additionally, the rising prevalence of opioid use in pregnancy has led to a sharp increase in neonatal abstinence syndrome (NAS), rising from 1.5 cases per 1000 hospital births in 1999 to 6.0 per 1000 hospital births in 2013.15 Unsurprisingly, states with the highest rates of opioid prescribing also have the highest rates of NAS.16
Methadone combined with counseling and behavioral therapy has been the standard of care for the treatment of OUD in pregnancy since the 1970s. Methadone treatment prevents opioid withdrawal symptoms and increases adherence to prenatal care.17 One of the largest methadone treatment clinics in the San Antonio, TX, area is the Center for Health Care Services (CHCS). University Health System in San Antonio (UHS) has established a clinic called The Mommies Program, where mothers addicted to opioids can receive prenatal care by a dedicated physician, registered nurse, and a certified nurse midwife, who work in collaboration with the CHCS methadone clinic. Pregnant patients with OUD in pregnancy are concurrently enrolled in the Mommies Program and receive prenatal care through UHS and methadone treatment and counseling through CHCS. The continuity effort aims to increase prenatal care rates and adherence to methadone treatment.
Once mothers are off illicit opioids and on methadone, it is essential to discuss breastfeeding with them, as many mothers addicted to illicit opioids may have been told that they should not be breastfeeding. However, breastfeeding should be encouraged in women who are stable on methadone if they are not using illicit drugs and do not have other contraindications, regardless of maternal methadone dose, since the transfer of methadone into breast milk is minimal.18-20 Breastfeeding is beneficial in women taking methadone and has been associated with decreased severity of NAS symptoms, decreased need for pharmacotherapy, and a shorter hospital stay for the baby.21 In addition, breastfeeding contributes to the development of an attachment between mother and infant, while also providing the infant with natural immunity. Women should be counseled about the need to stop breastfeeding in the event of a relapse.22
Finally, the postpartum period represents a time of increased stressors, such as loss of sleep, child protective services involvement, and frustration with constant demands from new baby. For mothers with addiction, this is an especially sensitive time, as the stressors may be exacerbated by their new sobriety and a sudden end to the motivation they experienced from pregnancy.23 Therefore, early and frequent postpartum care with methadone dose evaluation is essential in order to decrease drug relapse and screen for postpartum depression in detail, since patients with a history of drug use are at increased risk of postpartum depression.
In 2017 medical students at UT Health Long School of Medicine in San Antonio created a project to educate women about OUD in pregnancy and provide motivational incentives for sustained abstinence; this project has continued each year since. Students provide education about methadone treatment and the dangers of using illicit opioids during and after pregnancy. Students especially focus on educating patients on the key problem areas in the literature, such as overdose, NAS, breastfeeding, postpartum substance use, and postpartum depression.
Methods
From October 2018 to February 2020, a total of 15 medical students volunteered between 1 and 20 times at the Mommies Program clinic, which was held once or twice per week from 8
The only inclusion criteria for participating in the educational intervention and survey was participants had to be 18 years of age or older and enrolled in the Mommies Program. Patients who met the inclusion criteria and agreed to participate completed a pre-survey administered by the students during the patient’s initial prenatal visit (Figure 2). This survey collected baseline information about the patient’s history with opioid use and their current knowledge of methadone treatment, NAS, legal aspects of drug use disclosure, and drug testing prior to the education portion of the encounter. After the pre-survey was administered, students spent 30 minutes reviewing the correct answers of the survey with the patients by utilizing the standardized handout to help patients understand details of methadone and opioid use in pregnancy (Figure 1). The post-survey was administered by a student once patients entered the third trimester to assess whether the education session increased patients’ knowledge of these topics.
At the time patients completed the post-survey, they received a Baby Bag as well as education regarding each item in the bag. The aim of distributing Baby Bags was to relieve some possible postnatal stressors and educate the patients about infant care. Items included in the bag were diapers, wipes, bottles, clothes, and swaddles. Prenatal vitamins were added in January 2020, as many patients struggle to afford vitamins if they are not currently covered by Medicaid or have other barriers. The Baby Bag items were purchased through a Community Service Learning grant through UT Health San Antonio.
Results
Of 68 women enrolled in the Mommies Program during the intervention period, 33 completed the pre-survey and the post-survey (48.5%). Even though all patients enrolled in the program met the inclusion criteria, patients were not included in the educational program for multiple reasons, including refusal to participate, poor clinic follow-up, or lack of students to collect surveys. However, all patients who completed the pre-survey did complete the post-survey. In the pre-survey, only 39% of participants knew it was safe to breastfeed while on methadone. In the post-survey, 97% knew it safe to breastfeed. Nearly half (48%) reported being very motivated to quit opioids before pregnancy, but 85% were very motivated to quit once pregnant. In the pre-survey, 76% incorrectly thought they would be reported to authorities by their health providers if they used illegal drugs during pregnancy, while in the post-survey, 100% knew they would not be reported for doing so. Also, all participants said learning more about the effects of opiates would increase motivation for sobriety.
Discussion
Questions assessed during the educational surveys revolved around patients’ knowledge of the intricacies, legally and physiologically, of methadone treatment for OUD, as well as beneficial aspects for patients and future child health, such as breastfeeding and motivation to quit and stay sober.
It was clear that there was a lack of knowledge and education about breastfeeding, as only 39% of the participants thought that it was safe to breastfeed while on methadone in the pre-survey; in the post survey, this improved to 97%. Students spent a large portion of the educational time going over the safety of breastfeeding for patients on methadone and the many benefits to mother and baby. Students also reviewed breastfeeding with patients every time patients came in for a visit and debunked any falsehoods about the negatives of breastfeeding while on methadone. This is another testament to the benefits of reinforcement around patient education.
The area of trust between provider and patient is essential in all provider-patient relationships. However, in the area of addiction, a trusting bond is especially important, as patients must feel confident and comfortable to disclose every aspect of their lives so the provider can give the best care. It was clear from our initial data that many patients did not feel this trust or understand the legal aspects regarding the provider-patient relationship in the terms of drug use, as the pre-survey shows 76% of patients originally thought they would be reported to authorities if they told their provider they used illegal drugs during pregnancy. This was an enormous issue in the clinic and something that needed to be addressed because, based on these data, we feared many patients would not be honest about using illegal drugs to supplement their methadone if they believed they would be reported to the authorities or even jailed. The medical student education team continually assured patients that their honesty about illegal drug use during pregnancy would not be revealed to the authorities, and also made it clear to patients that it was essential they were honest about illegal drug use so the optimal care could be provided by the team. These discussions were successful, as the post-survey showed that 100% of patients knew they would not be reported to the authorities if they used illegal drugs during the pregnancy. This showed an increase in knowledge, but also suggested an increase in confidence in the provider-patient relationship by patients, which we speculate allowed for a better patient experience, better patient outcomes, and less emotional stress for the patient and provider.
Last, we wanted to study and address the motivation to quit using drugs and stay sober through learning about the effects of opiates and how this motivation was related to pregnancy. A study by Mitchell et al makes clear that pregnancy is a motivation to seek treatment for drug use and to quit,24 and our survey data support these findings, with 48% of patients motivated to quit before they were pregnant and 85% motivated to quit once they knew they were pregnant. In addition, all patients attested on the pre- and post-survey that learning more about opioids would increase their motivation for sobriety. Therefore, we believe education about the use of opioids and other drugs is a strong motivation towards sobriety and should be further studied in methadone treatment and other drugs as well.
We will continue to focus on sobriety postpartum by using the education in pregnancy as a springboard to further postpartum education, as education seems to be very beneficial to future sobriety. In the future, we believe extending the educational program past pregnancy and discussing opioid use and addiction with patients at multiple follow-up visits will be beneficial to patients’ sobriety.
We faced 2 main challenges in implementing this intervention and survey: patients would often miss multiple appointments during their third trimester or would not attend their postpartum visit if they only had 1 prenatal visit; and many clinic sessions had low student attendance because students often had many other responsibilities in medical school and there were only 15 volunteers over the study time. These challenges decreased our post-survey completion rate. However, there has been improvement in follow-up as the project has continued. The Mommies Program now has a full-time registered nurse, and a larger number of medical student teachers have volunteered to attend the clinic. In the future, we aim to increase awareness of our project and the benefits of participation, expand advertising at our medical school to increase student participation, and increase follow-up education in the postpartum period.
Another future direction is to include local, free doula services, which are offered through Catholic Charities in San Antonio. Doulas provide antepartum, intrapartum, and postpartum services, which we believe will help our patients through advocacy and support for sobriety during this emotional and stressful time.
Conclusion
Counseled participants were receptive to learning about the effects of OUD and methadone on themselves and their newborn. Participants unanimously stated that learning more about OUD increased their motivation for sobriety. It was also clear that the increased motivation to be sober during pregnancy, as compared to before pregnancy, is an opportunity to help these women take steps to get sober. Patients also advanced their breastfeeding knowledge, as we helped debunk falsehoods surrounding breastfeeding while on methadone, and we anticipate this will lead to greater breastfeeding rates for our patients on methadone, although this was not specifically studied. Finally, patients learned about patient-provider confidentiality, which allowed for more open and clear communication with patients so they could be cared for to the greatest degree and trust could remain paramount.
Drug use is a common problem in the health care system, and exposure to patients with addiction is important for medical students in training. We believe that attending the Mommies Program allowed medical students to gain exposure and skills to better help patients with OUD.
Corresponding author: Nicholas Stansbury, MD, Nmstansbury85@gmail.com.
Financial disclosures: None.
From the UT Health Long School of Medicine San Antonio, Texas.
Abstract
Objective: To educate pregnant patients with opioid use disorder (OUD) about the effects of opioids in order to improve understanding and help achieve sustained abstinence.
Methods: The Center for Health Care Services and University Hospital System (UHS) in San Antonio, TX, jointly o
Results: Of 68 women enrolled in the program, 33 completed both the pre-survey and the post-survey (48.5%). Nearly half (48%) were very motivated to quit before pregnancy, but 85% were very motivated to quit once pregnant. All participants said learning more about the effects of opiates would increase motivation for sobriety. Prior to the educational intervention, 39% of participants knew it was safe to breastfeed on methadone, which improved to 97% in the post-survey, and 76% incorrectly thought they would be reported to authorities by their health care providers if they used illegal drugs during pregnancy, while in the post-survey, 100% knew they would not be reported for doing so.
Conclusion: Pregnancy and education about opioids increased patients’ motivation to quit. Patients also advanced their breastfeeding knowledge and learned about patient-provider confidentiality. Our greatest challenge was participant follow-up; however, this improved with the help of a full-time Mommies Program nurse. Our future aim is to increase project awareness and extend the educational research.
Keywords: pregnancy; addiction; opioids; OUD; counseling.
In 2012 more than 259 million prescriptions for opioids were written in the United States, which was a 200% increase since 1998.1 Since the early 2000s, admissions to opioid substance abuse programs and the death rate from opioids have quadrupled.2-4 Specifically, the rate of heroin use increased more than 300% from 2010 to 2014.5 Opioid use in pregnancy has also escalated in recent years, with a 3- to 4-fold increase from 2000 to 2009 and with 4 in 1000 deliveries being complicated by opioid use disorder (OUD) in 2011.6-8
Between 2000 and 2014, the maternal mortality rate in the United States increased 24%, making it the only industrialized nation with a maternal mortality rate that is rising rather than falling.9 The Texas Maternal Mortality and Morbidity Task Force found that between 2012 and 2015 drug overdose was the leading cause of maternal death in the period from delivery to 365 days postpartum, and it has increased dramatically since 2010.10,11
In addition, maternal mortality reviews in several states have identified substance use as a major risk factor for pregnancy-associated deaths.12,13 In Texas between 2012 and 2015, opioids were found in 58% of maternal drug overdoses.10 In 2007, 22.8% of women who were enrolled in Medicaid programs in 46 states filled an opioid prescription during pregnancy.14 Additionally, the rising prevalence of opioid use in pregnancy has led to a sharp increase in neonatal abstinence syndrome (NAS), rising from 1.5 cases per 1000 hospital births in 1999 to 6.0 per 1000 hospital births in 2013.15 Unsurprisingly, states with the highest rates of opioid prescribing also have the highest rates of NAS.16
Methadone combined with counseling and behavioral therapy has been the standard of care for the treatment of OUD in pregnancy since the 1970s. Methadone treatment prevents opioid withdrawal symptoms and increases adherence to prenatal care.17 One of the largest methadone treatment clinics in the San Antonio, TX, area is the Center for Health Care Services (CHCS). University Health System in San Antonio (UHS) has established a clinic called The Mommies Program, where mothers addicted to opioids can receive prenatal care by a dedicated physician, registered nurse, and a certified nurse midwife, who work in collaboration with the CHCS methadone clinic. Pregnant patients with OUD in pregnancy are concurrently enrolled in the Mommies Program and receive prenatal care through UHS and methadone treatment and counseling through CHCS. The continuity effort aims to increase prenatal care rates and adherence to methadone treatment.
Once mothers are off illicit opioids and on methadone, it is essential to discuss breastfeeding with them, as many mothers addicted to illicit opioids may have been told that they should not be breastfeeding. However, breastfeeding should be encouraged in women who are stable on methadone if they are not using illicit drugs and do not have other contraindications, regardless of maternal methadone dose, since the transfer of methadone into breast milk is minimal.18-20 Breastfeeding is beneficial in women taking methadone and has been associated with decreased severity of NAS symptoms, decreased need for pharmacotherapy, and a shorter hospital stay for the baby.21 In addition, breastfeeding contributes to the development of an attachment between mother and infant, while also providing the infant with natural immunity. Women should be counseled about the need to stop breastfeeding in the event of a relapse.22
Finally, the postpartum period represents a time of increased stressors, such as loss of sleep, child protective services involvement, and frustration with constant demands from new baby. For mothers with addiction, this is an especially sensitive time, as the stressors may be exacerbated by their new sobriety and a sudden end to the motivation they experienced from pregnancy.23 Therefore, early and frequent postpartum care with methadone dose evaluation is essential in order to decrease drug relapse and screen for postpartum depression in detail, since patients with a history of drug use are at increased risk of postpartum depression.
In 2017 medical students at UT Health Long School of Medicine in San Antonio created a project to educate women about OUD in pregnancy and provide motivational incentives for sustained abstinence; this project has continued each year since. Students provide education about methadone treatment and the dangers of using illicit opioids during and after pregnancy. Students especially focus on educating patients on the key problem areas in the literature, such as overdose, NAS, breastfeeding, postpartum substance use, and postpartum depression.
Methods
From October 2018 to February 2020, a total of 15 medical students volunteered between 1 and 20 times at the Mommies Program clinic, which was held once or twice per week from 8
The only inclusion criteria for participating in the educational intervention and survey was participants had to be 18 years of age or older and enrolled in the Mommies Program. Patients who met the inclusion criteria and agreed to participate completed a pre-survey administered by the students during the patient’s initial prenatal visit (Figure 2). This survey collected baseline information about the patient’s history with opioid use and their current knowledge of methadone treatment, NAS, legal aspects of drug use disclosure, and drug testing prior to the education portion of the encounter. After the pre-survey was administered, students spent 30 minutes reviewing the correct answers of the survey with the patients by utilizing the standardized handout to help patients understand details of methadone and opioid use in pregnancy (Figure 1). The post-survey was administered by a student once patients entered the third trimester to assess whether the education session increased patients’ knowledge of these topics.
At the time patients completed the post-survey, they received a Baby Bag as well as education regarding each item in the bag. The aim of distributing Baby Bags was to relieve some possible postnatal stressors and educate the patients about infant care. Items included in the bag were diapers, wipes, bottles, clothes, and swaddles. Prenatal vitamins were added in January 2020, as many patients struggle to afford vitamins if they are not currently covered by Medicaid or have other barriers. The Baby Bag items were purchased through a Community Service Learning grant through UT Health San Antonio.
Results
Of 68 women enrolled in the Mommies Program during the intervention period, 33 completed the pre-survey and the post-survey (48.5%). Even though all patients enrolled in the program met the inclusion criteria, patients were not included in the educational program for multiple reasons, including refusal to participate, poor clinic follow-up, or lack of students to collect surveys. However, all patients who completed the pre-survey did complete the post-survey. In the pre-survey, only 39% of participants knew it was safe to breastfeed while on methadone. In the post-survey, 97% knew it safe to breastfeed. Nearly half (48%) reported being very motivated to quit opioids before pregnancy, but 85% were very motivated to quit once pregnant. In the pre-survey, 76% incorrectly thought they would be reported to authorities by their health providers if they used illegal drugs during pregnancy, while in the post-survey, 100% knew they would not be reported for doing so. Also, all participants said learning more about the effects of opiates would increase motivation for sobriety.
Discussion
Questions assessed during the educational surveys revolved around patients’ knowledge of the intricacies, legally and physiologically, of methadone treatment for OUD, as well as beneficial aspects for patients and future child health, such as breastfeeding and motivation to quit and stay sober.
It was clear that there was a lack of knowledge and education about breastfeeding, as only 39% of the participants thought that it was safe to breastfeed while on methadone in the pre-survey; in the post survey, this improved to 97%. Students spent a large portion of the educational time going over the safety of breastfeeding for patients on methadone and the many benefits to mother and baby. Students also reviewed breastfeeding with patients every time patients came in for a visit and debunked any falsehoods about the negatives of breastfeeding while on methadone. This is another testament to the benefits of reinforcement around patient education.
The area of trust between provider and patient is essential in all provider-patient relationships. However, in the area of addiction, a trusting bond is especially important, as patients must feel confident and comfortable to disclose every aspect of their lives so the provider can give the best care. It was clear from our initial data that many patients did not feel this trust or understand the legal aspects regarding the provider-patient relationship in the terms of drug use, as the pre-survey shows 76% of patients originally thought they would be reported to authorities if they told their provider they used illegal drugs during pregnancy. This was an enormous issue in the clinic and something that needed to be addressed because, based on these data, we feared many patients would not be honest about using illegal drugs to supplement their methadone if they believed they would be reported to the authorities or even jailed. The medical student education team continually assured patients that their honesty about illegal drug use during pregnancy would not be revealed to the authorities, and also made it clear to patients that it was essential they were honest about illegal drug use so the optimal care could be provided by the team. These discussions were successful, as the post-survey showed that 100% of patients knew they would not be reported to the authorities if they used illegal drugs during the pregnancy. This showed an increase in knowledge, but also suggested an increase in confidence in the provider-patient relationship by patients, which we speculate allowed for a better patient experience, better patient outcomes, and less emotional stress for the patient and provider.
Last, we wanted to study and address the motivation to quit using drugs and stay sober through learning about the effects of opiates and how this motivation was related to pregnancy. A study by Mitchell et al makes clear that pregnancy is a motivation to seek treatment for drug use and to quit,24 and our survey data support these findings, with 48% of patients motivated to quit before they were pregnant and 85% motivated to quit once they knew they were pregnant. In addition, all patients attested on the pre- and post-survey that learning more about opioids would increase their motivation for sobriety. Therefore, we believe education about the use of opioids and other drugs is a strong motivation towards sobriety and should be further studied in methadone treatment and other drugs as well.
We will continue to focus on sobriety postpartum by using the education in pregnancy as a springboard to further postpartum education, as education seems to be very beneficial to future sobriety. In the future, we believe extending the educational program past pregnancy and discussing opioid use and addiction with patients at multiple follow-up visits will be beneficial to patients’ sobriety.
We faced 2 main challenges in implementing this intervention and survey: patients would often miss multiple appointments during their third trimester or would not attend their postpartum visit if they only had 1 prenatal visit; and many clinic sessions had low student attendance because students often had many other responsibilities in medical school and there were only 15 volunteers over the study time. These challenges decreased our post-survey completion rate. However, there has been improvement in follow-up as the project has continued. The Mommies Program now has a full-time registered nurse, and a larger number of medical student teachers have volunteered to attend the clinic. In the future, we aim to increase awareness of our project and the benefits of participation, expand advertising at our medical school to increase student participation, and increase follow-up education in the postpartum period.
Another future direction is to include local, free doula services, which are offered through Catholic Charities in San Antonio. Doulas provide antepartum, intrapartum, and postpartum services, which we believe will help our patients through advocacy and support for sobriety during this emotional and stressful time.
Conclusion
Counseled participants were receptive to learning about the effects of OUD and methadone on themselves and their newborn. Participants unanimously stated that learning more about OUD increased their motivation for sobriety. It was also clear that the increased motivation to be sober during pregnancy, as compared to before pregnancy, is an opportunity to help these women take steps to get sober. Patients also advanced their breastfeeding knowledge, as we helped debunk falsehoods surrounding breastfeeding while on methadone, and we anticipate this will lead to greater breastfeeding rates for our patients on methadone, although this was not specifically studied. Finally, patients learned about patient-provider confidentiality, which allowed for more open and clear communication with patients so they could be cared for to the greatest degree and trust could remain paramount.
Drug use is a common problem in the health care system, and exposure to patients with addiction is important for medical students in training. We believe that attending the Mommies Program allowed medical students to gain exposure and skills to better help patients with OUD.
Corresponding author: Nicholas Stansbury, MD, Nmstansbury85@gmail.com.
Financial disclosures: None.
1. Centers for Disease Control and Prevention. Opioid painkiller prescribing: where you live makes a difference. CDC website. www.cdc.gov/vitalsigns/opioid-prescribing. Accessed October 28, 2020.
2. Substance Abuse and Mental Health Services Administration. Drug Abuse Warning Network, 2011: national estimates of drug-related emergency department visits. HHS Publication No. (SMA) 13-4760, DAWN Series D-39. Rockville (MD): SAMHSA; 2013. www.samhsa.gov/data/sites/default/files/DAWN2k11ED/DAWN2k11ED/DAWN2k11ED.pdf. Accessed October 28, 2020.
3. Compton WM, Jones CM, Baldwin GT. Relationship between nonmedical prescription-opioid use and heroin use. N Engl J Med. 2016;374:154-63.
4. National Center for Health Statistics. NCHS data on drug-poisoning deaths. NCHS Factsheet. https://www.cdc.gov/nchs/data/factsheets/factsheet-drug-poisoning-H.pdf. Accessed October 28, 2020.
5. National Institute on Drug Abuse. America’s addiction to opioids: heroin and prescription drug abuse. Bethesda (MD): NIDA; 2014. www.drugabuse.gov/about-nida/legislative-activities/testimony-to-congress/2016/americas-addiction-to-opioids-heroin-prescription-drug-abuse. Accessed October 28, 2020.
6. Substance Abuse and Mental Health Services Administration (SAMHSA). Results from the 2010 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: SAMHSA, 2011 Contract No.: HHS Publication no. (SMA) 11–4658.
7. Maeda A, Bateman BT, Clancy CR, et al. Opioid abuse and dependence during pregnancy: temporal trends and obstetrical outcomes. Anesthesiology. 2014;121:1158-1165.
8. Whiteman VE, Salemi JL, Mogos MF, et al. Maternal opioid drug use during pregnancy and its impact on perinatal morbidity, mortality, and the costs of medical care in the United States. J Pregnancy. 2014;2014:1-8
9. Pregnancy Mortality Surveillance System. www.cdc.gov/reproductivehealth/maternal-mortality/pregnancy-mortality-surveillance-system.htm#trends. Accessed February 4, 2020.
10. Macdorman MF, Declercq E, Cabral H, Morton C. Recent increases in the U.S. maternal mortality rate. Obstet Gynecol. 2016;128:447-455.
11. Texas Health and Human Services. Maternal Mortality and Morbidity Task Force and Department of State Health Services Joint Biennial Report, September 2018. www.dshs.texas.gov/legislative/2018-Reports/MMMTFJointReport2018.pdf
12. Virginia Department of Health. Pregnancy-associated deaths from drug overdose in Virginia, 1999-2007: a report from the Virginia Maternal Mortality Review Team. Richmond, VA: VDH; 2015. www.vdh.virginia.gov/content/uploads/sites/18/2016/04/Final-Pregnancy-Associated-Deaths-Due-to-Drug-Overdose.pdf. Accessed October 28, 2020.
13. Maryland Department of Health and Mental Hygiene. Maryland maternal mortality review 2016 annual report. Baltimore: DHMH; 2016. https://phpa.health.maryland.gov/Documents/Maryland-Maternal-Mortality-Review-2016-Report.pdf. Accessed October 28, 2020.
14. Desai RJ, Hernandez-Diaz S, Bateman BT, Huybrechts KF. Increase in prescription opioid use during pregnancy among Medicaid-enrolled women. Obstet Gynecol. 2014;123:997-1002.
15. Reddy UM, Davis JM, Ren Z, et al. Opioid use in pregnancy, neonatal abstinence syndrome, and childhood outcomes. Obstet Gynecol Survey. 2017;72:703-705.
16. Patrick SW, Davis MM, Lehmann CU, Cooper WO. Increasing incidence and geographic distribution of neonatal abstinence syndrome: United States 2009 to 2012. J Perinatol. 2015;35:650-655.
17. Center for Substance Abuse Treatment. Medication-assisted treatment for opioid addiction during pregnancy. In: Medication-assisted treatment for opioid addiction in opioid treatment programs. Treatment Improvement Protocol (TIP) Series, No. 43. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2005:211-224.
18. Wojnar-Horton RE, Kristensen JH, Yapp P, et al. Methadone distribution and excretion into breast milk of clients in a methadone maintenance programme. Br J Clin Pharmacol. 1997;44:543-547.
19. Reece-Stremtan S, Marinelli KA. ABM clinical protocol #21: guidelines for breastfeeding and substance use or substance use disorder, revised 2015. Breastfeed Med. 2015;10:135-141.
20. Sachs HC. The transfer of drugs and therapeutics into human breast milk: an update on selected topics. Committee on Drugs. Pediatrics. 2013;132:e796-809.
21. Bagley SM, Wachman EM, Holland E, Brogly SB. Review of the assessment and management of neonatal abstinence syndrome. Addict Sci Clin Pract. 2014;9:19.
22. Opioid use and opioid use disorder in pregnancy. Committee Opinion No. 711. Obstet Gynecol. 2017;130:488-489.
23. Gopman S. Prenatal and postpartum care of women with substance use disorders. Obstet Gynecol Clin North Am. 2014;41:213-228.
24. Mitchell M, Severtson S, Latimer W. Pregnancy and race/ethnicity as predictors of motivation for drug treatment. Am J Drug Alcohol Abuse. 2008;34:397-404.
1. Centers for Disease Control and Prevention. Opioid painkiller prescribing: where you live makes a difference. CDC website. www.cdc.gov/vitalsigns/opioid-prescribing. Accessed October 28, 2020.
2. Substance Abuse and Mental Health Services Administration. Drug Abuse Warning Network, 2011: national estimates of drug-related emergency department visits. HHS Publication No. (SMA) 13-4760, DAWN Series D-39. Rockville (MD): SAMHSA; 2013. www.samhsa.gov/data/sites/default/files/DAWN2k11ED/DAWN2k11ED/DAWN2k11ED.pdf. Accessed October 28, 2020.
3. Compton WM, Jones CM, Baldwin GT. Relationship between nonmedical prescription-opioid use and heroin use. N Engl J Med. 2016;374:154-63.
4. National Center for Health Statistics. NCHS data on drug-poisoning deaths. NCHS Factsheet. https://www.cdc.gov/nchs/data/factsheets/factsheet-drug-poisoning-H.pdf. Accessed October 28, 2020.
5. National Institute on Drug Abuse. America’s addiction to opioids: heroin and prescription drug abuse. Bethesda (MD): NIDA; 2014. www.drugabuse.gov/about-nida/legislative-activities/testimony-to-congress/2016/americas-addiction-to-opioids-heroin-prescription-drug-abuse. Accessed October 28, 2020.
6. Substance Abuse and Mental Health Services Administration (SAMHSA). Results from the 2010 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: SAMHSA, 2011 Contract No.: HHS Publication no. (SMA) 11–4658.
7. Maeda A, Bateman BT, Clancy CR, et al. Opioid abuse and dependence during pregnancy: temporal trends and obstetrical outcomes. Anesthesiology. 2014;121:1158-1165.
8. Whiteman VE, Salemi JL, Mogos MF, et al. Maternal opioid drug use during pregnancy and its impact on perinatal morbidity, mortality, and the costs of medical care in the United States. J Pregnancy. 2014;2014:1-8
9. Pregnancy Mortality Surveillance System. www.cdc.gov/reproductivehealth/maternal-mortality/pregnancy-mortality-surveillance-system.htm#trends. Accessed February 4, 2020.
10. Macdorman MF, Declercq E, Cabral H, Morton C. Recent increases in the U.S. maternal mortality rate. Obstet Gynecol. 2016;128:447-455.
11. Texas Health and Human Services. Maternal Mortality and Morbidity Task Force and Department of State Health Services Joint Biennial Report, September 2018. www.dshs.texas.gov/legislative/2018-Reports/MMMTFJointReport2018.pdf
12. Virginia Department of Health. Pregnancy-associated deaths from drug overdose in Virginia, 1999-2007: a report from the Virginia Maternal Mortality Review Team. Richmond, VA: VDH; 2015. www.vdh.virginia.gov/content/uploads/sites/18/2016/04/Final-Pregnancy-Associated-Deaths-Due-to-Drug-Overdose.pdf. Accessed October 28, 2020.
13. Maryland Department of Health and Mental Hygiene. Maryland maternal mortality review 2016 annual report. Baltimore: DHMH; 2016. https://phpa.health.maryland.gov/Documents/Maryland-Maternal-Mortality-Review-2016-Report.pdf. Accessed October 28, 2020.
14. Desai RJ, Hernandez-Diaz S, Bateman BT, Huybrechts KF. Increase in prescription opioid use during pregnancy among Medicaid-enrolled women. Obstet Gynecol. 2014;123:997-1002.
15. Reddy UM, Davis JM, Ren Z, et al. Opioid use in pregnancy, neonatal abstinence syndrome, and childhood outcomes. Obstet Gynecol Survey. 2017;72:703-705.
16. Patrick SW, Davis MM, Lehmann CU, Cooper WO. Increasing incidence and geographic distribution of neonatal abstinence syndrome: United States 2009 to 2012. J Perinatol. 2015;35:650-655.
17. Center for Substance Abuse Treatment. Medication-assisted treatment for opioid addiction during pregnancy. In: Medication-assisted treatment for opioid addiction in opioid treatment programs. Treatment Improvement Protocol (TIP) Series, No. 43. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2005:211-224.
18. Wojnar-Horton RE, Kristensen JH, Yapp P, et al. Methadone distribution and excretion into breast milk of clients in a methadone maintenance programme. Br J Clin Pharmacol. 1997;44:543-547.
19. Reece-Stremtan S, Marinelli KA. ABM clinical protocol #21: guidelines for breastfeeding and substance use or substance use disorder, revised 2015. Breastfeed Med. 2015;10:135-141.
20. Sachs HC. The transfer of drugs and therapeutics into human breast milk: an update on selected topics. Committee on Drugs. Pediatrics. 2013;132:e796-809.
21. Bagley SM, Wachman EM, Holland E, Brogly SB. Review of the assessment and management of neonatal abstinence syndrome. Addict Sci Clin Pract. 2014;9:19.
22. Opioid use and opioid use disorder in pregnancy. Committee Opinion No. 711. Obstet Gynecol. 2017;130:488-489.
23. Gopman S. Prenatal and postpartum care of women with substance use disorders. Obstet Gynecol Clin North Am. 2014;41:213-228.
24. Mitchell M, Severtson S, Latimer W. Pregnancy and race/ethnicity as predictors of motivation for drug treatment. Am J Drug Alcohol Abuse. 2008;34:397-404.
Improving Primary Care Fall Risk Management: Adoption of Practice Changes After a Geriatric Mini-Fellowship
From the Senior Health Program, Providence Health & Services, Oregon, Portland, OR.
Abstract
Background: Approximately 51 million adults in the United States are 65 years of age or older, yet few geriatric-trained primary care providers (PCP) serve this population. The Age-Friendly Health System framework, consisting of evidence-based 4M care (Mobility, Medication, Mentation, and what Matters), encourages all PCPs to assess mobility in older adults.
Objective: To improve PCP knowledge, confidence, and clinical practice in assessing and managing fall risk.
Methods: A 1-week educational session focusing on mobility (part of a 4-week Geriatric Mini-Fellowship) for 6 selected PCPs from a large health care system was conducted to increase knowledge and ability to address fall risk in older adults. The week included learning and practicing a Fall Risk Management Plan (FRMP) algorithm, including planning for their own practice changes. Pre- and post-test surveys assessed changes in knowledge and confidence. Patient data were compared 12 months before and after training to evaluate PCP adoption of FRMP components.
Results: The training increased provider knowledge and confidence. The trained PCPs were 1.7 times more likely to screen for fall risk; 3.6 times more likely to discuss fall risk; and 5.8 times more likely to assess orthostatic blood pressure in their 65+ patients after the mini-fellowship. In high-risk patients, they were 4.1 times more likely to discuss fall risk and 6.3 times more likely to assess orthostatic blood pressure than their nontrained peers. Changes in physical therapy referral rates were not observed.
Conclusions: In-depth, skills-based geriatric educational sessions improved PCPs’ knowledge and confidence and also improved their fall risk management practices for their older patients.
Keywords: geriatrics; guidelines; Age-Friendly Health System; 4M; workforce training; practice change; fellowship.
The US population is aging rapidly. People aged 85 years and older are the largest-growing segment of the US population, and this segment is expected to increase by 123% by 2040.1 Caregiving needs increase with age as older adults develop more chronic conditions, such as hypertension, heart disease, arthritis, and dementia. However, even with increasing morbidity and dependence, a majority of older adults still live in the community rather than in institutional settings.2 These older adults seek medical care more frequently than younger people, with about 22% of patients 75 years and older having 10 or more health care visits in the previous 12 months. By 2040, nearly a quarter of the US population is expected to be 65 or older, with many of these older adults seeking regular primary care from providers who do not have formal training in the care of a population with multiple complex, chronic health conditions and increased caregiving needs.1
Despite this growing demand for health care professionals trained in the care of older adults, access to these types of clinicians is limited. In 2018, there were roughly 7000 certified geriatricians, with only 3600 of them practicing full-time.3,4 Similarly, of 290,000 certified nurse practitioners (NPs), about 9% of them have geriatric certification.5 Geriatricians, medical doctors trained in the care of older adults, and geriatric-trained NPs are part of a cadre of a geriatric-trained workforce that provides unique expertise in caring for older adults with chronic and advanced illness. They know how to manage multiple, complex geriatric syndromes like falls, dementia, and polypharmacy; understand and maximize team-based care; and focus on caring for an older person with a goal-centered versus a disease-centered approach.6
Broadly, geriatric care includes a spectrum of adults, from those who are aging healthfully to those who are the frailest. Research has suggested that approximately 30% of older adults need care by a geriatric-trained clinician, with the oldest and frailest patients needing more clinician time for assessment and treatment, care coordination, and coaching of caregivers.7 With this assumption in mind, it is projected that by 2025, there will be a national shortage of 26,980 geriatricians, with the western United States disproportionately affected by this shortage.4Rather than lamenting this shortage, Tinetti recommends a new path forward: “Our mission should not be to train enough geriatricians to provide direct care, but rather to ensure that every clinician caring for older adults is competent in geriatric principles and practices.”8 Sometimes called ”geriatricizing,” the idea is to use existing geriatric providers as a small elite training force to infuse geriatric principles and skills across their colleagues in primary care and other disciplines.8,9 Efforts of the American Geriatrics Society (AGS), with support from the John A. Hartford Foundation (JAHF), have been successful in developing geriatric training across multiple specialties, including surgery, orthopedics, and emergency medicine (www.americangeriatrics.org/programs/geriatrics-specialists-initiative).
The Age-Friendly Health System and 4M Model
To help augment this idea of equipping health care systems and their clinicians with more readily available geriatric knowledge, skills, and tools, the JAHF, along with the Institute for Healthcare Improvement (IHI), created the Age-Friendly Health System (AFHS) paradigm in 2015.10 Using the 4M model, the AFHS initiative established a set of evidence-based geriatric priorities and interventions meant to improve the care of older adults, reduce harm and duplication, and provide a framework for engaging leadership, clinical teams, and operational systems across inpatient and ambulatory settings.11 Mobility, including fall risk screening and intervention, is 1 of the 4M foundational elements of the Age-Friendly model. In addition to Mobility, the 4M model also includes 3 other key geriatric domains: Mentation (dementia, depression, and delirium), Medication (high-risk medications, polypharmacy, and deprescribing), and What Matters (goals of care conversations and understanding quality of life for older patients).11 The 4M initiative encourages adoption of a geriatric lens that looks across chronic conditions and accounts for the interplay among geriatric syndromes, such as falls, cognitive impairment, and frailty, in order to provide care better tailored to what the patient needs and desires.12 IHI and JAHF have targeted the adoption of the 4M model by 20% of US health care systems by 2020.11
Mini-Fellowship and Mobility Week
To bolster geriatric skills among community-based primary care providers (PCPs), we initiated a Geriatric Mini-Fellowship, a 4-week condensed curriculum taught over 6 months. Each week focuses on 1 of the age-friendly 4Ms, with the goal of increasing the knowledge, self-efficacy, skills, and competencies of the participating PCPs (called “fellow” hereafter) and at the same time, equipping each to become a champion of geriatric practice. This article focuses on the Mobility week, the second week of the mini-fellowship, and the effect of the week on the fellows’ practice changes.
To construct the Mobility week’s curriculum with a focus on the ambulatory setting, we relied upon national evidence-based work in fall risk management. The Centers for Disease Control and Prevention (CDC) has made fall risk screening and management in primary care a high priority. Using the clinical practice guidelines for managing fall risk developed by the American and British Geriatrics Societies (AGS/BGS), the CDC developed the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) toolkit.13 Foundational to the toolkit is the validated 12-item Stay Independent falls screening questionnaire (STEADI questionnaire).14 Patients who score 4 or higher (out of a total score of 14) on the questionnaire are considered at increased risk of falling. The CDC has developed a clinical algorithm that guides clinical teams through screening and assessment to help identify appropriate interventions to target specific risk factors. Research has clearly established that a multifactorial approach to fall risk intervention can be successful in reducing fall risk by as much as 25%.15-17
The significant morbidity and mortality caused by falls make training nongeriatrician clinicians on how to better address fall risk imperative. More than 25% of older adults fall each year.18 These falls contribute to rising rates of fall-related deaths,19 emergency department (ED) visits,20 and hospital readmissions.21 Initiatives like the AFHS focus on mobility and the CDC’s development of supporting clinical materials22 aim to improve primary care adoption of fall risk screening and intervention practices.23,24 The epidemic of falls must compel all PCPs, not just those practicing geriatrics, to make discussing and addressing fall risk and falls a priority.
Methods
Setting
This project took place as part of a regional primary care effort in Oregon. Providence Health & Services-Oregon is part of a multi-state integrated health care system in the western United States whose PCPs serve more than 80,000 patients aged 65 years and older per year; these patients comprise 38% of the system’s office visits each year. Regionally, there are 47 family and internal medicine clinics employing roughly 290 providers (physicians, NPs, and physician assistants). The organization has only 4 PCPs trained in geriatrics and does not offer any geriatric clinical consultation services. Six PCPs from different clinics, representing both rural and urban settings, are chosen to participate in the geriatric mini-fellowship each year.
This project was conducted as a quality improvement initiative within the organization and did not constitute human subjects research. It was not conducted under the oversight of the Institutional Review Board.
Intervention
The mini-fellowship was taught in 4 1-week blocks between April and October 2018, with a curriculum designed to be interactive and practical. The faculty was intentionally interdisciplinary to teach and model team-based practice. Each week participants were excused from their clinical practice. Approximately 160 hours of continuing medical education credits were awarded for the full mini-fellowship. As part of each weekly session, a performance improvement project (PIP) focused on that week’s topic (1 of the 4Ms) was developed by the fellow and their team members to incorporate the mini-fellowship learnings into their clinic workflows. Fellows also had 2 hours per week of dedicated administration time for a year, outside the fellowship, to work on their PIP and 4M practice changes within their clinic.
Provider Education
The week for mobility training comprised 4 daylong sessions. The first 2 days were spent learning about the epidemiology of falls; risk factors for falling; how to conduct a thorough history and assessment of fall risk; and how to create a prioritized Fall Risk Management Plan (FRMP) to decrease a patient’s individual fall risk through tailored interventions. The FRMP was adapted from the CDC STEADI toolkit.13 Core faculty were 2 geriatric-trained providers (NP and physician) and a physical therapist (PT) specializing in fall prevention.
On the third day, fellows took part in a simulated fall risk clinic, in which older adults volunteered to be patient partners, providing an opportunity to apply learnings from days 1 and 2. The clinic included the fellow observing a PT complete a mobility assessment and a pharmacist conduct a high-risk medication review. The fellow synthesized the findings of the mobility assessment and medication review, as well as their own history and assessment, to create a summary of fall risk recommendations to discuss with their volunteer patient partner. The fellows were observed and evaluated in their skills by their patient partner, course faculty, and another fellow. The patient partners, and their assigned fellow, also participated in a 45-minute fall risk presentation, led by a nurse.
On the fourth day, the fellows were joined by select clinic partners, including nurses, pharmacists, and/or medical assistants. The session included discussions among each fellow’s clinical team regarding the current state of fall risk efforts at their clinic, an analysis of barriers, and identification of opportunities to improve workflows and screening rates. Each fellow took with them an action plan tailored to their clinic to improve fall risk management practices, starting with the fellow’s own practice.
Fall Risk Management Plan
The educational sessions introduced the fellows to the FRMP. The FRMP, adapted from the STEADI toolkit, includes a process for fall risk screening (Figure 1) and stratifying a patient’s risk based on their STEADI score in order to promote 3 priority assessments (gait evaluation with PT referral if appropriate; orthostatic blood pressure; and high-risk medication review; Figure 2). Initial actions based on these priority assessments were followed over time, with additional fall risk interventions added as clinically indicated.25 The FRMP is intended to be used during routine office visits, Medicare annual wellness visits, or office visits focused on fall risk or related medical disorders (ie, fall risk visits.)
Providers and their teams were encouraged to spread out fall-related conversations with their patients over multiple visits, since many patients have multiple fall risk factors at play, in addition to other chronic medical issues, and since many interventions often require behavior changes on the part of the patient. Providers also had access to fall-related electronic health record (EHR) templates as well as a comprehensive, internal fall risk management website that included assessment tools, evidence-based resources, and patient handouts.
Assessment and Measurements
We assessed provider knowledge and comfort in their fall risk evaluation and management skills before and after the educational intervention using an 11-item multiple-choice questionnaire and a 4-item confidence questionnaire. The confidence questions used a 7-point Likert scale, with 0 indicating “no confidence” and 7 indicating ”lots of confidence.” The questions were administered via a paper survey. Qualitative comments were derived from evaluations completed at the end of the week.
The fellows’ practice of fall risk screening and management was studied from May 2018, at the completion of Mobility week, to May 2019 for the post-intervention period. A 1-year timeframe before May 2018 was used as the pre-intervention period. Eligible visit types, during which we assumed fall risk was discussed, were any office visits for patients 65+ completed by the patients’ PCPs that used fall risk as a reason for the visit or had a fall-related diagnosis code. Fall risk visits performed by other clinic providers were not counted.
Of those patients who had fall risk screenings completed and were determined to be high risk (STEADI score ≥ 4), data were analyzed to determine whether these patients had any fall-related follow-up visits to their PCP within 60 days of the STEADI screening. For these high-risk patients, data were studied to understand whether orthostatic blood pressure measurements were performed (as documented in a flowsheet) and whether a PT referral was placed. These data were compared with those from providers who practiced in clinics within the same system but who did not participate in the mini-fellowship. Data were obtained from the organization’s EHR. Additional data were measured to evaluate patterns of deprescribing of select high-risk medications, but these data are not included in this analysis.
Analysis
A paired-samples t test was used to measure changes in provider confidence levels. Data were aggregated across fellows, resulting in a mean. A chi-square test of independence was performed to examine the relationship between rates of FRMP adoption by select provider groups. Analysis included a pre- and post-intervention assessment of the fellows’ adoption of FRMP practices, as well as a comparison between the fellows’ practice patterns and those of a control group of PCPs in the organization’s other clinics who did not participate in the mini-fellowship (nontrained control group). Excluded from the control group were providers from the same clinic as the fellows; providers in clinics with a geriatric-trained provider on staff; and clinics outside of the Portland metro and Medford service areas. We used an alpha level of 0.05 for all statistical tests.
Data from 5 providers were included in the analysis of the FRMP adoption. The sixth provider changed practice settings from the clinic to the ED after completing the fellowship; her patient data were not included in the FRMP part of the analysis. EHR data included data on all visits of patients 65+, as well as data for just those 65+ patients who had been identified as being at high risk to fall based on a STEADI score of 4 or higher.
Results
Provider Questionnaire
All 6 providers responded to the pre-intervention and post-intervention tests. For the knowledge questions, fellows, as a composite, correctly answered 57% of the questions before the intervention and 79% after the intervention. Provider confidence level in delivering fall risk care was measured prior to the training (mean, 4.12 [SD, 0.62]) and at the end of the training (mean, 6.47 [SD, 0.45]), demonstrating a significant increase in confidence (t (5) = –10.46, P < 0.001).
Qualitative Comments
Providers also had the opportunity to provide comments on their experience during the Mobility week and at the end of 1 year. In general, the simulated interdisciplinary fall risk clinic was highly rated (“the highlight of the week”) as a practical strategy to embed learning principles. One fellow commented, “Putting the learning into practice helps solidify it in my brain.” Fellows also appreciated the opportunity to learn and meet with their clinic colleagues to begin work on a fall-risk focused PIP and to “have a framework for what to do for people who screen positive [for fall risk].”
FRMP Adoption
A comparison of the care the fellows provided to their patients 65+ in the 12 months pre- and post-training shows the fellows demonstrated significant changes in practice patterns. The fellows were 1.7 times more likely to screen for fall risk; 3.6 times more likely to discuss fall risk; and 5.8 times more likely to check orthostatic blood pressure than prior to the mini-fellowship (Table 1).
The control providers also demonstrated significant increases in fall risk screening and discussion of fall risk between the pre- and post-intervention periods; however, the relative risk (RR) was between 1.10 and 1.13 for this group. For the control group, checking orthostatic blood pressure did not significantly change. In the 12 months after training (Table 2), the fellows were 4.2 times more likely to discuss fall risk and almost 5 times more likely to check orthostatic blood pressure than their nontrained peers for all of their patients 65+, regardless of their risk to fall.
As shown in Table 3, for those patients determined to be at high risk of falling (STEADI score ≥ 4), fellows showed statistically significant increases in fall risk visits (RR, 3.02) and assessment of orthostatic blood pressure (RR, 10.68) before and after the mini-fellowship. The control providers did not show any changes in practice patterns between the pre- and post-period among patients at high risk to fall.
Neither the fellows nor the control group showed changes in patterns of referral to PT. In comparing the 2 groups in the 12 months after training (Table 4), for their patients at risk of falling, the fellows were 4 times more likely to complete fall risk visits and over 6 times more likely to assess orthostatic blood pressure than their nontrained peers. Subgroup analysis of the 75+ population revealed similar trends and significance, but these results are not included here.
Discussion
This study aimed to improve not only providers’ knowledge and confidence in caring for older adults at increased risk to fall, but also their clinical practice in assessing and managing fall risk. In addition to improved knowledge and confidence, we found that the fellows increased their discussion of fall risk (through fall risk visits) and their assessment of orthostatic blood pressure for all of their patients, not just for those identified at increased risk to fall. This improvement held true for the fellows themselves before and after the intervention, but also as compared to their nontrained peers. These practice improvements for all of their 65+ patients, not just those identified as being at high risk to fall, are especially important, since studies indicate that early screening and intervention can help identify people at risk and prevent future falls.15
We were surprised that there were no significant differences in PT referrals made by the trained fellows, but this finding may have been confounded by the fact that the data included all PT referrals, regardless of diagnosis, not just those referrals that were fall-related. Furthermore, our baseline PT referral rates, at 39% for the intervention group and 42% for the control group, are higher than national data when looking at rehabilitation use by older adults.26
In comparison to a study evaluating the occurrence of fall risk–related clinical practice in primary care before any fall-related educational intervention, orthostatics were checked less frequently in our study (10% versus 30%) and there were fewer PT referrals (42%–44% versus 53%).27 However, the Phelan study took place in patients who had actually had a fall, rather than just having a higher risk for a fall, and was based on detailed chart review. Other studies23,24 found higher rates of fall risk interventions, but did not break out PT referrals specifically.
In terms of the educational intervention itself, most studies of geriatric education interventions have measured changes in knowledge, confidence, or self-efficacy as they relate to geriatric competence,28-30 and do not measure practice change as an outcome outside of intent to change or self-reported practice change.31,32 In general, practice change or longer-term health care–related outcomes have not been studied. Additionally, a range of dosages of educational interventions has been studied, from 1-hour lunchtime presentations23,32 to half-day29 or several half-day workshops,28 up to 160 hours over 10 months30 or 5 weekends over 6 months.31 The duration of our entire intervention at 160 hours over 6 months would be considered on the upper end of dosing relative to these studies, with our Mobility week intervention comprising 32 hours during 1 week. In the Warshaw study, despite 107 1-hour sessions being taught to over 60 physicians in 16 practices over 4 years, only 2 practices ultimately initiated any practice change projects.32 We believe that only curricula that embed practice change skills and opportunities, at a significant enough dose, can actually impact practice change in a sustainable manner.
Knowledge and skill acquisition among individual providers does not take place to a sufficient degree in the current health care arena, which is focused on productivity and short visit times. Consistent with other studies, we included interdisciplinary members of the primary care team for part of the mini-fellowship, although other studies used models that train across disciplines for the entirety of the learning experience.28-30,33 Our educational model was strengthened by including other professionals to provide some of the education and model the ideal geriatric team, including PT, occupational therapy, and pharmacy, for the week on mobility.
Most studies exploring interventions through geriatric educational initiatives are conducted within academic institutions, with a primary focus on physician faculty and, by extension, their teaching of residents and others.34,35 We believe our integrated model, which is steeped in community-based primary care practices like Lam’s,31 offers the greatest outreach to large community-based care systems and their patients. Training providers to work with their teams to change their own practices first gives skills and expertise that help further establish them as geriatric champions within their practices, laying the groundwork for more widespread practice change at their clinics.
Limitations
In addition to the limitations described above relating to the capture of PT referrals, other limitations included the relatively short time period for follow-up data as well as the small size of the intervention group. However, we found value in the instructional depth that the small group size allowed.
While the nontrained providers did show some improvement during the same period, we believe the relative risk was not clinically significant. We suspect that the larger health system efforts to standardize screening of patients 65+ across all clinics as a core quality metric confounded these results. The data analysis also included only fall-related patient visits that occurred with a provider who was that patient’s PCP, which could have missed visits done by other PCP colleagues, RNs, or pharmacists in the same clinic, thus undercounting the true number of fall-related visits. Furthermore, counting of fall-related interventions relied upon providers documenting consistently in the EHR, which could also lead to under-represention of fall risk clinical efforts.
The data presented, while encouraging, do not reflect clinic-wide practice change patterns and are considered only proximate outcomes rather than more long-term or cost-related outcomes, as would be captured by fall-related utilization measures like emergency room visits and hospitalizations. We expect to evaluate the broader impact and these value-based outcomes in the future. All providers and teams were from the same health care system, which may not allow our results to transfer to other organizations or regions of clinical practice.
Summary
This study demonstrates that an intensive mini-fellowship model of geriatrics training improved both knowledge and confidence in the realm of fall risk assessment and intervention among PCPs who had not been formally trained in geriatrics. More importantly, the training improved the fall-related care of their patients at increased risk to fall, but also of all of their older patients, with improvements in care measured up to a year after the mini-fellowship. Although this article only describes the work done as part of the Mobility aim of the 4M AFHS model, we believe the entire mini-fellowship curriculum offers the opportunity to “geriatricize” clinicians and their teams in learning geriatric principles and skills that they can translate into their practice in a sustainable way, as Tinetti encourages.8 Future study to evaluate other process outcomes more precisely, such as PT, as well as cost- and value-based outcomes, and the influence of trained providers on their clinic partners, will further establish the value proposition of targeted, disseminated, intensive geriatrics training of primary care clinicians as a strategy of age-friendly health systems as they work to improve the care of their older adults.
Acknowledgment: We are grateful for the dedication and hard work of the 2018 Geriatric Mini-Fellowship fellows at Providence Health & Services-Oregon who made this article possible. Thanks to Drs. Stephanie Cha, Emily Puukka-Clark, Laurie Dutkiewicz, Cara Ellis, Deb Frost, Jordan Roth, and Subhechchha Shah for promoting the AFHS work within their Providence Medical Group clinics and to PMG leadership and the fellows’ clinical teams for supporting the fellows, the AFHS work, and their older patients.
Corresponding author: Colleen M. Casey, PhD, ANP-BC, Providence Health & Services, Senior Health Program, 4400 NE Halsey, 5th Floor, Portland, OR 97213; colleen.casey@providence.org.
Financial disclosures: None.
1. US Department of Health and Human Services. 2018 Profile of Older Americans. Administration on Aging. April 2018.
2. Roberts AW, Ogunwole SU, Blakeslee L, Rabe MA. The population 65 years and older in the United States: 2016. Washington, DC: US Census Bureau; 2018.
3. American Board of Medicine Specialties. 2017-2018 ABMS Board Certification Report. https://www.abms.org/board-certification/abms-board-certification-report/. Accessed November 3, 2020.
4. US Department of Health and Human Services, Health Resources and Services Administration, National Center for Health Workforce Analysis. National and regional projections of supply and demand for geriatricians: 2013-2025. Rockville, MD: US Department of Health and Human Services; 2007.
5. American Association of Nurse Practitioners, NP Facts: The Voice of the Nurse Practitioner. 2020. https://storage.aanp.org/www/documents/NPFacts__080420.pdf.
6. Tinetti ME, Naik AD, Dodson JA, Moving from disease-centered to patient goals-directed care for patients with multiple chronic conditions: patient value-based care. JAMA Cardiol. 2016;1:9-10.
7. Fried LP, Hall WJ. Editorial: leading on behalf of an aging society. J Am Geriatr Soc. 2008;56:1791-1795.
8. Tinetti M. Mainstream or extinction: can defining who we are save geriatrics? J Am Geriatr Soc. 2016;64:1400-1404.
9. Jafari P, Kostas T, Levine S, et al. ECHO-Chicago Geriatrics: using telementoring to “geriatricize” the primary care workforce. Gerontol Geriatr Educ. 2020;41:333-341.
10. Fulmer T, Mate KS, Berman A. The Age-Friendly Health System imperative. J Am Geriatr Soc. 2018;66:22-24.
11. Mate KS, Berman A, Laderman M, et al. Creating Age-Friendly Health Systems - A vision for better care of older adults. Healthc (Amst). 2018;6:4-6.
12. Tinetti ME, et al. Patient priority-directed decision making and care for older adults with multiple chronic conditions. Clin Geriatr Med. 2016;32:261-275.
13. Stevens JA, Phelan EA. Development of STEADI: a fall prevention resource for health care providers. Health Promot Pract. 2013;14:706-714.
14. Rubenstein LZ, et al. Validating an evidence-based, self-rated fall risk questionnaire (FRQ) for older adults. J Safety Res. 2011;42:493-499.
15. Grossman DC, et al. Interventions to prevent falls in community-dwelling older adults: US Preventive Services Task Force Recommendation Statement. JAMA. 2018;319: 1696-1704.
16. Tricco AC, Thomas SM, Veroniki AA, et al. Comparisons of interventions for preventing falls in older adults: a systematic review and meta-analysis. JAMA. 2017;318:1687-1699.
17. Gillespie LD, Robertson MC, Gillespie WJ, et al. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2012(9):CD007146.
18. Bergen G, Stevens MR, Burns ER. Falls and fall injuries among adults aged ≥65 years - United States, 2014. MMWR Morb Mortal Wkly Rep. 2016;65:993-998.
19. Burns E, Kakara R. Deaths from falls among persons aged >=65 Years - United States, 2007-2016. MMWR Morb Mortal Wkly Rep. 2018;67:509-514.
20. Shankar KN, Liu SW, Ganz DA. Trends and characteristics of emergency department visits for fall-related injuries in older adults, 2003-2010. West J Emerg Med. 2017;18:785-793.
21. Hoffman GJ, et al. Posthospital fall injuries and 30-day readmissions in adults 65 years and older. JAMA Netw Open. 2019;2:e194276.
22. Eckstrom E, Parker EM, Shakya I, Lee R. Coordinated care plan to prevent older adult falls. 2018. Atlanta, GA: National Center for Injury Prevention and Control, Centers for Disease Control and Prevention; 2018.
23. Eckstrom E, Parker EM, Lambert GH, et al. Implementing STEADI in academic primary care to address older adult fall risk. Innov Aging. 2017;1:igx028.
24. Johnston YA, Bergen G, Bauer M, et al. Implementation of the stopping elderly accidents, deaths, and injuries initiative in primary care: an outcome evaluation. Gerontologist. 2019;59:1182-1191.
25. Phelan EA, Mahoney JE, Voit JC, Stevens JA. Assessment and management of fall risk in primary care settings. Med Clin North Am. 2015;99:281-293.
26. Gell NM, Mroz TM, Patel KV. Rehabilitation services use and patient-reported outcomes among older adults in the United States. Arch Phys Med Rehabil. 2017;98:2221-2227.e3.
27. Phelan EA, Aerts S, Dowler D, et al. Adoption of evidence-based fall prevention practices in primary care for older adults with a history of falls. Front Public Health. 2016;4:190.
28. Solberg LB, Carter CS, Solberg LM. Geriatric care boot camp series: interprofessional education for a new training paradigm. Geriatr Nurs. 2019;40:579-583.
29. Solberg LB, Solberg LM, Carter CS. Geriatric care boot cAMP: an interprofessional education program for healthcare professionals. J Am Geriatr Soc. 2015;63:997-1001.
30. Coogle CL, Hackett L, Owens MG, et al. Perceived self-efficacy gains following an interprofessional faculty development programme in geriatrics education. J Interprof Care. 2016;30:483-492.
31. Lam R, Lee L, Tazkarji B, et al. Five-weekend care of the elderly certificate course: continuing professional development activity for family physicians. Can Fam Physician. 2015;61:e135-141.
32. Warshaw GA, Modawal A, Kues J, et al. Community physician education in geriatrics: applying the assessing care of vulnerable elders model with a multisite primary care group. J Am Geriatr Soc. 2010;58:1780-1785.
33. Solai LK, Kumar K, Mulvaney E, et al. Geriatric mental healthcare training: a mini-fellowship approach to interprofessional assessment and management of geriatric mental health issues. Am J Geriatr Psychiatry. 2019;27:706-711.
34. Christmas C, Park E, Schmaltz H, et al. A model intensive course in geriatric teaching for non-geriatrician educators. J Gen Intern Med. 2008;23:1048-1052.
35. Heflin MT, Bragg EJ, Fernandez H, et al. The Donald W. Reynolds Consortium for Faculty Development to Advance Geriatrics Education (FD~AGE): a model for dissemination of subspecialty educational expertise. Acad Med. 2012;87:618-626.
From the Senior Health Program, Providence Health & Services, Oregon, Portland, OR.
Abstract
Background: Approximately 51 million adults in the United States are 65 years of age or older, yet few geriatric-trained primary care providers (PCP) serve this population. The Age-Friendly Health System framework, consisting of evidence-based 4M care (Mobility, Medication, Mentation, and what Matters), encourages all PCPs to assess mobility in older adults.
Objective: To improve PCP knowledge, confidence, and clinical practice in assessing and managing fall risk.
Methods: A 1-week educational session focusing on mobility (part of a 4-week Geriatric Mini-Fellowship) for 6 selected PCPs from a large health care system was conducted to increase knowledge and ability to address fall risk in older adults. The week included learning and practicing a Fall Risk Management Plan (FRMP) algorithm, including planning for their own practice changes. Pre- and post-test surveys assessed changes in knowledge and confidence. Patient data were compared 12 months before and after training to evaluate PCP adoption of FRMP components.
Results: The training increased provider knowledge and confidence. The trained PCPs were 1.7 times more likely to screen for fall risk; 3.6 times more likely to discuss fall risk; and 5.8 times more likely to assess orthostatic blood pressure in their 65+ patients after the mini-fellowship. In high-risk patients, they were 4.1 times more likely to discuss fall risk and 6.3 times more likely to assess orthostatic blood pressure than their nontrained peers. Changes in physical therapy referral rates were not observed.
Conclusions: In-depth, skills-based geriatric educational sessions improved PCPs’ knowledge and confidence and also improved their fall risk management practices for their older patients.
Keywords: geriatrics; guidelines; Age-Friendly Health System; 4M; workforce training; practice change; fellowship.
The US population is aging rapidly. People aged 85 years and older are the largest-growing segment of the US population, and this segment is expected to increase by 123% by 2040.1 Caregiving needs increase with age as older adults develop more chronic conditions, such as hypertension, heart disease, arthritis, and dementia. However, even with increasing morbidity and dependence, a majority of older adults still live in the community rather than in institutional settings.2 These older adults seek medical care more frequently than younger people, with about 22% of patients 75 years and older having 10 or more health care visits in the previous 12 months. By 2040, nearly a quarter of the US population is expected to be 65 or older, with many of these older adults seeking regular primary care from providers who do not have formal training in the care of a population with multiple complex, chronic health conditions and increased caregiving needs.1
Despite this growing demand for health care professionals trained in the care of older adults, access to these types of clinicians is limited. In 2018, there were roughly 7000 certified geriatricians, with only 3600 of them practicing full-time.3,4 Similarly, of 290,000 certified nurse practitioners (NPs), about 9% of them have geriatric certification.5 Geriatricians, medical doctors trained in the care of older adults, and geriatric-trained NPs are part of a cadre of a geriatric-trained workforce that provides unique expertise in caring for older adults with chronic and advanced illness. They know how to manage multiple, complex geriatric syndromes like falls, dementia, and polypharmacy; understand and maximize team-based care; and focus on caring for an older person with a goal-centered versus a disease-centered approach.6
Broadly, geriatric care includes a spectrum of adults, from those who are aging healthfully to those who are the frailest. Research has suggested that approximately 30% of older adults need care by a geriatric-trained clinician, with the oldest and frailest patients needing more clinician time for assessment and treatment, care coordination, and coaching of caregivers.7 With this assumption in mind, it is projected that by 2025, there will be a national shortage of 26,980 geriatricians, with the western United States disproportionately affected by this shortage.4Rather than lamenting this shortage, Tinetti recommends a new path forward: “Our mission should not be to train enough geriatricians to provide direct care, but rather to ensure that every clinician caring for older adults is competent in geriatric principles and practices.”8 Sometimes called ”geriatricizing,” the idea is to use existing geriatric providers as a small elite training force to infuse geriatric principles and skills across their colleagues in primary care and other disciplines.8,9 Efforts of the American Geriatrics Society (AGS), with support from the John A. Hartford Foundation (JAHF), have been successful in developing geriatric training across multiple specialties, including surgery, orthopedics, and emergency medicine (www.americangeriatrics.org/programs/geriatrics-specialists-initiative).
The Age-Friendly Health System and 4M Model
To help augment this idea of equipping health care systems and their clinicians with more readily available geriatric knowledge, skills, and tools, the JAHF, along with the Institute for Healthcare Improvement (IHI), created the Age-Friendly Health System (AFHS) paradigm in 2015.10 Using the 4M model, the AFHS initiative established a set of evidence-based geriatric priorities and interventions meant to improve the care of older adults, reduce harm and duplication, and provide a framework for engaging leadership, clinical teams, and operational systems across inpatient and ambulatory settings.11 Mobility, including fall risk screening and intervention, is 1 of the 4M foundational elements of the Age-Friendly model. In addition to Mobility, the 4M model also includes 3 other key geriatric domains: Mentation (dementia, depression, and delirium), Medication (high-risk medications, polypharmacy, and deprescribing), and What Matters (goals of care conversations and understanding quality of life for older patients).11 The 4M initiative encourages adoption of a geriatric lens that looks across chronic conditions and accounts for the interplay among geriatric syndromes, such as falls, cognitive impairment, and frailty, in order to provide care better tailored to what the patient needs and desires.12 IHI and JAHF have targeted the adoption of the 4M model by 20% of US health care systems by 2020.11
Mini-Fellowship and Mobility Week
To bolster geriatric skills among community-based primary care providers (PCPs), we initiated a Geriatric Mini-Fellowship, a 4-week condensed curriculum taught over 6 months. Each week focuses on 1 of the age-friendly 4Ms, with the goal of increasing the knowledge, self-efficacy, skills, and competencies of the participating PCPs (called “fellow” hereafter) and at the same time, equipping each to become a champion of geriatric practice. This article focuses on the Mobility week, the second week of the mini-fellowship, and the effect of the week on the fellows’ practice changes.
To construct the Mobility week’s curriculum with a focus on the ambulatory setting, we relied upon national evidence-based work in fall risk management. The Centers for Disease Control and Prevention (CDC) has made fall risk screening and management in primary care a high priority. Using the clinical practice guidelines for managing fall risk developed by the American and British Geriatrics Societies (AGS/BGS), the CDC developed the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) toolkit.13 Foundational to the toolkit is the validated 12-item Stay Independent falls screening questionnaire (STEADI questionnaire).14 Patients who score 4 or higher (out of a total score of 14) on the questionnaire are considered at increased risk of falling. The CDC has developed a clinical algorithm that guides clinical teams through screening and assessment to help identify appropriate interventions to target specific risk factors. Research has clearly established that a multifactorial approach to fall risk intervention can be successful in reducing fall risk by as much as 25%.15-17
The significant morbidity and mortality caused by falls make training nongeriatrician clinicians on how to better address fall risk imperative. More than 25% of older adults fall each year.18 These falls contribute to rising rates of fall-related deaths,19 emergency department (ED) visits,20 and hospital readmissions.21 Initiatives like the AFHS focus on mobility and the CDC’s development of supporting clinical materials22 aim to improve primary care adoption of fall risk screening and intervention practices.23,24 The epidemic of falls must compel all PCPs, not just those practicing geriatrics, to make discussing and addressing fall risk and falls a priority.
Methods
Setting
This project took place as part of a regional primary care effort in Oregon. Providence Health & Services-Oregon is part of a multi-state integrated health care system in the western United States whose PCPs serve more than 80,000 patients aged 65 years and older per year; these patients comprise 38% of the system’s office visits each year. Regionally, there are 47 family and internal medicine clinics employing roughly 290 providers (physicians, NPs, and physician assistants). The organization has only 4 PCPs trained in geriatrics and does not offer any geriatric clinical consultation services. Six PCPs from different clinics, representing both rural and urban settings, are chosen to participate in the geriatric mini-fellowship each year.
This project was conducted as a quality improvement initiative within the organization and did not constitute human subjects research. It was not conducted under the oversight of the Institutional Review Board.
Intervention
The mini-fellowship was taught in 4 1-week blocks between April and October 2018, with a curriculum designed to be interactive and practical. The faculty was intentionally interdisciplinary to teach and model team-based practice. Each week participants were excused from their clinical practice. Approximately 160 hours of continuing medical education credits were awarded for the full mini-fellowship. As part of each weekly session, a performance improvement project (PIP) focused on that week’s topic (1 of the 4Ms) was developed by the fellow and their team members to incorporate the mini-fellowship learnings into their clinic workflows. Fellows also had 2 hours per week of dedicated administration time for a year, outside the fellowship, to work on their PIP and 4M practice changes within their clinic.
Provider Education
The week for mobility training comprised 4 daylong sessions. The first 2 days were spent learning about the epidemiology of falls; risk factors for falling; how to conduct a thorough history and assessment of fall risk; and how to create a prioritized Fall Risk Management Plan (FRMP) to decrease a patient’s individual fall risk through tailored interventions. The FRMP was adapted from the CDC STEADI toolkit.13 Core faculty were 2 geriatric-trained providers (NP and physician) and a physical therapist (PT) specializing in fall prevention.
On the third day, fellows took part in a simulated fall risk clinic, in which older adults volunteered to be patient partners, providing an opportunity to apply learnings from days 1 and 2. The clinic included the fellow observing a PT complete a mobility assessment and a pharmacist conduct a high-risk medication review. The fellow synthesized the findings of the mobility assessment and medication review, as well as their own history and assessment, to create a summary of fall risk recommendations to discuss with their volunteer patient partner. The fellows were observed and evaluated in their skills by their patient partner, course faculty, and another fellow. The patient partners, and their assigned fellow, also participated in a 45-minute fall risk presentation, led by a nurse.
On the fourth day, the fellows were joined by select clinic partners, including nurses, pharmacists, and/or medical assistants. The session included discussions among each fellow’s clinical team regarding the current state of fall risk efforts at their clinic, an analysis of barriers, and identification of opportunities to improve workflows and screening rates. Each fellow took with them an action plan tailored to their clinic to improve fall risk management practices, starting with the fellow’s own practice.
Fall Risk Management Plan
The educational sessions introduced the fellows to the FRMP. The FRMP, adapted from the STEADI toolkit, includes a process for fall risk screening (Figure 1) and stratifying a patient’s risk based on their STEADI score in order to promote 3 priority assessments (gait evaluation with PT referral if appropriate; orthostatic blood pressure; and high-risk medication review; Figure 2). Initial actions based on these priority assessments were followed over time, with additional fall risk interventions added as clinically indicated.25 The FRMP is intended to be used during routine office visits, Medicare annual wellness visits, or office visits focused on fall risk or related medical disorders (ie, fall risk visits.)
Providers and their teams were encouraged to spread out fall-related conversations with their patients over multiple visits, since many patients have multiple fall risk factors at play, in addition to other chronic medical issues, and since many interventions often require behavior changes on the part of the patient. Providers also had access to fall-related electronic health record (EHR) templates as well as a comprehensive, internal fall risk management website that included assessment tools, evidence-based resources, and patient handouts.
Assessment and Measurements
We assessed provider knowledge and comfort in their fall risk evaluation and management skills before and after the educational intervention using an 11-item multiple-choice questionnaire and a 4-item confidence questionnaire. The confidence questions used a 7-point Likert scale, with 0 indicating “no confidence” and 7 indicating ”lots of confidence.” The questions were administered via a paper survey. Qualitative comments were derived from evaluations completed at the end of the week.
The fellows’ practice of fall risk screening and management was studied from May 2018, at the completion of Mobility week, to May 2019 for the post-intervention period. A 1-year timeframe before May 2018 was used as the pre-intervention period. Eligible visit types, during which we assumed fall risk was discussed, were any office visits for patients 65+ completed by the patients’ PCPs that used fall risk as a reason for the visit or had a fall-related diagnosis code. Fall risk visits performed by other clinic providers were not counted.
Of those patients who had fall risk screenings completed and were determined to be high risk (STEADI score ≥ 4), data were analyzed to determine whether these patients had any fall-related follow-up visits to their PCP within 60 days of the STEADI screening. For these high-risk patients, data were studied to understand whether orthostatic blood pressure measurements were performed (as documented in a flowsheet) and whether a PT referral was placed. These data were compared with those from providers who practiced in clinics within the same system but who did not participate in the mini-fellowship. Data were obtained from the organization’s EHR. Additional data were measured to evaluate patterns of deprescribing of select high-risk medications, but these data are not included in this analysis.
Analysis
A paired-samples t test was used to measure changes in provider confidence levels. Data were aggregated across fellows, resulting in a mean. A chi-square test of independence was performed to examine the relationship between rates of FRMP adoption by select provider groups. Analysis included a pre- and post-intervention assessment of the fellows’ adoption of FRMP practices, as well as a comparison between the fellows’ practice patterns and those of a control group of PCPs in the organization’s other clinics who did not participate in the mini-fellowship (nontrained control group). Excluded from the control group were providers from the same clinic as the fellows; providers in clinics with a geriatric-trained provider on staff; and clinics outside of the Portland metro and Medford service areas. We used an alpha level of 0.05 for all statistical tests.
Data from 5 providers were included in the analysis of the FRMP adoption. The sixth provider changed practice settings from the clinic to the ED after completing the fellowship; her patient data were not included in the FRMP part of the analysis. EHR data included data on all visits of patients 65+, as well as data for just those 65+ patients who had been identified as being at high risk to fall based on a STEADI score of 4 or higher.
Results
Provider Questionnaire
All 6 providers responded to the pre-intervention and post-intervention tests. For the knowledge questions, fellows, as a composite, correctly answered 57% of the questions before the intervention and 79% after the intervention. Provider confidence level in delivering fall risk care was measured prior to the training (mean, 4.12 [SD, 0.62]) and at the end of the training (mean, 6.47 [SD, 0.45]), demonstrating a significant increase in confidence (t (5) = –10.46, P < 0.001).
Qualitative Comments
Providers also had the opportunity to provide comments on their experience during the Mobility week and at the end of 1 year. In general, the simulated interdisciplinary fall risk clinic was highly rated (“the highlight of the week”) as a practical strategy to embed learning principles. One fellow commented, “Putting the learning into practice helps solidify it in my brain.” Fellows also appreciated the opportunity to learn and meet with their clinic colleagues to begin work on a fall-risk focused PIP and to “have a framework for what to do for people who screen positive [for fall risk].”
FRMP Adoption
A comparison of the care the fellows provided to their patients 65+ in the 12 months pre- and post-training shows the fellows demonstrated significant changes in practice patterns. The fellows were 1.7 times more likely to screen for fall risk; 3.6 times more likely to discuss fall risk; and 5.8 times more likely to check orthostatic blood pressure than prior to the mini-fellowship (Table 1).
The control providers also demonstrated significant increases in fall risk screening and discussion of fall risk between the pre- and post-intervention periods; however, the relative risk (RR) was between 1.10 and 1.13 for this group. For the control group, checking orthostatic blood pressure did not significantly change. In the 12 months after training (Table 2), the fellows were 4.2 times more likely to discuss fall risk and almost 5 times more likely to check orthostatic blood pressure than their nontrained peers for all of their patients 65+, regardless of their risk to fall.
As shown in Table 3, for those patients determined to be at high risk of falling (STEADI score ≥ 4), fellows showed statistically significant increases in fall risk visits (RR, 3.02) and assessment of orthostatic blood pressure (RR, 10.68) before and after the mini-fellowship. The control providers did not show any changes in practice patterns between the pre- and post-period among patients at high risk to fall.
Neither the fellows nor the control group showed changes in patterns of referral to PT. In comparing the 2 groups in the 12 months after training (Table 4), for their patients at risk of falling, the fellows were 4 times more likely to complete fall risk visits and over 6 times more likely to assess orthostatic blood pressure than their nontrained peers. Subgroup analysis of the 75+ population revealed similar trends and significance, but these results are not included here.
Discussion
This study aimed to improve not only providers’ knowledge and confidence in caring for older adults at increased risk to fall, but also their clinical practice in assessing and managing fall risk. In addition to improved knowledge and confidence, we found that the fellows increased their discussion of fall risk (through fall risk visits) and their assessment of orthostatic blood pressure for all of their patients, not just for those identified at increased risk to fall. This improvement held true for the fellows themselves before and after the intervention, but also as compared to their nontrained peers. These practice improvements for all of their 65+ patients, not just those identified as being at high risk to fall, are especially important, since studies indicate that early screening and intervention can help identify people at risk and prevent future falls.15
We were surprised that there were no significant differences in PT referrals made by the trained fellows, but this finding may have been confounded by the fact that the data included all PT referrals, regardless of diagnosis, not just those referrals that were fall-related. Furthermore, our baseline PT referral rates, at 39% for the intervention group and 42% for the control group, are higher than national data when looking at rehabilitation use by older adults.26
In comparison to a study evaluating the occurrence of fall risk–related clinical practice in primary care before any fall-related educational intervention, orthostatics were checked less frequently in our study (10% versus 30%) and there were fewer PT referrals (42%–44% versus 53%).27 However, the Phelan study took place in patients who had actually had a fall, rather than just having a higher risk for a fall, and was based on detailed chart review. Other studies23,24 found higher rates of fall risk interventions, but did not break out PT referrals specifically.
In terms of the educational intervention itself, most studies of geriatric education interventions have measured changes in knowledge, confidence, or self-efficacy as they relate to geriatric competence,28-30 and do not measure practice change as an outcome outside of intent to change or self-reported practice change.31,32 In general, practice change or longer-term health care–related outcomes have not been studied. Additionally, a range of dosages of educational interventions has been studied, from 1-hour lunchtime presentations23,32 to half-day29 or several half-day workshops,28 up to 160 hours over 10 months30 or 5 weekends over 6 months.31 The duration of our entire intervention at 160 hours over 6 months would be considered on the upper end of dosing relative to these studies, with our Mobility week intervention comprising 32 hours during 1 week. In the Warshaw study, despite 107 1-hour sessions being taught to over 60 physicians in 16 practices over 4 years, only 2 practices ultimately initiated any practice change projects.32 We believe that only curricula that embed practice change skills and opportunities, at a significant enough dose, can actually impact practice change in a sustainable manner.
Knowledge and skill acquisition among individual providers does not take place to a sufficient degree in the current health care arena, which is focused on productivity and short visit times. Consistent with other studies, we included interdisciplinary members of the primary care team for part of the mini-fellowship, although other studies used models that train across disciplines for the entirety of the learning experience.28-30,33 Our educational model was strengthened by including other professionals to provide some of the education and model the ideal geriatric team, including PT, occupational therapy, and pharmacy, for the week on mobility.
Most studies exploring interventions through geriatric educational initiatives are conducted within academic institutions, with a primary focus on physician faculty and, by extension, their teaching of residents and others.34,35 We believe our integrated model, which is steeped in community-based primary care practices like Lam’s,31 offers the greatest outreach to large community-based care systems and their patients. Training providers to work with their teams to change their own practices first gives skills and expertise that help further establish them as geriatric champions within their practices, laying the groundwork for more widespread practice change at their clinics.
Limitations
In addition to the limitations described above relating to the capture of PT referrals, other limitations included the relatively short time period for follow-up data as well as the small size of the intervention group. However, we found value in the instructional depth that the small group size allowed.
While the nontrained providers did show some improvement during the same period, we believe the relative risk was not clinically significant. We suspect that the larger health system efforts to standardize screening of patients 65+ across all clinics as a core quality metric confounded these results. The data analysis also included only fall-related patient visits that occurred with a provider who was that patient’s PCP, which could have missed visits done by other PCP colleagues, RNs, or pharmacists in the same clinic, thus undercounting the true number of fall-related visits. Furthermore, counting of fall-related interventions relied upon providers documenting consistently in the EHR, which could also lead to under-represention of fall risk clinical efforts.
The data presented, while encouraging, do not reflect clinic-wide practice change patterns and are considered only proximate outcomes rather than more long-term or cost-related outcomes, as would be captured by fall-related utilization measures like emergency room visits and hospitalizations. We expect to evaluate the broader impact and these value-based outcomes in the future. All providers and teams were from the same health care system, which may not allow our results to transfer to other organizations or regions of clinical practice.
Summary
This study demonstrates that an intensive mini-fellowship model of geriatrics training improved both knowledge and confidence in the realm of fall risk assessment and intervention among PCPs who had not been formally trained in geriatrics. More importantly, the training improved the fall-related care of their patients at increased risk to fall, but also of all of their older patients, with improvements in care measured up to a year after the mini-fellowship. Although this article only describes the work done as part of the Mobility aim of the 4M AFHS model, we believe the entire mini-fellowship curriculum offers the opportunity to “geriatricize” clinicians and their teams in learning geriatric principles and skills that they can translate into their practice in a sustainable way, as Tinetti encourages.8 Future study to evaluate other process outcomes more precisely, such as PT, as well as cost- and value-based outcomes, and the influence of trained providers on their clinic partners, will further establish the value proposition of targeted, disseminated, intensive geriatrics training of primary care clinicians as a strategy of age-friendly health systems as they work to improve the care of their older adults.
Acknowledgment: We are grateful for the dedication and hard work of the 2018 Geriatric Mini-Fellowship fellows at Providence Health & Services-Oregon who made this article possible. Thanks to Drs. Stephanie Cha, Emily Puukka-Clark, Laurie Dutkiewicz, Cara Ellis, Deb Frost, Jordan Roth, and Subhechchha Shah for promoting the AFHS work within their Providence Medical Group clinics and to PMG leadership and the fellows’ clinical teams for supporting the fellows, the AFHS work, and their older patients.
Corresponding author: Colleen M. Casey, PhD, ANP-BC, Providence Health & Services, Senior Health Program, 4400 NE Halsey, 5th Floor, Portland, OR 97213; colleen.casey@providence.org.
Financial disclosures: None.
From the Senior Health Program, Providence Health & Services, Oregon, Portland, OR.
Abstract
Background: Approximately 51 million adults in the United States are 65 years of age or older, yet few geriatric-trained primary care providers (PCP) serve this population. The Age-Friendly Health System framework, consisting of evidence-based 4M care (Mobility, Medication, Mentation, and what Matters), encourages all PCPs to assess mobility in older adults.
Objective: To improve PCP knowledge, confidence, and clinical practice in assessing and managing fall risk.
Methods: A 1-week educational session focusing on mobility (part of a 4-week Geriatric Mini-Fellowship) for 6 selected PCPs from a large health care system was conducted to increase knowledge and ability to address fall risk in older adults. The week included learning and practicing a Fall Risk Management Plan (FRMP) algorithm, including planning for their own practice changes. Pre- and post-test surveys assessed changes in knowledge and confidence. Patient data were compared 12 months before and after training to evaluate PCP adoption of FRMP components.
Results: The training increased provider knowledge and confidence. The trained PCPs were 1.7 times more likely to screen for fall risk; 3.6 times more likely to discuss fall risk; and 5.8 times more likely to assess orthostatic blood pressure in their 65+ patients after the mini-fellowship. In high-risk patients, they were 4.1 times more likely to discuss fall risk and 6.3 times more likely to assess orthostatic blood pressure than their nontrained peers. Changes in physical therapy referral rates were not observed.
Conclusions: In-depth, skills-based geriatric educational sessions improved PCPs’ knowledge and confidence and also improved their fall risk management practices for their older patients.
Keywords: geriatrics; guidelines; Age-Friendly Health System; 4M; workforce training; practice change; fellowship.
The US population is aging rapidly. People aged 85 years and older are the largest-growing segment of the US population, and this segment is expected to increase by 123% by 2040.1 Caregiving needs increase with age as older adults develop more chronic conditions, such as hypertension, heart disease, arthritis, and dementia. However, even with increasing morbidity and dependence, a majority of older adults still live in the community rather than in institutional settings.2 These older adults seek medical care more frequently than younger people, with about 22% of patients 75 years and older having 10 or more health care visits in the previous 12 months. By 2040, nearly a quarter of the US population is expected to be 65 or older, with many of these older adults seeking regular primary care from providers who do not have formal training in the care of a population with multiple complex, chronic health conditions and increased caregiving needs.1
Despite this growing demand for health care professionals trained in the care of older adults, access to these types of clinicians is limited. In 2018, there were roughly 7000 certified geriatricians, with only 3600 of them practicing full-time.3,4 Similarly, of 290,000 certified nurse practitioners (NPs), about 9% of them have geriatric certification.5 Geriatricians, medical doctors trained in the care of older adults, and geriatric-trained NPs are part of a cadre of a geriatric-trained workforce that provides unique expertise in caring for older adults with chronic and advanced illness. They know how to manage multiple, complex geriatric syndromes like falls, dementia, and polypharmacy; understand and maximize team-based care; and focus on caring for an older person with a goal-centered versus a disease-centered approach.6
Broadly, geriatric care includes a spectrum of adults, from those who are aging healthfully to those who are the frailest. Research has suggested that approximately 30% of older adults need care by a geriatric-trained clinician, with the oldest and frailest patients needing more clinician time for assessment and treatment, care coordination, and coaching of caregivers.7 With this assumption in mind, it is projected that by 2025, there will be a national shortage of 26,980 geriatricians, with the western United States disproportionately affected by this shortage.4Rather than lamenting this shortage, Tinetti recommends a new path forward: “Our mission should not be to train enough geriatricians to provide direct care, but rather to ensure that every clinician caring for older adults is competent in geriatric principles and practices.”8 Sometimes called ”geriatricizing,” the idea is to use existing geriatric providers as a small elite training force to infuse geriatric principles and skills across their colleagues in primary care and other disciplines.8,9 Efforts of the American Geriatrics Society (AGS), with support from the John A. Hartford Foundation (JAHF), have been successful in developing geriatric training across multiple specialties, including surgery, orthopedics, and emergency medicine (www.americangeriatrics.org/programs/geriatrics-specialists-initiative).
The Age-Friendly Health System and 4M Model
To help augment this idea of equipping health care systems and their clinicians with more readily available geriatric knowledge, skills, and tools, the JAHF, along with the Institute for Healthcare Improvement (IHI), created the Age-Friendly Health System (AFHS) paradigm in 2015.10 Using the 4M model, the AFHS initiative established a set of evidence-based geriatric priorities and interventions meant to improve the care of older adults, reduce harm and duplication, and provide a framework for engaging leadership, clinical teams, and operational systems across inpatient and ambulatory settings.11 Mobility, including fall risk screening and intervention, is 1 of the 4M foundational elements of the Age-Friendly model. In addition to Mobility, the 4M model also includes 3 other key geriatric domains: Mentation (dementia, depression, and delirium), Medication (high-risk medications, polypharmacy, and deprescribing), and What Matters (goals of care conversations and understanding quality of life for older patients).11 The 4M initiative encourages adoption of a geriatric lens that looks across chronic conditions and accounts for the interplay among geriatric syndromes, such as falls, cognitive impairment, and frailty, in order to provide care better tailored to what the patient needs and desires.12 IHI and JAHF have targeted the adoption of the 4M model by 20% of US health care systems by 2020.11
Mini-Fellowship and Mobility Week
To bolster geriatric skills among community-based primary care providers (PCPs), we initiated a Geriatric Mini-Fellowship, a 4-week condensed curriculum taught over 6 months. Each week focuses on 1 of the age-friendly 4Ms, with the goal of increasing the knowledge, self-efficacy, skills, and competencies of the participating PCPs (called “fellow” hereafter) and at the same time, equipping each to become a champion of geriatric practice. This article focuses on the Mobility week, the second week of the mini-fellowship, and the effect of the week on the fellows’ practice changes.
To construct the Mobility week’s curriculum with a focus on the ambulatory setting, we relied upon national evidence-based work in fall risk management. The Centers for Disease Control and Prevention (CDC) has made fall risk screening and management in primary care a high priority. Using the clinical practice guidelines for managing fall risk developed by the American and British Geriatrics Societies (AGS/BGS), the CDC developed the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) toolkit.13 Foundational to the toolkit is the validated 12-item Stay Independent falls screening questionnaire (STEADI questionnaire).14 Patients who score 4 or higher (out of a total score of 14) on the questionnaire are considered at increased risk of falling. The CDC has developed a clinical algorithm that guides clinical teams through screening and assessment to help identify appropriate interventions to target specific risk factors. Research has clearly established that a multifactorial approach to fall risk intervention can be successful in reducing fall risk by as much as 25%.15-17
The significant morbidity and mortality caused by falls make training nongeriatrician clinicians on how to better address fall risk imperative. More than 25% of older adults fall each year.18 These falls contribute to rising rates of fall-related deaths,19 emergency department (ED) visits,20 and hospital readmissions.21 Initiatives like the AFHS focus on mobility and the CDC’s development of supporting clinical materials22 aim to improve primary care adoption of fall risk screening and intervention practices.23,24 The epidemic of falls must compel all PCPs, not just those practicing geriatrics, to make discussing and addressing fall risk and falls a priority.
Methods
Setting
This project took place as part of a regional primary care effort in Oregon. Providence Health & Services-Oregon is part of a multi-state integrated health care system in the western United States whose PCPs serve more than 80,000 patients aged 65 years and older per year; these patients comprise 38% of the system’s office visits each year. Regionally, there are 47 family and internal medicine clinics employing roughly 290 providers (physicians, NPs, and physician assistants). The organization has only 4 PCPs trained in geriatrics and does not offer any geriatric clinical consultation services. Six PCPs from different clinics, representing both rural and urban settings, are chosen to participate in the geriatric mini-fellowship each year.
This project was conducted as a quality improvement initiative within the organization and did not constitute human subjects research. It was not conducted under the oversight of the Institutional Review Board.
Intervention
The mini-fellowship was taught in 4 1-week blocks between April and October 2018, with a curriculum designed to be interactive and practical. The faculty was intentionally interdisciplinary to teach and model team-based practice. Each week participants were excused from their clinical practice. Approximately 160 hours of continuing medical education credits were awarded for the full mini-fellowship. As part of each weekly session, a performance improvement project (PIP) focused on that week’s topic (1 of the 4Ms) was developed by the fellow and their team members to incorporate the mini-fellowship learnings into their clinic workflows. Fellows also had 2 hours per week of dedicated administration time for a year, outside the fellowship, to work on their PIP and 4M practice changes within their clinic.
Provider Education
The week for mobility training comprised 4 daylong sessions. The first 2 days were spent learning about the epidemiology of falls; risk factors for falling; how to conduct a thorough history and assessment of fall risk; and how to create a prioritized Fall Risk Management Plan (FRMP) to decrease a patient’s individual fall risk through tailored interventions. The FRMP was adapted from the CDC STEADI toolkit.13 Core faculty were 2 geriatric-trained providers (NP and physician) and a physical therapist (PT) specializing in fall prevention.
On the third day, fellows took part in a simulated fall risk clinic, in which older adults volunteered to be patient partners, providing an opportunity to apply learnings from days 1 and 2. The clinic included the fellow observing a PT complete a mobility assessment and a pharmacist conduct a high-risk medication review. The fellow synthesized the findings of the mobility assessment and medication review, as well as their own history and assessment, to create a summary of fall risk recommendations to discuss with their volunteer patient partner. The fellows were observed and evaluated in their skills by their patient partner, course faculty, and another fellow. The patient partners, and their assigned fellow, also participated in a 45-minute fall risk presentation, led by a nurse.
On the fourth day, the fellows were joined by select clinic partners, including nurses, pharmacists, and/or medical assistants. The session included discussions among each fellow’s clinical team regarding the current state of fall risk efforts at their clinic, an analysis of barriers, and identification of opportunities to improve workflows and screening rates. Each fellow took with them an action plan tailored to their clinic to improve fall risk management practices, starting with the fellow’s own practice.
Fall Risk Management Plan
The educational sessions introduced the fellows to the FRMP. The FRMP, adapted from the STEADI toolkit, includes a process for fall risk screening (Figure 1) and stratifying a patient’s risk based on their STEADI score in order to promote 3 priority assessments (gait evaluation with PT referral if appropriate; orthostatic blood pressure; and high-risk medication review; Figure 2). Initial actions based on these priority assessments were followed over time, with additional fall risk interventions added as clinically indicated.25 The FRMP is intended to be used during routine office visits, Medicare annual wellness visits, or office visits focused on fall risk or related medical disorders (ie, fall risk visits.)
Providers and their teams were encouraged to spread out fall-related conversations with their patients over multiple visits, since many patients have multiple fall risk factors at play, in addition to other chronic medical issues, and since many interventions often require behavior changes on the part of the patient. Providers also had access to fall-related electronic health record (EHR) templates as well as a comprehensive, internal fall risk management website that included assessment tools, evidence-based resources, and patient handouts.
Assessment and Measurements
We assessed provider knowledge and comfort in their fall risk evaluation and management skills before and after the educational intervention using an 11-item multiple-choice questionnaire and a 4-item confidence questionnaire. The confidence questions used a 7-point Likert scale, with 0 indicating “no confidence” and 7 indicating ”lots of confidence.” The questions were administered via a paper survey. Qualitative comments were derived from evaluations completed at the end of the week.
The fellows’ practice of fall risk screening and management was studied from May 2018, at the completion of Mobility week, to May 2019 for the post-intervention period. A 1-year timeframe before May 2018 was used as the pre-intervention period. Eligible visit types, during which we assumed fall risk was discussed, were any office visits for patients 65+ completed by the patients’ PCPs that used fall risk as a reason for the visit or had a fall-related diagnosis code. Fall risk visits performed by other clinic providers were not counted.
Of those patients who had fall risk screenings completed and were determined to be high risk (STEADI score ≥ 4), data were analyzed to determine whether these patients had any fall-related follow-up visits to their PCP within 60 days of the STEADI screening. For these high-risk patients, data were studied to understand whether orthostatic blood pressure measurements were performed (as documented in a flowsheet) and whether a PT referral was placed. These data were compared with those from providers who practiced in clinics within the same system but who did not participate in the mini-fellowship. Data were obtained from the organization’s EHR. Additional data were measured to evaluate patterns of deprescribing of select high-risk medications, but these data are not included in this analysis.
Analysis
A paired-samples t test was used to measure changes in provider confidence levels. Data were aggregated across fellows, resulting in a mean. A chi-square test of independence was performed to examine the relationship between rates of FRMP adoption by select provider groups. Analysis included a pre- and post-intervention assessment of the fellows’ adoption of FRMP practices, as well as a comparison between the fellows’ practice patterns and those of a control group of PCPs in the organization’s other clinics who did not participate in the mini-fellowship (nontrained control group). Excluded from the control group were providers from the same clinic as the fellows; providers in clinics with a geriatric-trained provider on staff; and clinics outside of the Portland metro and Medford service areas. We used an alpha level of 0.05 for all statistical tests.
Data from 5 providers were included in the analysis of the FRMP adoption. The sixth provider changed practice settings from the clinic to the ED after completing the fellowship; her patient data were not included in the FRMP part of the analysis. EHR data included data on all visits of patients 65+, as well as data for just those 65+ patients who had been identified as being at high risk to fall based on a STEADI score of 4 or higher.
Results
Provider Questionnaire
All 6 providers responded to the pre-intervention and post-intervention tests. For the knowledge questions, fellows, as a composite, correctly answered 57% of the questions before the intervention and 79% after the intervention. Provider confidence level in delivering fall risk care was measured prior to the training (mean, 4.12 [SD, 0.62]) and at the end of the training (mean, 6.47 [SD, 0.45]), demonstrating a significant increase in confidence (t (5) = –10.46, P < 0.001).
Qualitative Comments
Providers also had the opportunity to provide comments on their experience during the Mobility week and at the end of 1 year. In general, the simulated interdisciplinary fall risk clinic was highly rated (“the highlight of the week”) as a practical strategy to embed learning principles. One fellow commented, “Putting the learning into practice helps solidify it in my brain.” Fellows also appreciated the opportunity to learn and meet with their clinic colleagues to begin work on a fall-risk focused PIP and to “have a framework for what to do for people who screen positive [for fall risk].”
FRMP Adoption
A comparison of the care the fellows provided to their patients 65+ in the 12 months pre- and post-training shows the fellows demonstrated significant changes in practice patterns. The fellows were 1.7 times more likely to screen for fall risk; 3.6 times more likely to discuss fall risk; and 5.8 times more likely to check orthostatic blood pressure than prior to the mini-fellowship (Table 1).
The control providers also demonstrated significant increases in fall risk screening and discussion of fall risk between the pre- and post-intervention periods; however, the relative risk (RR) was between 1.10 and 1.13 for this group. For the control group, checking orthostatic blood pressure did not significantly change. In the 12 months after training (Table 2), the fellows were 4.2 times more likely to discuss fall risk and almost 5 times more likely to check orthostatic blood pressure than their nontrained peers for all of their patients 65+, regardless of their risk to fall.
As shown in Table 3, for those patients determined to be at high risk of falling (STEADI score ≥ 4), fellows showed statistically significant increases in fall risk visits (RR, 3.02) and assessment of orthostatic blood pressure (RR, 10.68) before and after the mini-fellowship. The control providers did not show any changes in practice patterns between the pre- and post-period among patients at high risk to fall.
Neither the fellows nor the control group showed changes in patterns of referral to PT. In comparing the 2 groups in the 12 months after training (Table 4), for their patients at risk of falling, the fellows were 4 times more likely to complete fall risk visits and over 6 times more likely to assess orthostatic blood pressure than their nontrained peers. Subgroup analysis of the 75+ population revealed similar trends and significance, but these results are not included here.
Discussion
This study aimed to improve not only providers’ knowledge and confidence in caring for older adults at increased risk to fall, but also their clinical practice in assessing and managing fall risk. In addition to improved knowledge and confidence, we found that the fellows increased their discussion of fall risk (through fall risk visits) and their assessment of orthostatic blood pressure for all of their patients, not just for those identified at increased risk to fall. This improvement held true for the fellows themselves before and after the intervention, but also as compared to their nontrained peers. These practice improvements for all of their 65+ patients, not just those identified as being at high risk to fall, are especially important, since studies indicate that early screening and intervention can help identify people at risk and prevent future falls.15
We were surprised that there were no significant differences in PT referrals made by the trained fellows, but this finding may have been confounded by the fact that the data included all PT referrals, regardless of diagnosis, not just those referrals that were fall-related. Furthermore, our baseline PT referral rates, at 39% for the intervention group and 42% for the control group, are higher than national data when looking at rehabilitation use by older adults.26
In comparison to a study evaluating the occurrence of fall risk–related clinical practice in primary care before any fall-related educational intervention, orthostatics were checked less frequently in our study (10% versus 30%) and there were fewer PT referrals (42%–44% versus 53%).27 However, the Phelan study took place in patients who had actually had a fall, rather than just having a higher risk for a fall, and was based on detailed chart review. Other studies23,24 found higher rates of fall risk interventions, but did not break out PT referrals specifically.
In terms of the educational intervention itself, most studies of geriatric education interventions have measured changes in knowledge, confidence, or self-efficacy as they relate to geriatric competence,28-30 and do not measure practice change as an outcome outside of intent to change or self-reported practice change.31,32 In general, practice change or longer-term health care–related outcomes have not been studied. Additionally, a range of dosages of educational interventions has been studied, from 1-hour lunchtime presentations23,32 to half-day29 or several half-day workshops,28 up to 160 hours over 10 months30 or 5 weekends over 6 months.31 The duration of our entire intervention at 160 hours over 6 months would be considered on the upper end of dosing relative to these studies, with our Mobility week intervention comprising 32 hours during 1 week. In the Warshaw study, despite 107 1-hour sessions being taught to over 60 physicians in 16 practices over 4 years, only 2 practices ultimately initiated any practice change projects.32 We believe that only curricula that embed practice change skills and opportunities, at a significant enough dose, can actually impact practice change in a sustainable manner.
Knowledge and skill acquisition among individual providers does not take place to a sufficient degree in the current health care arena, which is focused on productivity and short visit times. Consistent with other studies, we included interdisciplinary members of the primary care team for part of the mini-fellowship, although other studies used models that train across disciplines for the entirety of the learning experience.28-30,33 Our educational model was strengthened by including other professionals to provide some of the education and model the ideal geriatric team, including PT, occupational therapy, and pharmacy, for the week on mobility.
Most studies exploring interventions through geriatric educational initiatives are conducted within academic institutions, with a primary focus on physician faculty and, by extension, their teaching of residents and others.34,35 We believe our integrated model, which is steeped in community-based primary care practices like Lam’s,31 offers the greatest outreach to large community-based care systems and their patients. Training providers to work with their teams to change their own practices first gives skills and expertise that help further establish them as geriatric champions within their practices, laying the groundwork for more widespread practice change at their clinics.
Limitations
In addition to the limitations described above relating to the capture of PT referrals, other limitations included the relatively short time period for follow-up data as well as the small size of the intervention group. However, we found value in the instructional depth that the small group size allowed.
While the nontrained providers did show some improvement during the same period, we believe the relative risk was not clinically significant. We suspect that the larger health system efforts to standardize screening of patients 65+ across all clinics as a core quality metric confounded these results. The data analysis also included only fall-related patient visits that occurred with a provider who was that patient’s PCP, which could have missed visits done by other PCP colleagues, RNs, or pharmacists in the same clinic, thus undercounting the true number of fall-related visits. Furthermore, counting of fall-related interventions relied upon providers documenting consistently in the EHR, which could also lead to under-represention of fall risk clinical efforts.
The data presented, while encouraging, do not reflect clinic-wide practice change patterns and are considered only proximate outcomes rather than more long-term or cost-related outcomes, as would be captured by fall-related utilization measures like emergency room visits and hospitalizations. We expect to evaluate the broader impact and these value-based outcomes in the future. All providers and teams were from the same health care system, which may not allow our results to transfer to other organizations or regions of clinical practice.
Summary
This study demonstrates that an intensive mini-fellowship model of geriatrics training improved both knowledge and confidence in the realm of fall risk assessment and intervention among PCPs who had not been formally trained in geriatrics. More importantly, the training improved the fall-related care of their patients at increased risk to fall, but also of all of their older patients, with improvements in care measured up to a year after the mini-fellowship. Although this article only describes the work done as part of the Mobility aim of the 4M AFHS model, we believe the entire mini-fellowship curriculum offers the opportunity to “geriatricize” clinicians and their teams in learning geriatric principles and skills that they can translate into their practice in a sustainable way, as Tinetti encourages.8 Future study to evaluate other process outcomes more precisely, such as PT, as well as cost- and value-based outcomes, and the influence of trained providers on their clinic partners, will further establish the value proposition of targeted, disseminated, intensive geriatrics training of primary care clinicians as a strategy of age-friendly health systems as they work to improve the care of their older adults.
Acknowledgment: We are grateful for the dedication and hard work of the 2018 Geriatric Mini-Fellowship fellows at Providence Health & Services-Oregon who made this article possible. Thanks to Drs. Stephanie Cha, Emily Puukka-Clark, Laurie Dutkiewicz, Cara Ellis, Deb Frost, Jordan Roth, and Subhechchha Shah for promoting the AFHS work within their Providence Medical Group clinics and to PMG leadership and the fellows’ clinical teams for supporting the fellows, the AFHS work, and their older patients.
Corresponding author: Colleen M. Casey, PhD, ANP-BC, Providence Health & Services, Senior Health Program, 4400 NE Halsey, 5th Floor, Portland, OR 97213; colleen.casey@providence.org.
Financial disclosures: None.
1. US Department of Health and Human Services. 2018 Profile of Older Americans. Administration on Aging. April 2018.
2. Roberts AW, Ogunwole SU, Blakeslee L, Rabe MA. The population 65 years and older in the United States: 2016. Washington, DC: US Census Bureau; 2018.
3. American Board of Medicine Specialties. 2017-2018 ABMS Board Certification Report. https://www.abms.org/board-certification/abms-board-certification-report/. Accessed November 3, 2020.
4. US Department of Health and Human Services, Health Resources and Services Administration, National Center for Health Workforce Analysis. National and regional projections of supply and demand for geriatricians: 2013-2025. Rockville, MD: US Department of Health and Human Services; 2007.
5. American Association of Nurse Practitioners, NP Facts: The Voice of the Nurse Practitioner. 2020. https://storage.aanp.org/www/documents/NPFacts__080420.pdf.
6. Tinetti ME, Naik AD, Dodson JA, Moving from disease-centered to patient goals-directed care for patients with multiple chronic conditions: patient value-based care. JAMA Cardiol. 2016;1:9-10.
7. Fried LP, Hall WJ. Editorial: leading on behalf of an aging society. J Am Geriatr Soc. 2008;56:1791-1795.
8. Tinetti M. Mainstream or extinction: can defining who we are save geriatrics? J Am Geriatr Soc. 2016;64:1400-1404.
9. Jafari P, Kostas T, Levine S, et al. ECHO-Chicago Geriatrics: using telementoring to “geriatricize” the primary care workforce. Gerontol Geriatr Educ. 2020;41:333-341.
10. Fulmer T, Mate KS, Berman A. The Age-Friendly Health System imperative. J Am Geriatr Soc. 2018;66:22-24.
11. Mate KS, Berman A, Laderman M, et al. Creating Age-Friendly Health Systems - A vision for better care of older adults. Healthc (Amst). 2018;6:4-6.
12. Tinetti ME, et al. Patient priority-directed decision making and care for older adults with multiple chronic conditions. Clin Geriatr Med. 2016;32:261-275.
13. Stevens JA, Phelan EA. Development of STEADI: a fall prevention resource for health care providers. Health Promot Pract. 2013;14:706-714.
14. Rubenstein LZ, et al. Validating an evidence-based, self-rated fall risk questionnaire (FRQ) for older adults. J Safety Res. 2011;42:493-499.
15. Grossman DC, et al. Interventions to prevent falls in community-dwelling older adults: US Preventive Services Task Force Recommendation Statement. JAMA. 2018;319: 1696-1704.
16. Tricco AC, Thomas SM, Veroniki AA, et al. Comparisons of interventions for preventing falls in older adults: a systematic review and meta-analysis. JAMA. 2017;318:1687-1699.
17. Gillespie LD, Robertson MC, Gillespie WJ, et al. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2012(9):CD007146.
18. Bergen G, Stevens MR, Burns ER. Falls and fall injuries among adults aged ≥65 years - United States, 2014. MMWR Morb Mortal Wkly Rep. 2016;65:993-998.
19. Burns E, Kakara R. Deaths from falls among persons aged >=65 Years - United States, 2007-2016. MMWR Morb Mortal Wkly Rep. 2018;67:509-514.
20. Shankar KN, Liu SW, Ganz DA. Trends and characteristics of emergency department visits for fall-related injuries in older adults, 2003-2010. West J Emerg Med. 2017;18:785-793.
21. Hoffman GJ, et al. Posthospital fall injuries and 30-day readmissions in adults 65 years and older. JAMA Netw Open. 2019;2:e194276.
22. Eckstrom E, Parker EM, Shakya I, Lee R. Coordinated care plan to prevent older adult falls. 2018. Atlanta, GA: National Center for Injury Prevention and Control, Centers for Disease Control and Prevention; 2018.
23. Eckstrom E, Parker EM, Lambert GH, et al. Implementing STEADI in academic primary care to address older adult fall risk. Innov Aging. 2017;1:igx028.
24. Johnston YA, Bergen G, Bauer M, et al. Implementation of the stopping elderly accidents, deaths, and injuries initiative in primary care: an outcome evaluation. Gerontologist. 2019;59:1182-1191.
25. Phelan EA, Mahoney JE, Voit JC, Stevens JA. Assessment and management of fall risk in primary care settings. Med Clin North Am. 2015;99:281-293.
26. Gell NM, Mroz TM, Patel KV. Rehabilitation services use and patient-reported outcomes among older adults in the United States. Arch Phys Med Rehabil. 2017;98:2221-2227.e3.
27. Phelan EA, Aerts S, Dowler D, et al. Adoption of evidence-based fall prevention practices in primary care for older adults with a history of falls. Front Public Health. 2016;4:190.
28. Solberg LB, Carter CS, Solberg LM. Geriatric care boot camp series: interprofessional education for a new training paradigm. Geriatr Nurs. 2019;40:579-583.
29. Solberg LB, Solberg LM, Carter CS. Geriatric care boot cAMP: an interprofessional education program for healthcare professionals. J Am Geriatr Soc. 2015;63:997-1001.
30. Coogle CL, Hackett L, Owens MG, et al. Perceived self-efficacy gains following an interprofessional faculty development programme in geriatrics education. J Interprof Care. 2016;30:483-492.
31. Lam R, Lee L, Tazkarji B, et al. Five-weekend care of the elderly certificate course: continuing professional development activity for family physicians. Can Fam Physician. 2015;61:e135-141.
32. Warshaw GA, Modawal A, Kues J, et al. Community physician education in geriatrics: applying the assessing care of vulnerable elders model with a multisite primary care group. J Am Geriatr Soc. 2010;58:1780-1785.
33. Solai LK, Kumar K, Mulvaney E, et al. Geriatric mental healthcare training: a mini-fellowship approach to interprofessional assessment and management of geriatric mental health issues. Am J Geriatr Psychiatry. 2019;27:706-711.
34. Christmas C, Park E, Schmaltz H, et al. A model intensive course in geriatric teaching for non-geriatrician educators. J Gen Intern Med. 2008;23:1048-1052.
35. Heflin MT, Bragg EJ, Fernandez H, et al. The Donald W. Reynolds Consortium for Faculty Development to Advance Geriatrics Education (FD~AGE): a model for dissemination of subspecialty educational expertise. Acad Med. 2012;87:618-626.
1. US Department of Health and Human Services. 2018 Profile of Older Americans. Administration on Aging. April 2018.
2. Roberts AW, Ogunwole SU, Blakeslee L, Rabe MA. The population 65 years and older in the United States: 2016. Washington, DC: US Census Bureau; 2018.
3. American Board of Medicine Specialties. 2017-2018 ABMS Board Certification Report. https://www.abms.org/board-certification/abms-board-certification-report/. Accessed November 3, 2020.
4. US Department of Health and Human Services, Health Resources and Services Administration, National Center for Health Workforce Analysis. National and regional projections of supply and demand for geriatricians: 2013-2025. Rockville, MD: US Department of Health and Human Services; 2007.
5. American Association of Nurse Practitioners, NP Facts: The Voice of the Nurse Practitioner. 2020. https://storage.aanp.org/www/documents/NPFacts__080420.pdf.
6. Tinetti ME, Naik AD, Dodson JA, Moving from disease-centered to patient goals-directed care for patients with multiple chronic conditions: patient value-based care. JAMA Cardiol. 2016;1:9-10.
7. Fried LP, Hall WJ. Editorial: leading on behalf of an aging society. J Am Geriatr Soc. 2008;56:1791-1795.
8. Tinetti M. Mainstream or extinction: can defining who we are save geriatrics? J Am Geriatr Soc. 2016;64:1400-1404.
9. Jafari P, Kostas T, Levine S, et al. ECHO-Chicago Geriatrics: using telementoring to “geriatricize” the primary care workforce. Gerontol Geriatr Educ. 2020;41:333-341.
10. Fulmer T, Mate KS, Berman A. The Age-Friendly Health System imperative. J Am Geriatr Soc. 2018;66:22-24.
11. Mate KS, Berman A, Laderman M, et al. Creating Age-Friendly Health Systems - A vision for better care of older adults. Healthc (Amst). 2018;6:4-6.
12. Tinetti ME, et al. Patient priority-directed decision making and care for older adults with multiple chronic conditions. Clin Geriatr Med. 2016;32:261-275.
13. Stevens JA, Phelan EA. Development of STEADI: a fall prevention resource for health care providers. Health Promot Pract. 2013;14:706-714.
14. Rubenstein LZ, et al. Validating an evidence-based, self-rated fall risk questionnaire (FRQ) for older adults. J Safety Res. 2011;42:493-499.
15. Grossman DC, et al. Interventions to prevent falls in community-dwelling older adults: US Preventive Services Task Force Recommendation Statement. JAMA. 2018;319: 1696-1704.
16. Tricco AC, Thomas SM, Veroniki AA, et al. Comparisons of interventions for preventing falls in older adults: a systematic review and meta-analysis. JAMA. 2017;318:1687-1699.
17. Gillespie LD, Robertson MC, Gillespie WJ, et al. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2012(9):CD007146.
18. Bergen G, Stevens MR, Burns ER. Falls and fall injuries among adults aged ≥65 years - United States, 2014. MMWR Morb Mortal Wkly Rep. 2016;65:993-998.
19. Burns E, Kakara R. Deaths from falls among persons aged >=65 Years - United States, 2007-2016. MMWR Morb Mortal Wkly Rep. 2018;67:509-514.
20. Shankar KN, Liu SW, Ganz DA. Trends and characteristics of emergency department visits for fall-related injuries in older adults, 2003-2010. West J Emerg Med. 2017;18:785-793.
21. Hoffman GJ, et al. Posthospital fall injuries and 30-day readmissions in adults 65 years and older. JAMA Netw Open. 2019;2:e194276.
22. Eckstrom E, Parker EM, Shakya I, Lee R. Coordinated care plan to prevent older adult falls. 2018. Atlanta, GA: National Center for Injury Prevention and Control, Centers for Disease Control and Prevention; 2018.
23. Eckstrom E, Parker EM, Lambert GH, et al. Implementing STEADI in academic primary care to address older adult fall risk. Innov Aging. 2017;1:igx028.
24. Johnston YA, Bergen G, Bauer M, et al. Implementation of the stopping elderly accidents, deaths, and injuries initiative in primary care: an outcome evaluation. Gerontologist. 2019;59:1182-1191.
25. Phelan EA, Mahoney JE, Voit JC, Stevens JA. Assessment and management of fall risk in primary care settings. Med Clin North Am. 2015;99:281-293.
26. Gell NM, Mroz TM, Patel KV. Rehabilitation services use and patient-reported outcomes among older adults in the United States. Arch Phys Med Rehabil. 2017;98:2221-2227.e3.
27. Phelan EA, Aerts S, Dowler D, et al. Adoption of evidence-based fall prevention practices in primary care for older adults with a history of falls. Front Public Health. 2016;4:190.
28. Solberg LB, Carter CS, Solberg LM. Geriatric care boot camp series: interprofessional education for a new training paradigm. Geriatr Nurs. 2019;40:579-583.
29. Solberg LB, Solberg LM, Carter CS. Geriatric care boot cAMP: an interprofessional education program for healthcare professionals. J Am Geriatr Soc. 2015;63:997-1001.
30. Coogle CL, Hackett L, Owens MG, et al. Perceived self-efficacy gains following an interprofessional faculty development programme in geriatrics education. J Interprof Care. 2016;30:483-492.
31. Lam R, Lee L, Tazkarji B, et al. Five-weekend care of the elderly certificate course: continuing professional development activity for family physicians. Can Fam Physician. 2015;61:e135-141.
32. Warshaw GA, Modawal A, Kues J, et al. Community physician education in geriatrics: applying the assessing care of vulnerable elders model with a multisite primary care group. J Am Geriatr Soc. 2010;58:1780-1785.
33. Solai LK, Kumar K, Mulvaney E, et al. Geriatric mental healthcare training: a mini-fellowship approach to interprofessional assessment and management of geriatric mental health issues. Am J Geriatr Psychiatry. 2019;27:706-711.
34. Christmas C, Park E, Schmaltz H, et al. A model intensive course in geriatric teaching for non-geriatrician educators. J Gen Intern Med. 2008;23:1048-1052.
35. Heflin MT, Bragg EJ, Fernandez H, et al. The Donald W. Reynolds Consortium for Faculty Development to Advance Geriatrics Education (FD~AGE): a model for dissemination of subspecialty educational expertise. Acad Med. 2012;87:618-626.
COVID-19 Screening and Testing Among Patients With Neurologic Dysfunction: The Neuro-COVID-19 Time-out Process and Checklist
From the University of Mississippi Medical Center, Department of Neurology, Division of Neuroscience Intensive Care, Jackson, MS.
Abstract
Objective: To test a coronavirus disease 2019 (COVID-19) screening tool to identify patients who qualify for testing among patients with neurologic dysfunction who are unable to answer the usual screening questions, which could help to prevent unprotected exposure of patients and health care workers to COVID-19.
Methods: The Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) was implemented at our institution for 1 week as a quality improvement project to improve the pathway for COVID-19 screening and testing among patients with neurologic dysfunction.
Results: A total of 14 new patients were admitted into the neuroscience intensive care unit (NSICU) service during the pilot period. The NCOT-PC was utilized on 9 (64%) patients with neurologic dysfunction; 7 of these patients were found to have a likelihood of requiring testing based on the NCOT-PC and were subsequently screened for COVID-19 testing by contacting the institution’s COVID-19 testing hotline (Med-Com). All these patients were subsequently transitioned into person-under-investigation status based on the determination from Med-Com. The NSICU staff involved were able to utilize NCOT-PC without issues. The NCOT-PC was immediately adopted into the NSICU process.
Conclusion: Use of the NCOT-PC tool was found to be feasible and improved the screening methodology of patients with neurologic dysfunction.
Keywords: coronavirus; health care planning; quality improvement; patient safety; medical decision-making; neuroscience intensive care unit.
The coronavirus disease 2019 (COVID-19) pandemic has altered various standard emergent care pathways. Current recommendations regarding COVID-19 screening for testing involve asking patients about their symptoms, including fever, cough, chest pain, and dyspnea.1 This standard screening method poses a problem when caring for patients with neurologic dysfunction. COVID-19 patients may pre-sent with conditions that affect their ability to answer questions, such as stroke, encephalitis, neuromuscular disorders, or headache, and that may preclude the use of standard screening for testing.2 Patients with acute neurologic dysfunction who cannot undergo standard screening may leave the emergency department (ED) and transition into the neuroscience intensive care unit (NSICU) or any intensive care unit (ICU) without a reliable COVID-19 screening test.
The Protected Code Stroke pathway offers protection in the emergent setting for patients with stroke when their COVID-19 status is unknown.3 A similar process has been applied at our institution for emergent management of patients with cerebrovascular disease (stroke, intracerebral hemorrhage, and subarachnoid hemorrhage). However, the process from the ED after designating “difficult to screen” patients as persons under investigation (PUI) is unclear. The Centers for Disease Control and Prevention (CDC) has delineated the priorities for testing, with not all declared PUIs requiring testing.4 This poses a great challenge, because patients designated as PUIs require the same management as a COVID-19-positive patient, with negative-pressure isolation rooms as well as use of protective personal equipment (PPE), which may not be readily available. It was also recognized that, because the ED staff can be overwhelmed by COVID-19 patients, there may not be enough time to perform detailed screening of patients with neurologic dysfunction and that “reverse masking” may not be done consistently for nonintubated patients. This may place patients and health care workers at risk of unprotected exposure.
Recognizing these challenges, we created a Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) as a quality improvement project. The aim of this project was to improve and standardize the current process of identifying patients with neurologic dysfunction who require COVID-19 testing to decrease the risk of unprotected exposure of patients and health care workers.
Methods
Patients and Definitions
This quality improvement project was undertaken at the University of Mississippi Medical Center NSICU. Because this was a quality improvement project, an Institutional Review Board exemption was granted.
The NCOT-PC was utilized in consecutive patients with neurologic dysfunction admitted to the NSICU during a period of 1 week. “Neurologic dysfunction” encompasses any neurologic illness affecting the mental status and/or level of alertness, subsequently precluding the ability to reliably screen the patient utilizing standard COVID-19 screening. “Med-Com” at our institution is the equivalent of the national COVID-19 testing hotline, where our institution’s infectious diseases experts screen calls for testing and determine whether testing is warranted. “Unprotected exposure” means exposure to COVID-19 without adequate and appropriate PPE.
Quality Improvement Process
As more PUIs were being admitted to the institution, we used the Plan-Do-Study-Act method for process improvements in the NSICU.5 NSICU stakeholders, including attendings, the nurse manager, and nurse practitioners (NPs), developed an algorithm to facilitate the coordination of the NSICU staff in screening patients to identify those with a high likelihood of needing COVID-19 testing upon arrival in the NSICU (Figure 1). Once the NCOT-PC was finalized, NSICU stakeholders were educated regarding the use of this screening tool.
The checklist clinicians review when screening patients is shown in Figure 2. The risk factors comprising the checklist include patient history and clinical and radiographic characteristics that have been shown to be relevant for identifying patients with COVID-19.6,7 The imaging criteria utilize imaging that is part of the standard of care for NSICU patients. For example, computed tomography angiogram of the head and neck performed as part of the acute stroke protocol captures the upper part of the chest. These images are utilized for their incidental findings, such as apical ground-glass opacities and tree-in-bud formation. The risk factors applicable to the patient determine whether the clinician will call Med-Com for testing approval. Institutional COVID-19 processes were then followed accordingly.8 The decision from Med-Com was considered final, and no deviation from institutional policies was allowed.
NCOT-PC was utilized for consecutive days for 1 week before re-evaluation of its feasibility and adaptability.
Data Collection and Analysis
Consecutive patients with neurologic dysfunction admitted into the NSICU were assigned nonlinkable patient numbers. No identifiers were collected for the purpose of this project. The primary diagnosis for admission, the neurologic dysfunction that precluded standard screening, and checklist components that the patient fulfilled were collected.
To assess the tool’s feasibility, feedback regarding the ease of use of the NCOT-PC was gathered from the nurses, NPs, charge nurses, fellows, and other attendings. To assess the utility of the NCOT-PC in identifying patients who will be approved for COVID-19 testing, we calculated the proportion of patients who were deemed to have a high likelihood of testing and the proportion of patients who were approved for testing. Descriptive statistics were used, as applicable for the project, to summarize the utility of the NCOT-PC.
Results
We found that the NCOT-PC can be easily used by clinicians. The NSICU staff did not communicate any implementation issues, and since the NCOT-PC was implemented, no problems have been identified.
During the pilot period of the NCOT-PC, 14 new patients were admitted to the NSICU service. Nine (64%) of these had neurologic dysfunction, and the NCOT-PC was used to determine whether Med-Com should be called based on the patients’ likelihood (high vs low) of needing a COVID-19 test. Of those patients with neurologic dysfunction, 7 (78%) were deemed to have a high likelihood of needing a COVID-19 test based on the NCOT-PC. Med-Com was contacted regarding these patients, and all were deemed to require the COVID-19 test by Med-Com and were transitioned into PUI status per institutional policy (Table).
Discussion
The NCOT-PC project improved and standardized the process of identifying and screening patients with neurologic dysfunction for COVID-19 testing. The screening tool is feasible to use, and it decreased inadvertent unprotected exposure of patients and health care workers.
The NCOT-PC was easy to administer. Educating the staff regarding the new process took only a few minutes and involved a meeting with the nurse manager, NPs, fellows, residents, and attendings. We found that this process works well in tandem with the standard institutional processes in place in terms of Protected Code Stroke pathway, PUI isolation, PPE use, and Med-Com screening for COVID-19 testing. Med-Com was called only if the patient fulfilled the checklist criteria. In addition, no extra cost was attributed to implementing the NCOT-PC, since we utilized imaging that was already done as part of the standard of care for patients with neurologic dysfunction.
The standardization of the process of screening for COVID-19 testing among patients with neurologic dysfunction improved patient selection. Before the NCOT-PC, there was no consistency in terms of who should get tested and the reason for testing patients with neurologic dysfunction. Patients can pass through the ED and arrive in the NSICU with an unclear screening status, which may cause inadvertent patient and health care worker exposure to COVID-19. With the NCOT-PC, we have avoided instances of inadvertent staff or patient exposure in the NSICU.
The NCOT-PC was adopted into the NSICU process after the first week it was piloted. Beyond the NSICU, the application of the NCOT-PC can be extended to any patient presentation that precludes standard screening, such as ED and interhospital transfers for stroke codes, trauma codes, code blue, or myocardial infarction codes. In our department, as we started the process of PCS for stroke codes, we included NCOT-PC for stroke patients with neurologic dysfunction.
The results of our initiative are largely limited by the decision-making process of Med-Com when patients are called in for testing. At the time of our project, there were no specific criteria used for patients with altered mental status, except for the standard screening methods, and it was through clinician-to-clinician discussion that testing decisions were made. Another limitation is the short period of time that the NCOT-PC was applied before adoption.
In summary, the NCOT-PC tool improved the screening process for COVID-19 testing in patients with neurologic dysfunction admitted to the NSICU. It was feasible and prevented unprotected staff and patient exposure to COVID-19. The NCOT-PC functionality was compatible with institutional COVID-19 policies in place, which contributed to its overall sustainability.
The Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) were utilized in preparing this manuscript.9
Acknowledgment: The authors thank the University of Mississippi Medical Center NSICU staff for their input with implementation of the NCOT-PC.
Corresponding author: Prashant A. Natteru, MD, University of Mississippi Medical Center, Department of Neurology, 2500 North State St., Jackson, MS 39216; pnatteru@umc.edu.
Financial disclosures: None.
1. Coronavirus disease 2019 (COVID-19) Symptoms. www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html. Accessed April 9, 2020.
2. Mao L, Jin H, Wang M, et al. Neurologic manifestations of hospitalized patients with coronavirus disease 2019 in Wuhan, China. JAMA Neurol. 2020;77:1-9.
3. Khosravani H, Rajendram P, Notario L, et al. Protected code stroke: hyperacute stroke management during the coronavirus disease 2019. (COVID-19) pandemic. Stroke. 2020;51:1891-1895.
4. Coronavirus disease 2019 (COVID-19) evaluation and testing. www.cdc.gov/coronavirus/2019-nCoV/hcp/clinical-criteria.html. Accessed April 9, 2020.
5. Plan-Do-Study-Act Worksheet. Institute for Healthcare Improvement website. www.ihi.org/resources/Pages/Tools/PlanDoStudyActWorksheet.aspx. Accessed March 31,2020.
6. Li YC, Bai WZ, Hashikawa T. The neuroinvasive potential of SARS-CoV2 may play a role in the respiratory failure of COVID-19 patients. J Med Virol. 2020;10.1002/jmv.25728.
7. Rodriguez-Morales AJ, Cardona-Ospina JA, Gutiérrez-Ocampo E, et al. Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis. Travel Med Infect Dis. 2020;101623.
8. UMMC’s COVID-19 Clinical Processes. www.umc.edu/CoronaVirus/Mississippi-Health-Care-Professionals/Clinical-Resources/Clinical-Resources.html. Accessed April 9, 2020.
9. SQUIRE 2.0 (Standards for QUality Improvement Reporting Excellence): Revised Publication Guidelines from a Detailed Consensus Process. The EQUATOR Network. www.equator-network.org/reporting-guidelines/squire/. Accessed May 12, 2020.
From the University of Mississippi Medical Center, Department of Neurology, Division of Neuroscience Intensive Care, Jackson, MS.
Abstract
Objective: To test a coronavirus disease 2019 (COVID-19) screening tool to identify patients who qualify for testing among patients with neurologic dysfunction who are unable to answer the usual screening questions, which could help to prevent unprotected exposure of patients and health care workers to COVID-19.
Methods: The Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) was implemented at our institution for 1 week as a quality improvement project to improve the pathway for COVID-19 screening and testing among patients with neurologic dysfunction.
Results: A total of 14 new patients were admitted into the neuroscience intensive care unit (NSICU) service during the pilot period. The NCOT-PC was utilized on 9 (64%) patients with neurologic dysfunction; 7 of these patients were found to have a likelihood of requiring testing based on the NCOT-PC and were subsequently screened for COVID-19 testing by contacting the institution’s COVID-19 testing hotline (Med-Com). All these patients were subsequently transitioned into person-under-investigation status based on the determination from Med-Com. The NSICU staff involved were able to utilize NCOT-PC without issues. The NCOT-PC was immediately adopted into the NSICU process.
Conclusion: Use of the NCOT-PC tool was found to be feasible and improved the screening methodology of patients with neurologic dysfunction.
Keywords: coronavirus; health care planning; quality improvement; patient safety; medical decision-making; neuroscience intensive care unit.
The coronavirus disease 2019 (COVID-19) pandemic has altered various standard emergent care pathways. Current recommendations regarding COVID-19 screening for testing involve asking patients about their symptoms, including fever, cough, chest pain, and dyspnea.1 This standard screening method poses a problem when caring for patients with neurologic dysfunction. COVID-19 patients may pre-sent with conditions that affect their ability to answer questions, such as stroke, encephalitis, neuromuscular disorders, or headache, and that may preclude the use of standard screening for testing.2 Patients with acute neurologic dysfunction who cannot undergo standard screening may leave the emergency department (ED) and transition into the neuroscience intensive care unit (NSICU) or any intensive care unit (ICU) without a reliable COVID-19 screening test.
The Protected Code Stroke pathway offers protection in the emergent setting for patients with stroke when their COVID-19 status is unknown.3 A similar process has been applied at our institution for emergent management of patients with cerebrovascular disease (stroke, intracerebral hemorrhage, and subarachnoid hemorrhage). However, the process from the ED after designating “difficult to screen” patients as persons under investigation (PUI) is unclear. The Centers for Disease Control and Prevention (CDC) has delineated the priorities for testing, with not all declared PUIs requiring testing.4 This poses a great challenge, because patients designated as PUIs require the same management as a COVID-19-positive patient, with negative-pressure isolation rooms as well as use of protective personal equipment (PPE), which may not be readily available. It was also recognized that, because the ED staff can be overwhelmed by COVID-19 patients, there may not be enough time to perform detailed screening of patients with neurologic dysfunction and that “reverse masking” may not be done consistently for nonintubated patients. This may place patients and health care workers at risk of unprotected exposure.
Recognizing these challenges, we created a Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) as a quality improvement project. The aim of this project was to improve and standardize the current process of identifying patients with neurologic dysfunction who require COVID-19 testing to decrease the risk of unprotected exposure of patients and health care workers.
Methods
Patients and Definitions
This quality improvement project was undertaken at the University of Mississippi Medical Center NSICU. Because this was a quality improvement project, an Institutional Review Board exemption was granted.
The NCOT-PC was utilized in consecutive patients with neurologic dysfunction admitted to the NSICU during a period of 1 week. “Neurologic dysfunction” encompasses any neurologic illness affecting the mental status and/or level of alertness, subsequently precluding the ability to reliably screen the patient utilizing standard COVID-19 screening. “Med-Com” at our institution is the equivalent of the national COVID-19 testing hotline, where our institution’s infectious diseases experts screen calls for testing and determine whether testing is warranted. “Unprotected exposure” means exposure to COVID-19 without adequate and appropriate PPE.
Quality Improvement Process
As more PUIs were being admitted to the institution, we used the Plan-Do-Study-Act method for process improvements in the NSICU.5 NSICU stakeholders, including attendings, the nurse manager, and nurse practitioners (NPs), developed an algorithm to facilitate the coordination of the NSICU staff in screening patients to identify those with a high likelihood of needing COVID-19 testing upon arrival in the NSICU (Figure 1). Once the NCOT-PC was finalized, NSICU stakeholders were educated regarding the use of this screening tool.
The checklist clinicians review when screening patients is shown in Figure 2. The risk factors comprising the checklist include patient history and clinical and radiographic characteristics that have been shown to be relevant for identifying patients with COVID-19.6,7 The imaging criteria utilize imaging that is part of the standard of care for NSICU patients. For example, computed tomography angiogram of the head and neck performed as part of the acute stroke protocol captures the upper part of the chest. These images are utilized for their incidental findings, such as apical ground-glass opacities and tree-in-bud formation. The risk factors applicable to the patient determine whether the clinician will call Med-Com for testing approval. Institutional COVID-19 processes were then followed accordingly.8 The decision from Med-Com was considered final, and no deviation from institutional policies was allowed.
NCOT-PC was utilized for consecutive days for 1 week before re-evaluation of its feasibility and adaptability.
Data Collection and Analysis
Consecutive patients with neurologic dysfunction admitted into the NSICU were assigned nonlinkable patient numbers. No identifiers were collected for the purpose of this project. The primary diagnosis for admission, the neurologic dysfunction that precluded standard screening, and checklist components that the patient fulfilled were collected.
To assess the tool’s feasibility, feedback regarding the ease of use of the NCOT-PC was gathered from the nurses, NPs, charge nurses, fellows, and other attendings. To assess the utility of the NCOT-PC in identifying patients who will be approved for COVID-19 testing, we calculated the proportion of patients who were deemed to have a high likelihood of testing and the proportion of patients who were approved for testing. Descriptive statistics were used, as applicable for the project, to summarize the utility of the NCOT-PC.
Results
We found that the NCOT-PC can be easily used by clinicians. The NSICU staff did not communicate any implementation issues, and since the NCOT-PC was implemented, no problems have been identified.
During the pilot period of the NCOT-PC, 14 new patients were admitted to the NSICU service. Nine (64%) of these had neurologic dysfunction, and the NCOT-PC was used to determine whether Med-Com should be called based on the patients’ likelihood (high vs low) of needing a COVID-19 test. Of those patients with neurologic dysfunction, 7 (78%) were deemed to have a high likelihood of needing a COVID-19 test based on the NCOT-PC. Med-Com was contacted regarding these patients, and all were deemed to require the COVID-19 test by Med-Com and were transitioned into PUI status per institutional policy (Table).
Discussion
The NCOT-PC project improved and standardized the process of identifying and screening patients with neurologic dysfunction for COVID-19 testing. The screening tool is feasible to use, and it decreased inadvertent unprotected exposure of patients and health care workers.
The NCOT-PC was easy to administer. Educating the staff regarding the new process took only a few minutes and involved a meeting with the nurse manager, NPs, fellows, residents, and attendings. We found that this process works well in tandem with the standard institutional processes in place in terms of Protected Code Stroke pathway, PUI isolation, PPE use, and Med-Com screening for COVID-19 testing. Med-Com was called only if the patient fulfilled the checklist criteria. In addition, no extra cost was attributed to implementing the NCOT-PC, since we utilized imaging that was already done as part of the standard of care for patients with neurologic dysfunction.
The standardization of the process of screening for COVID-19 testing among patients with neurologic dysfunction improved patient selection. Before the NCOT-PC, there was no consistency in terms of who should get tested and the reason for testing patients with neurologic dysfunction. Patients can pass through the ED and arrive in the NSICU with an unclear screening status, which may cause inadvertent patient and health care worker exposure to COVID-19. With the NCOT-PC, we have avoided instances of inadvertent staff or patient exposure in the NSICU.
The NCOT-PC was adopted into the NSICU process after the first week it was piloted. Beyond the NSICU, the application of the NCOT-PC can be extended to any patient presentation that precludes standard screening, such as ED and interhospital transfers for stroke codes, trauma codes, code blue, or myocardial infarction codes. In our department, as we started the process of PCS for stroke codes, we included NCOT-PC for stroke patients with neurologic dysfunction.
The results of our initiative are largely limited by the decision-making process of Med-Com when patients are called in for testing. At the time of our project, there were no specific criteria used for patients with altered mental status, except for the standard screening methods, and it was through clinician-to-clinician discussion that testing decisions were made. Another limitation is the short period of time that the NCOT-PC was applied before adoption.
In summary, the NCOT-PC tool improved the screening process for COVID-19 testing in patients with neurologic dysfunction admitted to the NSICU. It was feasible and prevented unprotected staff and patient exposure to COVID-19. The NCOT-PC functionality was compatible with institutional COVID-19 policies in place, which contributed to its overall sustainability.
The Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) were utilized in preparing this manuscript.9
Acknowledgment: The authors thank the University of Mississippi Medical Center NSICU staff for their input with implementation of the NCOT-PC.
Corresponding author: Prashant A. Natteru, MD, University of Mississippi Medical Center, Department of Neurology, 2500 North State St., Jackson, MS 39216; pnatteru@umc.edu.
Financial disclosures: None.
From the University of Mississippi Medical Center, Department of Neurology, Division of Neuroscience Intensive Care, Jackson, MS.
Abstract
Objective: To test a coronavirus disease 2019 (COVID-19) screening tool to identify patients who qualify for testing among patients with neurologic dysfunction who are unable to answer the usual screening questions, which could help to prevent unprotected exposure of patients and health care workers to COVID-19.
Methods: The Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) was implemented at our institution for 1 week as a quality improvement project to improve the pathway for COVID-19 screening and testing among patients with neurologic dysfunction.
Results: A total of 14 new patients were admitted into the neuroscience intensive care unit (NSICU) service during the pilot period. The NCOT-PC was utilized on 9 (64%) patients with neurologic dysfunction; 7 of these patients were found to have a likelihood of requiring testing based on the NCOT-PC and were subsequently screened for COVID-19 testing by contacting the institution’s COVID-19 testing hotline (Med-Com). All these patients were subsequently transitioned into person-under-investigation status based on the determination from Med-Com. The NSICU staff involved were able to utilize NCOT-PC without issues. The NCOT-PC was immediately adopted into the NSICU process.
Conclusion: Use of the NCOT-PC tool was found to be feasible and improved the screening methodology of patients with neurologic dysfunction.
Keywords: coronavirus; health care planning; quality improvement; patient safety; medical decision-making; neuroscience intensive care unit.
The coronavirus disease 2019 (COVID-19) pandemic has altered various standard emergent care pathways. Current recommendations regarding COVID-19 screening for testing involve asking patients about their symptoms, including fever, cough, chest pain, and dyspnea.1 This standard screening method poses a problem when caring for patients with neurologic dysfunction. COVID-19 patients may pre-sent with conditions that affect their ability to answer questions, such as stroke, encephalitis, neuromuscular disorders, or headache, and that may preclude the use of standard screening for testing.2 Patients with acute neurologic dysfunction who cannot undergo standard screening may leave the emergency department (ED) and transition into the neuroscience intensive care unit (NSICU) or any intensive care unit (ICU) without a reliable COVID-19 screening test.
The Protected Code Stroke pathway offers protection in the emergent setting for patients with stroke when their COVID-19 status is unknown.3 A similar process has been applied at our institution for emergent management of patients with cerebrovascular disease (stroke, intracerebral hemorrhage, and subarachnoid hemorrhage). However, the process from the ED after designating “difficult to screen” patients as persons under investigation (PUI) is unclear. The Centers for Disease Control and Prevention (CDC) has delineated the priorities for testing, with not all declared PUIs requiring testing.4 This poses a great challenge, because patients designated as PUIs require the same management as a COVID-19-positive patient, with negative-pressure isolation rooms as well as use of protective personal equipment (PPE), which may not be readily available. It was also recognized that, because the ED staff can be overwhelmed by COVID-19 patients, there may not be enough time to perform detailed screening of patients with neurologic dysfunction and that “reverse masking” may not be done consistently for nonintubated patients. This may place patients and health care workers at risk of unprotected exposure.
Recognizing these challenges, we created a Neuro-COVID-19 Time-out Process and Checklist (NCOT-PC) as a quality improvement project. The aim of this project was to improve and standardize the current process of identifying patients with neurologic dysfunction who require COVID-19 testing to decrease the risk of unprotected exposure of patients and health care workers.
Methods
Patients and Definitions
This quality improvement project was undertaken at the University of Mississippi Medical Center NSICU. Because this was a quality improvement project, an Institutional Review Board exemption was granted.
The NCOT-PC was utilized in consecutive patients with neurologic dysfunction admitted to the NSICU during a period of 1 week. “Neurologic dysfunction” encompasses any neurologic illness affecting the mental status and/or level of alertness, subsequently precluding the ability to reliably screen the patient utilizing standard COVID-19 screening. “Med-Com” at our institution is the equivalent of the national COVID-19 testing hotline, where our institution’s infectious diseases experts screen calls for testing and determine whether testing is warranted. “Unprotected exposure” means exposure to COVID-19 without adequate and appropriate PPE.
Quality Improvement Process
As more PUIs were being admitted to the institution, we used the Plan-Do-Study-Act method for process improvements in the NSICU.5 NSICU stakeholders, including attendings, the nurse manager, and nurse practitioners (NPs), developed an algorithm to facilitate the coordination of the NSICU staff in screening patients to identify those with a high likelihood of needing COVID-19 testing upon arrival in the NSICU (Figure 1). Once the NCOT-PC was finalized, NSICU stakeholders were educated regarding the use of this screening tool.
The checklist clinicians review when screening patients is shown in Figure 2. The risk factors comprising the checklist include patient history and clinical and radiographic characteristics that have been shown to be relevant for identifying patients with COVID-19.6,7 The imaging criteria utilize imaging that is part of the standard of care for NSICU patients. For example, computed tomography angiogram of the head and neck performed as part of the acute stroke protocol captures the upper part of the chest. These images are utilized for their incidental findings, such as apical ground-glass opacities and tree-in-bud formation. The risk factors applicable to the patient determine whether the clinician will call Med-Com for testing approval. Institutional COVID-19 processes were then followed accordingly.8 The decision from Med-Com was considered final, and no deviation from institutional policies was allowed.
NCOT-PC was utilized for consecutive days for 1 week before re-evaluation of its feasibility and adaptability.
Data Collection and Analysis
Consecutive patients with neurologic dysfunction admitted into the NSICU were assigned nonlinkable patient numbers. No identifiers were collected for the purpose of this project. The primary diagnosis for admission, the neurologic dysfunction that precluded standard screening, and checklist components that the patient fulfilled were collected.
To assess the tool’s feasibility, feedback regarding the ease of use of the NCOT-PC was gathered from the nurses, NPs, charge nurses, fellows, and other attendings. To assess the utility of the NCOT-PC in identifying patients who will be approved for COVID-19 testing, we calculated the proportion of patients who were deemed to have a high likelihood of testing and the proportion of patients who were approved for testing. Descriptive statistics were used, as applicable for the project, to summarize the utility of the NCOT-PC.
Results
We found that the NCOT-PC can be easily used by clinicians. The NSICU staff did not communicate any implementation issues, and since the NCOT-PC was implemented, no problems have been identified.
During the pilot period of the NCOT-PC, 14 new patients were admitted to the NSICU service. Nine (64%) of these had neurologic dysfunction, and the NCOT-PC was used to determine whether Med-Com should be called based on the patients’ likelihood (high vs low) of needing a COVID-19 test. Of those patients with neurologic dysfunction, 7 (78%) were deemed to have a high likelihood of needing a COVID-19 test based on the NCOT-PC. Med-Com was contacted regarding these patients, and all were deemed to require the COVID-19 test by Med-Com and were transitioned into PUI status per institutional policy (Table).
Discussion
The NCOT-PC project improved and standardized the process of identifying and screening patients with neurologic dysfunction for COVID-19 testing. The screening tool is feasible to use, and it decreased inadvertent unprotected exposure of patients and health care workers.
The NCOT-PC was easy to administer. Educating the staff regarding the new process took only a few minutes and involved a meeting with the nurse manager, NPs, fellows, residents, and attendings. We found that this process works well in tandem with the standard institutional processes in place in terms of Protected Code Stroke pathway, PUI isolation, PPE use, and Med-Com screening for COVID-19 testing. Med-Com was called only if the patient fulfilled the checklist criteria. In addition, no extra cost was attributed to implementing the NCOT-PC, since we utilized imaging that was already done as part of the standard of care for patients with neurologic dysfunction.
The standardization of the process of screening for COVID-19 testing among patients with neurologic dysfunction improved patient selection. Before the NCOT-PC, there was no consistency in terms of who should get tested and the reason for testing patients with neurologic dysfunction. Patients can pass through the ED and arrive in the NSICU with an unclear screening status, which may cause inadvertent patient and health care worker exposure to COVID-19. With the NCOT-PC, we have avoided instances of inadvertent staff or patient exposure in the NSICU.
The NCOT-PC was adopted into the NSICU process after the first week it was piloted. Beyond the NSICU, the application of the NCOT-PC can be extended to any patient presentation that precludes standard screening, such as ED and interhospital transfers for stroke codes, trauma codes, code blue, or myocardial infarction codes. In our department, as we started the process of PCS for stroke codes, we included NCOT-PC for stroke patients with neurologic dysfunction.
The results of our initiative are largely limited by the decision-making process of Med-Com when patients are called in for testing. At the time of our project, there were no specific criteria used for patients with altered mental status, except for the standard screening methods, and it was through clinician-to-clinician discussion that testing decisions were made. Another limitation is the short period of time that the NCOT-PC was applied before adoption.
In summary, the NCOT-PC tool improved the screening process for COVID-19 testing in patients with neurologic dysfunction admitted to the NSICU. It was feasible and prevented unprotected staff and patient exposure to COVID-19. The NCOT-PC functionality was compatible with institutional COVID-19 policies in place, which contributed to its overall sustainability.
The Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) were utilized in preparing this manuscript.9
Acknowledgment: The authors thank the University of Mississippi Medical Center NSICU staff for their input with implementation of the NCOT-PC.
Corresponding author: Prashant A. Natteru, MD, University of Mississippi Medical Center, Department of Neurology, 2500 North State St., Jackson, MS 39216; pnatteru@umc.edu.
Financial disclosures: None.
1. Coronavirus disease 2019 (COVID-19) Symptoms. www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html. Accessed April 9, 2020.
2. Mao L, Jin H, Wang M, et al. Neurologic manifestations of hospitalized patients with coronavirus disease 2019 in Wuhan, China. JAMA Neurol. 2020;77:1-9.
3. Khosravani H, Rajendram P, Notario L, et al. Protected code stroke: hyperacute stroke management during the coronavirus disease 2019. (COVID-19) pandemic. Stroke. 2020;51:1891-1895.
4. Coronavirus disease 2019 (COVID-19) evaluation and testing. www.cdc.gov/coronavirus/2019-nCoV/hcp/clinical-criteria.html. Accessed April 9, 2020.
5. Plan-Do-Study-Act Worksheet. Institute for Healthcare Improvement website. www.ihi.org/resources/Pages/Tools/PlanDoStudyActWorksheet.aspx. Accessed March 31,2020.
6. Li YC, Bai WZ, Hashikawa T. The neuroinvasive potential of SARS-CoV2 may play a role in the respiratory failure of COVID-19 patients. J Med Virol. 2020;10.1002/jmv.25728.
7. Rodriguez-Morales AJ, Cardona-Ospina JA, Gutiérrez-Ocampo E, et al. Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis. Travel Med Infect Dis. 2020;101623.
8. UMMC’s COVID-19 Clinical Processes. www.umc.edu/CoronaVirus/Mississippi-Health-Care-Professionals/Clinical-Resources/Clinical-Resources.html. Accessed April 9, 2020.
9. SQUIRE 2.0 (Standards for QUality Improvement Reporting Excellence): Revised Publication Guidelines from a Detailed Consensus Process. The EQUATOR Network. www.equator-network.org/reporting-guidelines/squire/. Accessed May 12, 2020.
1. Coronavirus disease 2019 (COVID-19) Symptoms. www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/symptoms.html. Accessed April 9, 2020.
2. Mao L, Jin H, Wang M, et al. Neurologic manifestations of hospitalized patients with coronavirus disease 2019 in Wuhan, China. JAMA Neurol. 2020;77:1-9.
3. Khosravani H, Rajendram P, Notario L, et al. Protected code stroke: hyperacute stroke management during the coronavirus disease 2019. (COVID-19) pandemic. Stroke. 2020;51:1891-1895.
4. Coronavirus disease 2019 (COVID-19) evaluation and testing. www.cdc.gov/coronavirus/2019-nCoV/hcp/clinical-criteria.html. Accessed April 9, 2020.
5. Plan-Do-Study-Act Worksheet. Institute for Healthcare Improvement website. www.ihi.org/resources/Pages/Tools/PlanDoStudyActWorksheet.aspx. Accessed March 31,2020.
6. Li YC, Bai WZ, Hashikawa T. The neuroinvasive potential of SARS-CoV2 may play a role in the respiratory failure of COVID-19 patients. J Med Virol. 2020;10.1002/jmv.25728.
7. Rodriguez-Morales AJ, Cardona-Ospina JA, Gutiérrez-Ocampo E, et al. Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis. Travel Med Infect Dis. 2020;101623.
8. UMMC’s COVID-19 Clinical Processes. www.umc.edu/CoronaVirus/Mississippi-Health-Care-Professionals/Clinical-Resources/Clinical-Resources.html. Accessed April 9, 2020.
9. SQUIRE 2.0 (Standards for QUality Improvement Reporting Excellence): Revised Publication Guidelines from a Detailed Consensus Process. The EQUATOR Network. www.equator-network.org/reporting-guidelines/squire/. Accessed May 12, 2020.
A Multidisciplinary Ambulation Protocol to Reduce Postoperative Venous Thromboembolism After Colorectal Surgery
From the Department of Surgery, Washington University School of Medicine, St. Louis, MO.
Abstract
Background: Patients undergoing colorectal surgery are at high risk for postoperative venous thromboembolism (VTE). Early ambulation has been encouraged to lower rates of VTE, but evidence demonstrating its effectiveness outside of a bundle is limited.
Objective: To create a multidisciplinary ambulation protocol in an effort to reduce postoperative VTE.
Methods: A single-center, retrospective, comparative study of patients who underwent colectomy or proctectomy was conducted. Outcomes of patients operated on prior to protocol implementation were compared with a cohort after implementation. The intervention studied was the implementation of a multidisciplinary ambulation protocol. The primary endpoint was postoperative VTE.
Results: There was no difference between the pre-intervention group (n = 1762) and the postintervention group (n = 253) in terms of sex, race, origin, emergency status, operative time, and the majority of medical comorbidities (with the exception of smoking status and congestive heart failure). After the protocol was implemented, ambulation rates on postoperative days 0, 1, and 2 improved from 36.4%, 47.3%, and 50.2% to 36.8%, 74.7%, and 82.6%, respectively The VTE rate in the pre-intervention group was 2.7% versus a rate of 0.4% in the postintervention group (P = 0.02).
Conclusion: Creation of an ambulation protocol is associated with a significant reduction in VTE. Commitment from patients, families, nurses, physician extenders, and physicians is critical to the success of the program.
Keywords: VTE; pulmonary embolism; deep vein thrombosis; postoperative; quality improvement.
Postoperative venous thromboembolism (VTE) is a significant source of morbidity, mortality, and cost.1,2 Colorectal surgery patients are at particularly high risk for VTE due to positioning during surgery, pelvic dissection, and other conditions often found in these patients, such as cancer and inflammatory bowel disease.3 A National Surgical Quality Improvement Program (NSQIP) analysis demonstrated an overall rate of VTE in colorectal surgery patients of 2.4%, although other studies have demonstrated rates up to 9%, even in those receiving appropriate chemoprophylaxis.4-6 Many of these VTEs occur in the postdischarge setting. In a NSQIP study of colorectal surgery patients, the rate of VTE between discharge and 30 days was 0.47%.7 The cost burdenfor a postoperative VTE has been estimated to be more than $18,000.8
Studies from NSQIP have identified multiple factors associated with VTE in colorectal surgery patients, but NSQIP does not record ambulation as a standard variable.9 Multiple strategies have been implemented to reduce postoperative VTE. Often, these studies focus on increasing compliance with appropriate chemoprophylaxis, risk stratification, or bundling multiple strategies.10,11 However, despite the fact that postsurgical ambulation is widely encouraged and recommended by the American Society of Colon and Rectal Surgeons clinical practice guidelines, there is little evidence demonstrating the role of ambulation alone in the reduction of VTE.4,12 The purpose of this study was to create a multidisciplinary protocol to increase postoperative ambulation and evaluate its effect on VTE.
Methods
Setting
This study was conducted at a single academic tertiary care center.
Patients and Outcome Measures
All patients undergoing colectomy or proctectomy by surgeons in the section of colon and rectal surgery at a single institution between January 2011 and March 2017 were included. Colectomy and proctectomy were defined by CPT codes 44140, 44141, 44143, 44144, 44145, 44146, 44147, 44150, 44151, 44155, 44156, 44157, 44158, 44160, 44204, 44205, 44206, 44207, 44208, 44210, 44211, 44212, 44213, 45110, 45111, 45112, 45113, 45114, 45116, 45119, 45120, 45121, 45123, 45126, 45160, 45395, and 45397. The primary outcome of VTE within 30 days, including deep venous thrombosis (DVT) and pulmonary embolism (PE), was measured using institution-specific data from NSQIP in both the pre-intervention and postintervention setting. The occurrence of both DVT and PE in 1 patient was counted as a single event of VTE. Ambulation rate on postoperative day (POD) 0, 1, and 2 was calculated by NSQIP in the pre-intervention setting (our institution-specific NSQIP recorded ambulation data for an unrelated project) and by review of the electronic health record in the postintervention setting, as this institution-specific variable was no longer being collected. Ambulation was defined as getting out of bed and taking at least 1 step. The threshold for ambulating each day was once on POD 0 and twice on PODs 1 and 2. Patients with missing ambulation data were excluded from the analysis. Both prior to and throughout the intervention, all patients were given VTE chemoprophylaxis with either low-dose unfractionated heparin or low-molecular-weight heparin prior to induction of anesthesia, with chemoprophylaxis extending an additional 21 days after discharge (unless specifically contraindicated); sequential compression devices; and standard orders to ambulate 3 times daily from POD 0 as part of the standard Enhanced Recovery After Surgery protocol.
Analysis
Statistical analysis was performed using univariate analysis. Chi-square test and univariate logistic regression were used to determine the association between ambulation rates and VTE in the pre-intervention group. Chi-square test was also used to compare ambulation and VTE rates between the pre-intervention and postintervention groups. Plan-Do-Study-Act (PDSA) cycle fidelity (the degree to which a PDSA cycle is carried out in accordance with the guiding principles of its use) was measured by recording the ambulation rates both before and after the intervention.13 Statistical analysis was performed using SAS Version 9.4 (SAS Institute, Cary, NC). This study was reviewed by the Washington University School of Medicine Institutional Review Board and deemed to be quality improvement, not human subjects research, and therefore did not require formal approval.
Baseline Outcome Rates
A total of 1762 patients were identified during the pre-intervention period. The overall VTE rate in the pre-intervention group was 2.7% (n = 48), with 39 DVTs (2.2%) and 13 PEs (0.7%). Pre-intervention ambulation data were available on 590 patients. Baseline ambulation rates on PODs 0, 1, and 2 were 36.4% (213/590), 47.3% (279/590), and 50.2% (296/590), respectively. Patients who did not ambulate on POD 0 had a VTE rate of 4.3%, as compared to 0.9% in those who did ambulate (Table 1). Patients who did not ambulate twice on POD 1 had a VTE rate of 4.8%, compared to 1.1% in those who did ambulate (odds ratio [OR], 4.66; 95% confidence interval [CI], 1.34 to 16.28). Patients who did not ambulate twice on POD 2 had a VTE rate of 5.4%, compared to 0.7% in those who did. Finally, those who ambulated twice on both PODs 1 and 2 had a 0% rate of VTE, compared to 4.9% in those who did not ambulate on both PODs.
Ambulation Protocol
After baseline outcome rates had been established, a multidisciplinary team of medical assistants, nurses, nurse practitioners, and physicians worked together to identify all processes that involved postoperative ambulation. Given the significant differences in VTE rates between patients who ambulated and those that did not, we created a multidisciplinary ambulation protocol using the PDSA method.14 Multiple points of patient contact were chosen for intervention, and the ambulation protocol was implemented in June 2018 and continued for 7 months.
Patients were observed from their initial office visit with a surgeon, during the preoperative education encounter, and in the operating room and on the surgical ward until discharge. Representatives from multiple disciplines who encountered patients at various times in the process, including medical assistants, patient care technicians, nurses, nurse practitioners, physical therapists, and physicians, participated in a kick-off meeting to identify difficulties they encounter when encouraging patient ambulation. The following 4 areas were identified.
Barriers to Patient Ambulation
Patient Expectations. Patients did not appear to have a clear expectation of what their ambulation goals were postoperatively, despite the fact that each patient is given an operative pathway booklet that includes their goals for each day, including ambulation. The consensus was that patients were overwhelmed with the amount of information and, oftentimes, the severity of their diagnosis, so the information regarding ambulation was not retained. Nurses commented that patients frequently stated that they did not think their surgeon wanted them to get out of bed postoperatively.
Electronic Orders. There was confusion within the nursing staff regarding orders in the electronic health record compared to physician expectations. Orders stated patients should ambulate 3 times daily, but did not specify on which postoperative day this should start. Often, nursing verbal sign-out from the post-anesthesia care unit (PACU) would be an order for bedrest, despite no clear origin of this order. This created confusion among the nursing staff as to what the appropriate ambulation orders should be.
Nursing Workflow. The initial state of the nursing workflow was not conducive to evaluating for, or assisting with, ambulation. With no set time to assist and evaluate patients for ambulation, it turned into a task nurses needed to accomplish when they had extra time. With increasing demands of charting in the electronic health record, nurses often had to skip ambulation in order to accomplish other tasks.
Family Expectations. In addition to patient expectations, family members often had expectations that were not congruent with the planned postoperative course. Nurses stated family members would often tell them that they did not feel that their family member should be ambulating so soon after surgery. Often these family members had not attended preoperative education sessions with the patient. This was compounded by the uncertainty among the nursing staff regarding what exactly the ambulation orders were.
Interventions
Targeted interventions were created to address these 4 barriers to ambulation identified by staff.
Preoperative Education. Although all elective patients received a printed operative pathway booklet describing daily goals, including ambulation, patients still did not have a sufficient understanding of what was expected of them. The education session was modified to increase the time spent on both the expectation for and the rationale behind ambulation. That section of the education session ended with a verbal commitment and read-back of the expectations for ambulation by the patient.
Clarification of Electronic Orders. Postoperative orders within the colorectal standard pathway were changed, including specific time frames and frequency, to match the information provided in the patient education booklet. These orders were for ambulation within 4 hours of arrival to the floor, and the orders also noted that no patient should be on bedrest unless explicitly stated. From POD 1, all patients were to ambulate at least twice daily for the remainder of the hospital stay (patients were encouraged to walk 4 times daily, but we set a minimum expectation of twice daily for the order set). These orders were clarified with in-person meetings with the nursing staff and leadership from the PACU and the colorectal surgical ward.
Adjusted Nursing Workflow. Nurses were interviewed and asked to create a plan regarding how they could better incorporate ambulation into their daily workflow. Ambulation assessment was incorporated into the twice-per-shift recording of vital signs and patient safety assessment. This was recorded into the electronic health record at the same time as the patients’ vital signs. This allowed nurses to keep track of which patients would need extra assistance in ambulation and which patients were doing well on their own with the assistance of family. It also helped focus the resources of physical therapy and the single ambulation technician on the floor and to assist patients who needed more assistance.
Creation of Ambulation Encouragement Signs. The authors discovered that despite patients being told preoperatively about ambulation expectations, friends and family are not always included in these conversations. As nurses frequently cited both patients and family as reasons patients thought they should not walk, multiple signs inviting patients to take an active role in their recovery by ambulating were created and placed around the unit. The signs outlined the expectations of being out of bed and taking at least 1 step on the day of surgery and walking at least 4 times per day thereafter. In addition, we addressed frequently asked questions around issues such as walking with intravenous poles and urinary catheters. The posters were signed by all staff colorectal surgeons.
Results
Over the course of 7 months (June 2018 to December 2018), 253 postintervention patients were identified (Table 2). There was no difference between the pre-intervention group (n = 1762) and the postintervention group in terms of sex, race, origin, emergency status, operative time, and the majority of medical comorbidities (with the exception of smoking status and congestive heart failure). The postintervention group was slightly older (60 versus 57 years) and had a higher percentage of patients with an American Society of Anesthesiologists physical status score greater than 2 (66.8% versus 51.2%). The postintervention group also had higher rates of both malignancy (53.4% versus 33.3%) and inflammatory bowel disease (18.2% versus 14.4%).
The fidelity of the PDSA cycle was measured by pre-intervention and postintervention ambulation rates. Ambulation rates on POD 0, 1, and 2 improved from 36.4%, 47.3%, and 50.2% to 36.8%, 74.7%, and 82.6%, respectively (Table 3). The VTE rate decreased from 2.7% to 0.4% (P = 0.02), with 1 DVT and 0 PEs. It should be noted that the only patient who developed a VTE postintervention did not ambulate on PODs 0, 1, or 2.
Discussion
Postoperative VTE is a severe complication for postoperative colorectal surgery patients. Previous studies have demonstrated that increasing ambulation is associated with a lower rate of overall complications, and, when incorporated into a bundle, is associated with decreased rates of VTE.11,15 However, this is the first study to our knowledge demonstrating that creation of an ambulation protocol alone is associated with a decrease in VTE.
Analysis of pre-intervention data demonstrated a strong association between ambulation and an absence of VTE. No patient who ambulated on PODs 0, 1, and 2 developed a VTE. Based on those results, we moved forward with creating the ambulation protocol. While ambulation stayed stable on POD 0, there were 60% and 65% increases on PODs 1 and 2, respectively. Nurses cited late arrival to the floor for second and third start cases as the primary difficulty in getting patients to ambulate more on POD 0.
We believe the key to the success of the ambulation protocol was its multidisciplinary nature. Certainly, the easiest way to create an ambulation protocol is to change the postoperative orders to state patients must walk 4 times per day. However, if the nursing staff is unable or unwilling to carry out these orders, the orders serve little purpose. In order to make lasting changes, all stakeholders in the process must be identified. In our case, stakeholders included surgery and nursing leadership, surgeons, nurse practitioners, nurses, medical assistants, physical therapists, patient care technicians, and patients. This is where we utilized kaizen, a core principle of Lean methodology that empowers employees at the level of the work being carried out to propose ideas for improvement.16 From the beginning of the patient experience, the health care practitioners who were carrying out each step of the process were best able to identify the problems and create solutions. In addition, stakeholders were given regular updates regarding how their efforts were increasing ambulation rates and the results at the end of the study period.
This study also demonstrates that, in a health care system increasingly focused on both quality and cost, significant improvements in quality can be made without increasing cost or resource utilization. Early in the process, it was proposed that the only way to increase the ambulation rate would be to increase the number of physical therapists, nurses, and nursing assistants. However, after identifying the root causes of the problem, the solutions had more to do with improving workflow and fixing problem areas identified by the staff.
In addition to having a positive effect on the outcome studied, collaborative projects such as this between physicians and nurses may lead to increased nursing job satisfaction. A meta-analysis of 31 studies identified nurse-physician collaboration and autonomy as 2 factors that correlate most strongly with nursing satisfaction.17 A Cochrane review also suggests that practice-based interprofessional collaboration may lead to improved health care processes and outcomes.18
This study has several limitations. Pre-intervention ambulation rates were abstracted from institution-specific NSQIP data, and missing data were excluded from analysis. Also, due to the retrospective collection of the pre-intervention data, the distance of ambulation could not be quantified. The bar for ambulation is low, as patients were only required to get out of bed and walk 1 step. However, we feel that getting out of bed and taking even 1 step is substantially better than complete bedrest. It is likely that once patients cross the threshold of taking 1 step, they are more likely to ambulate. An area of future study may be to more precisely define the relationship between the quantity of ambulation in steps and its effect on VTE. Finally, we acknowledge that while there is no direct increase in costs, implementing an ambulation protocol does take time from all who participate in the project.
Conclusion
Creation of an ambulation protocol is associated with a decrease in postoperative VTE rates in colorectal surgery patients. A multidisciplinary approach is critical to identify the underlying problems and propose effective solutions. Further studies are required to better correlate the distance of ambulation and its effect on VTE. However, this study shows that even a minimum of 1 step is associated with decreased VTE rates.
Corresponding author: Aneel Damle, MD, MBA, Colon & Rectal Surgery Associates, 3433 Broadway St. NE, Suite 115, Minneapolis, MN 55413; adamle@CRSAL.org.
Financial disclosures: None.
1. Gangireddy C, Rectenwald JR, Upchurch GR, et al. Risk factors and clinical impact of postoperative symptomatic venous thromboembolism. J Vasc Surg. 2007;45:341-342.
2. Newhook TE, LaPar DJ, Walters DM, et al. Impact of postoperative venous thromboembolism on postoperative morbidity, mortality, and resource utilization after hepatectomy. Am Surg. 2015;81:1216-1223.
3. Bergqvist D. Venous thromboembolism: a review of risk and prevention in colorectal surgery patients. Dis Colon Rectum. 2006;49:1620-1628.
4. Fleming F, Gaertner W, Ternent CA, et al. The American society of colon and rectal surgeons clinical practice guideline for the prevention of venous thromboembolic disease in colorectal surgery. Dis Colon Rectum. 2018;61:14-20.
5. McLeod RS, Geerts WH, Sniderman KW, et al. Canadian Colorectal Surgery DVT Prophylaxis Trial investigators. Subcutaneous heparin versus low-molecular-weight heparin as thromboprophylaxis in patients undergoing colorectal surgery: results of the Canadian colorectal DV prophylaxis trial: a randomized, double-blind trial. Ann Surg. 2001;233:438-444.
6. Shapiro R, Vogel JD, Kiran RP. Risk of postoperative venous thromboembolism after laparoscopic and open colorectal surgery: an additional benefit of the minimally invasive approach? Dis Colon Rectum. 2011;54:1496-1502.
7. Dimick JB, Chen SL, Taheri PA, et al. Hospital costs associated with surgical complications: a report from the private-sector National Surgical Quality Improvement Program. J Am Coll Surg. 2004;199:531-537.
8. Fleming FJ, Kim MJ, Salloum RM, et al. How much do we need to worry about venous thromboembolism after hospital discharge? A study of colorectal surgery patients using the National Surgical Quality Improvement Program database. Dis Colon Rectum. 2010;53:1355-1360.
9. ACS NSQIP. User guide for the 2016 ACS NSQIP participant use data file (PUF). 2017. www.facs.org/~/media/files/quality%20programs/nsqip/nsqip_puf_userguide_2016.ashx Accessed July 10, 2020.
10. Caprini JA. Risk assessment as a guide for the prevention of the many faces of venous thromboembolism. Am J Surg. 2010;199(1 Suppl):S3-S10.
11. Cassidy MR, Rosenkranz P, McAney D. Reducing postoperative venous thromboembolism complications with a standardized risk-stratified prophylaxis protocol and mobilization protocol. J Am Coll Surg. 2014;218:1095-1104.
12. Lau BD, Streiff MB, Kraus PS, et al. No evidence to support ambulation for reducing postoperative venous thromboembolism. J Am Coll Surg. 2014;219:1101-1103.
13. McNicholas C, Lennox L, Woodcock T, et al. Evolving quality improvement support strategies to improve Plan–Do–Study–Act cycle fidelity: a retrospective mixed-methods study. BMJ Qual Saf. 2019;28:356-365.
14. Taylor MJ, McNicholas C, Nicolay C, et al. Systematic review of the application of the plan–do–study–act method to improve quality in healthcare. BMC Qual Saf. 2014;23:290-298.
15. Nevo Y, Shaltiel T, Constantini N, et al. Effect of ambulation and physical activity on postoperative complications. J Am Coll Surg. 2016;223(Suppl 1):S61.
16. Mazzocato P, Stenfors-Hayes T, von Thiele Schwarz U, et al. Kaizen practice in healthcare: a qualitative analysis of hospital employees’ suggestions for improvement. BMJ Open. 2016;6:e012256.
17. Zangaro GA, Soeken KL. A meta-analysis of studies of nurses’ job satisfaction. Res Nursing Health. 2007;30:445-458.
18. Reeves S, Pelone F, Harrison R, et al. Interprofessional collaboration to improve professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2017;6(6):CD000072.
From the Department of Surgery, Washington University School of Medicine, St. Louis, MO.
Abstract
Background: Patients undergoing colorectal surgery are at high risk for postoperative venous thromboembolism (VTE). Early ambulation has been encouraged to lower rates of VTE, but evidence demonstrating its effectiveness outside of a bundle is limited.
Objective: To create a multidisciplinary ambulation protocol in an effort to reduce postoperative VTE.
Methods: A single-center, retrospective, comparative study of patients who underwent colectomy or proctectomy was conducted. Outcomes of patients operated on prior to protocol implementation were compared with a cohort after implementation. The intervention studied was the implementation of a multidisciplinary ambulation protocol. The primary endpoint was postoperative VTE.
Results: There was no difference between the pre-intervention group (n = 1762) and the postintervention group (n = 253) in terms of sex, race, origin, emergency status, operative time, and the majority of medical comorbidities (with the exception of smoking status and congestive heart failure). After the protocol was implemented, ambulation rates on postoperative days 0, 1, and 2 improved from 36.4%, 47.3%, and 50.2% to 36.8%, 74.7%, and 82.6%, respectively The VTE rate in the pre-intervention group was 2.7% versus a rate of 0.4% in the postintervention group (P = 0.02).
Conclusion: Creation of an ambulation protocol is associated with a significant reduction in VTE. Commitment from patients, families, nurses, physician extenders, and physicians is critical to the success of the program.
Keywords: VTE; pulmonary embolism; deep vein thrombosis; postoperative; quality improvement.
Postoperative venous thromboembolism (VTE) is a significant source of morbidity, mortality, and cost.1,2 Colorectal surgery patients are at particularly high risk for VTE due to positioning during surgery, pelvic dissection, and other conditions often found in these patients, such as cancer and inflammatory bowel disease.3 A National Surgical Quality Improvement Program (NSQIP) analysis demonstrated an overall rate of VTE in colorectal surgery patients of 2.4%, although other studies have demonstrated rates up to 9%, even in those receiving appropriate chemoprophylaxis.4-6 Many of these VTEs occur in the postdischarge setting. In a NSQIP study of colorectal surgery patients, the rate of VTE between discharge and 30 days was 0.47%.7 The cost burdenfor a postoperative VTE has been estimated to be more than $18,000.8
Studies from NSQIP have identified multiple factors associated with VTE in colorectal surgery patients, but NSQIP does not record ambulation as a standard variable.9 Multiple strategies have been implemented to reduce postoperative VTE. Often, these studies focus on increasing compliance with appropriate chemoprophylaxis, risk stratification, or bundling multiple strategies.10,11 However, despite the fact that postsurgical ambulation is widely encouraged and recommended by the American Society of Colon and Rectal Surgeons clinical practice guidelines, there is little evidence demonstrating the role of ambulation alone in the reduction of VTE.4,12 The purpose of this study was to create a multidisciplinary protocol to increase postoperative ambulation and evaluate its effect on VTE.
Methods
Setting
This study was conducted at a single academic tertiary care center.
Patients and Outcome Measures
All patients undergoing colectomy or proctectomy by surgeons in the section of colon and rectal surgery at a single institution between January 2011 and March 2017 were included. Colectomy and proctectomy were defined by CPT codes 44140, 44141, 44143, 44144, 44145, 44146, 44147, 44150, 44151, 44155, 44156, 44157, 44158, 44160, 44204, 44205, 44206, 44207, 44208, 44210, 44211, 44212, 44213, 45110, 45111, 45112, 45113, 45114, 45116, 45119, 45120, 45121, 45123, 45126, 45160, 45395, and 45397. The primary outcome of VTE within 30 days, including deep venous thrombosis (DVT) and pulmonary embolism (PE), was measured using institution-specific data from NSQIP in both the pre-intervention and postintervention setting. The occurrence of both DVT and PE in 1 patient was counted as a single event of VTE. Ambulation rate on postoperative day (POD) 0, 1, and 2 was calculated by NSQIP in the pre-intervention setting (our institution-specific NSQIP recorded ambulation data for an unrelated project) and by review of the electronic health record in the postintervention setting, as this institution-specific variable was no longer being collected. Ambulation was defined as getting out of bed and taking at least 1 step. The threshold for ambulating each day was once on POD 0 and twice on PODs 1 and 2. Patients with missing ambulation data were excluded from the analysis. Both prior to and throughout the intervention, all patients were given VTE chemoprophylaxis with either low-dose unfractionated heparin or low-molecular-weight heparin prior to induction of anesthesia, with chemoprophylaxis extending an additional 21 days after discharge (unless specifically contraindicated); sequential compression devices; and standard orders to ambulate 3 times daily from POD 0 as part of the standard Enhanced Recovery After Surgery protocol.
Analysis
Statistical analysis was performed using univariate analysis. Chi-square test and univariate logistic regression were used to determine the association between ambulation rates and VTE in the pre-intervention group. Chi-square test was also used to compare ambulation and VTE rates between the pre-intervention and postintervention groups. Plan-Do-Study-Act (PDSA) cycle fidelity (the degree to which a PDSA cycle is carried out in accordance with the guiding principles of its use) was measured by recording the ambulation rates both before and after the intervention.13 Statistical analysis was performed using SAS Version 9.4 (SAS Institute, Cary, NC). This study was reviewed by the Washington University School of Medicine Institutional Review Board and deemed to be quality improvement, not human subjects research, and therefore did not require formal approval.
Baseline Outcome Rates
A total of 1762 patients were identified during the pre-intervention period. The overall VTE rate in the pre-intervention group was 2.7% (n = 48), with 39 DVTs (2.2%) and 13 PEs (0.7%). Pre-intervention ambulation data were available on 590 patients. Baseline ambulation rates on PODs 0, 1, and 2 were 36.4% (213/590), 47.3% (279/590), and 50.2% (296/590), respectively. Patients who did not ambulate on POD 0 had a VTE rate of 4.3%, as compared to 0.9% in those who did ambulate (Table 1). Patients who did not ambulate twice on POD 1 had a VTE rate of 4.8%, compared to 1.1% in those who did ambulate (odds ratio [OR], 4.66; 95% confidence interval [CI], 1.34 to 16.28). Patients who did not ambulate twice on POD 2 had a VTE rate of 5.4%, compared to 0.7% in those who did. Finally, those who ambulated twice on both PODs 1 and 2 had a 0% rate of VTE, compared to 4.9% in those who did not ambulate on both PODs.
Ambulation Protocol
After baseline outcome rates had been established, a multidisciplinary team of medical assistants, nurses, nurse practitioners, and physicians worked together to identify all processes that involved postoperative ambulation. Given the significant differences in VTE rates between patients who ambulated and those that did not, we created a multidisciplinary ambulation protocol using the PDSA method.14 Multiple points of patient contact were chosen for intervention, and the ambulation protocol was implemented in June 2018 and continued for 7 months.
Patients were observed from their initial office visit with a surgeon, during the preoperative education encounter, and in the operating room and on the surgical ward until discharge. Representatives from multiple disciplines who encountered patients at various times in the process, including medical assistants, patient care technicians, nurses, nurse practitioners, physical therapists, and physicians, participated in a kick-off meeting to identify difficulties they encounter when encouraging patient ambulation. The following 4 areas were identified.
Barriers to Patient Ambulation
Patient Expectations. Patients did not appear to have a clear expectation of what their ambulation goals were postoperatively, despite the fact that each patient is given an operative pathway booklet that includes their goals for each day, including ambulation. The consensus was that patients were overwhelmed with the amount of information and, oftentimes, the severity of their diagnosis, so the information regarding ambulation was not retained. Nurses commented that patients frequently stated that they did not think their surgeon wanted them to get out of bed postoperatively.
Electronic Orders. There was confusion within the nursing staff regarding orders in the electronic health record compared to physician expectations. Orders stated patients should ambulate 3 times daily, but did not specify on which postoperative day this should start. Often, nursing verbal sign-out from the post-anesthesia care unit (PACU) would be an order for bedrest, despite no clear origin of this order. This created confusion among the nursing staff as to what the appropriate ambulation orders should be.
Nursing Workflow. The initial state of the nursing workflow was not conducive to evaluating for, or assisting with, ambulation. With no set time to assist and evaluate patients for ambulation, it turned into a task nurses needed to accomplish when they had extra time. With increasing demands of charting in the electronic health record, nurses often had to skip ambulation in order to accomplish other tasks.
Family Expectations. In addition to patient expectations, family members often had expectations that were not congruent with the planned postoperative course. Nurses stated family members would often tell them that they did not feel that their family member should be ambulating so soon after surgery. Often these family members had not attended preoperative education sessions with the patient. This was compounded by the uncertainty among the nursing staff regarding what exactly the ambulation orders were.
Interventions
Targeted interventions were created to address these 4 barriers to ambulation identified by staff.
Preoperative Education. Although all elective patients received a printed operative pathway booklet describing daily goals, including ambulation, patients still did not have a sufficient understanding of what was expected of them. The education session was modified to increase the time spent on both the expectation for and the rationale behind ambulation. That section of the education session ended with a verbal commitment and read-back of the expectations for ambulation by the patient.
Clarification of Electronic Orders. Postoperative orders within the colorectal standard pathway were changed, including specific time frames and frequency, to match the information provided in the patient education booklet. These orders were for ambulation within 4 hours of arrival to the floor, and the orders also noted that no patient should be on bedrest unless explicitly stated. From POD 1, all patients were to ambulate at least twice daily for the remainder of the hospital stay (patients were encouraged to walk 4 times daily, but we set a minimum expectation of twice daily for the order set). These orders were clarified with in-person meetings with the nursing staff and leadership from the PACU and the colorectal surgical ward.
Adjusted Nursing Workflow. Nurses were interviewed and asked to create a plan regarding how they could better incorporate ambulation into their daily workflow. Ambulation assessment was incorporated into the twice-per-shift recording of vital signs and patient safety assessment. This was recorded into the electronic health record at the same time as the patients’ vital signs. This allowed nurses to keep track of which patients would need extra assistance in ambulation and which patients were doing well on their own with the assistance of family. It also helped focus the resources of physical therapy and the single ambulation technician on the floor and to assist patients who needed more assistance.
Creation of Ambulation Encouragement Signs. The authors discovered that despite patients being told preoperatively about ambulation expectations, friends and family are not always included in these conversations. As nurses frequently cited both patients and family as reasons patients thought they should not walk, multiple signs inviting patients to take an active role in their recovery by ambulating were created and placed around the unit. The signs outlined the expectations of being out of bed and taking at least 1 step on the day of surgery and walking at least 4 times per day thereafter. In addition, we addressed frequently asked questions around issues such as walking with intravenous poles and urinary catheters. The posters were signed by all staff colorectal surgeons.
Results
Over the course of 7 months (June 2018 to December 2018), 253 postintervention patients were identified (Table 2). There was no difference between the pre-intervention group (n = 1762) and the postintervention group in terms of sex, race, origin, emergency status, operative time, and the majority of medical comorbidities (with the exception of smoking status and congestive heart failure). The postintervention group was slightly older (60 versus 57 years) and had a higher percentage of patients with an American Society of Anesthesiologists physical status score greater than 2 (66.8% versus 51.2%). The postintervention group also had higher rates of both malignancy (53.4% versus 33.3%) and inflammatory bowel disease (18.2% versus 14.4%).
The fidelity of the PDSA cycle was measured by pre-intervention and postintervention ambulation rates. Ambulation rates on POD 0, 1, and 2 improved from 36.4%, 47.3%, and 50.2% to 36.8%, 74.7%, and 82.6%, respectively (Table 3). The VTE rate decreased from 2.7% to 0.4% (P = 0.02), with 1 DVT and 0 PEs. It should be noted that the only patient who developed a VTE postintervention did not ambulate on PODs 0, 1, or 2.
Discussion
Postoperative VTE is a severe complication for postoperative colorectal surgery patients. Previous studies have demonstrated that increasing ambulation is associated with a lower rate of overall complications, and, when incorporated into a bundle, is associated with decreased rates of VTE.11,15 However, this is the first study to our knowledge demonstrating that creation of an ambulation protocol alone is associated with a decrease in VTE.
Analysis of pre-intervention data demonstrated a strong association between ambulation and an absence of VTE. No patient who ambulated on PODs 0, 1, and 2 developed a VTE. Based on those results, we moved forward with creating the ambulation protocol. While ambulation stayed stable on POD 0, there were 60% and 65% increases on PODs 1 and 2, respectively. Nurses cited late arrival to the floor for second and third start cases as the primary difficulty in getting patients to ambulate more on POD 0.
We believe the key to the success of the ambulation protocol was its multidisciplinary nature. Certainly, the easiest way to create an ambulation protocol is to change the postoperative orders to state patients must walk 4 times per day. However, if the nursing staff is unable or unwilling to carry out these orders, the orders serve little purpose. In order to make lasting changes, all stakeholders in the process must be identified. In our case, stakeholders included surgery and nursing leadership, surgeons, nurse practitioners, nurses, medical assistants, physical therapists, patient care technicians, and patients. This is where we utilized kaizen, a core principle of Lean methodology that empowers employees at the level of the work being carried out to propose ideas for improvement.16 From the beginning of the patient experience, the health care practitioners who were carrying out each step of the process were best able to identify the problems and create solutions. In addition, stakeholders were given regular updates regarding how their efforts were increasing ambulation rates and the results at the end of the study period.
This study also demonstrates that, in a health care system increasingly focused on both quality and cost, significant improvements in quality can be made without increasing cost or resource utilization. Early in the process, it was proposed that the only way to increase the ambulation rate would be to increase the number of physical therapists, nurses, and nursing assistants. However, after identifying the root causes of the problem, the solutions had more to do with improving workflow and fixing problem areas identified by the staff.
In addition to having a positive effect on the outcome studied, collaborative projects such as this between physicians and nurses may lead to increased nursing job satisfaction. A meta-analysis of 31 studies identified nurse-physician collaboration and autonomy as 2 factors that correlate most strongly with nursing satisfaction.17 A Cochrane review also suggests that practice-based interprofessional collaboration may lead to improved health care processes and outcomes.18
This study has several limitations. Pre-intervention ambulation rates were abstracted from institution-specific NSQIP data, and missing data were excluded from analysis. Also, due to the retrospective collection of the pre-intervention data, the distance of ambulation could not be quantified. The bar for ambulation is low, as patients were only required to get out of bed and walk 1 step. However, we feel that getting out of bed and taking even 1 step is substantially better than complete bedrest. It is likely that once patients cross the threshold of taking 1 step, they are more likely to ambulate. An area of future study may be to more precisely define the relationship between the quantity of ambulation in steps and its effect on VTE. Finally, we acknowledge that while there is no direct increase in costs, implementing an ambulation protocol does take time from all who participate in the project.
Conclusion
Creation of an ambulation protocol is associated with a decrease in postoperative VTE rates in colorectal surgery patients. A multidisciplinary approach is critical to identify the underlying problems and propose effective solutions. Further studies are required to better correlate the distance of ambulation and its effect on VTE. However, this study shows that even a minimum of 1 step is associated with decreased VTE rates.
Corresponding author: Aneel Damle, MD, MBA, Colon & Rectal Surgery Associates, 3433 Broadway St. NE, Suite 115, Minneapolis, MN 55413; adamle@CRSAL.org.
Financial disclosures: None.
From the Department of Surgery, Washington University School of Medicine, St. Louis, MO.
Abstract
Background: Patients undergoing colorectal surgery are at high risk for postoperative venous thromboembolism (VTE). Early ambulation has been encouraged to lower rates of VTE, but evidence demonstrating its effectiveness outside of a bundle is limited.
Objective: To create a multidisciplinary ambulation protocol in an effort to reduce postoperative VTE.
Methods: A single-center, retrospective, comparative study of patients who underwent colectomy or proctectomy was conducted. Outcomes of patients operated on prior to protocol implementation were compared with a cohort after implementation. The intervention studied was the implementation of a multidisciplinary ambulation protocol. The primary endpoint was postoperative VTE.
Results: There was no difference between the pre-intervention group (n = 1762) and the postintervention group (n = 253) in terms of sex, race, origin, emergency status, operative time, and the majority of medical comorbidities (with the exception of smoking status and congestive heart failure). After the protocol was implemented, ambulation rates on postoperative days 0, 1, and 2 improved from 36.4%, 47.3%, and 50.2% to 36.8%, 74.7%, and 82.6%, respectively The VTE rate in the pre-intervention group was 2.7% versus a rate of 0.4% in the postintervention group (P = 0.02).
Conclusion: Creation of an ambulation protocol is associated with a significant reduction in VTE. Commitment from patients, families, nurses, physician extenders, and physicians is critical to the success of the program.
Keywords: VTE; pulmonary embolism; deep vein thrombosis; postoperative; quality improvement.
Postoperative venous thromboembolism (VTE) is a significant source of morbidity, mortality, and cost.1,2 Colorectal surgery patients are at particularly high risk for VTE due to positioning during surgery, pelvic dissection, and other conditions often found in these patients, such as cancer and inflammatory bowel disease.3 A National Surgical Quality Improvement Program (NSQIP) analysis demonstrated an overall rate of VTE in colorectal surgery patients of 2.4%, although other studies have demonstrated rates up to 9%, even in those receiving appropriate chemoprophylaxis.4-6 Many of these VTEs occur in the postdischarge setting. In a NSQIP study of colorectal surgery patients, the rate of VTE between discharge and 30 days was 0.47%.7 The cost burdenfor a postoperative VTE has been estimated to be more than $18,000.8
Studies from NSQIP have identified multiple factors associated with VTE in colorectal surgery patients, but NSQIP does not record ambulation as a standard variable.9 Multiple strategies have been implemented to reduce postoperative VTE. Often, these studies focus on increasing compliance with appropriate chemoprophylaxis, risk stratification, or bundling multiple strategies.10,11 However, despite the fact that postsurgical ambulation is widely encouraged and recommended by the American Society of Colon and Rectal Surgeons clinical practice guidelines, there is little evidence demonstrating the role of ambulation alone in the reduction of VTE.4,12 The purpose of this study was to create a multidisciplinary protocol to increase postoperative ambulation and evaluate its effect on VTE.
Methods
Setting
This study was conducted at a single academic tertiary care center.
Patients and Outcome Measures
All patients undergoing colectomy or proctectomy by surgeons in the section of colon and rectal surgery at a single institution between January 2011 and March 2017 were included. Colectomy and proctectomy were defined by CPT codes 44140, 44141, 44143, 44144, 44145, 44146, 44147, 44150, 44151, 44155, 44156, 44157, 44158, 44160, 44204, 44205, 44206, 44207, 44208, 44210, 44211, 44212, 44213, 45110, 45111, 45112, 45113, 45114, 45116, 45119, 45120, 45121, 45123, 45126, 45160, 45395, and 45397. The primary outcome of VTE within 30 days, including deep venous thrombosis (DVT) and pulmonary embolism (PE), was measured using institution-specific data from NSQIP in both the pre-intervention and postintervention setting. The occurrence of both DVT and PE in 1 patient was counted as a single event of VTE. Ambulation rate on postoperative day (POD) 0, 1, and 2 was calculated by NSQIP in the pre-intervention setting (our institution-specific NSQIP recorded ambulation data for an unrelated project) and by review of the electronic health record in the postintervention setting, as this institution-specific variable was no longer being collected. Ambulation was defined as getting out of bed and taking at least 1 step. The threshold for ambulating each day was once on POD 0 and twice on PODs 1 and 2. Patients with missing ambulation data were excluded from the analysis. Both prior to and throughout the intervention, all patients were given VTE chemoprophylaxis with either low-dose unfractionated heparin or low-molecular-weight heparin prior to induction of anesthesia, with chemoprophylaxis extending an additional 21 days after discharge (unless specifically contraindicated); sequential compression devices; and standard orders to ambulate 3 times daily from POD 0 as part of the standard Enhanced Recovery After Surgery protocol.
Analysis
Statistical analysis was performed using univariate analysis. Chi-square test and univariate logistic regression were used to determine the association between ambulation rates and VTE in the pre-intervention group. Chi-square test was also used to compare ambulation and VTE rates between the pre-intervention and postintervention groups. Plan-Do-Study-Act (PDSA) cycle fidelity (the degree to which a PDSA cycle is carried out in accordance with the guiding principles of its use) was measured by recording the ambulation rates both before and after the intervention.13 Statistical analysis was performed using SAS Version 9.4 (SAS Institute, Cary, NC). This study was reviewed by the Washington University School of Medicine Institutional Review Board and deemed to be quality improvement, not human subjects research, and therefore did not require formal approval.
Baseline Outcome Rates
A total of 1762 patients were identified during the pre-intervention period. The overall VTE rate in the pre-intervention group was 2.7% (n = 48), with 39 DVTs (2.2%) and 13 PEs (0.7%). Pre-intervention ambulation data were available on 590 patients. Baseline ambulation rates on PODs 0, 1, and 2 were 36.4% (213/590), 47.3% (279/590), and 50.2% (296/590), respectively. Patients who did not ambulate on POD 0 had a VTE rate of 4.3%, as compared to 0.9% in those who did ambulate (Table 1). Patients who did not ambulate twice on POD 1 had a VTE rate of 4.8%, compared to 1.1% in those who did ambulate (odds ratio [OR], 4.66; 95% confidence interval [CI], 1.34 to 16.28). Patients who did not ambulate twice on POD 2 had a VTE rate of 5.4%, compared to 0.7% in those who did. Finally, those who ambulated twice on both PODs 1 and 2 had a 0% rate of VTE, compared to 4.9% in those who did not ambulate on both PODs.
Ambulation Protocol
After baseline outcome rates had been established, a multidisciplinary team of medical assistants, nurses, nurse practitioners, and physicians worked together to identify all processes that involved postoperative ambulation. Given the significant differences in VTE rates between patients who ambulated and those that did not, we created a multidisciplinary ambulation protocol using the PDSA method.14 Multiple points of patient contact were chosen for intervention, and the ambulation protocol was implemented in June 2018 and continued for 7 months.
Patients were observed from their initial office visit with a surgeon, during the preoperative education encounter, and in the operating room and on the surgical ward until discharge. Representatives from multiple disciplines who encountered patients at various times in the process, including medical assistants, patient care technicians, nurses, nurse practitioners, physical therapists, and physicians, participated in a kick-off meeting to identify difficulties they encounter when encouraging patient ambulation. The following 4 areas were identified.
Barriers to Patient Ambulation
Patient Expectations. Patients did not appear to have a clear expectation of what their ambulation goals were postoperatively, despite the fact that each patient is given an operative pathway booklet that includes their goals for each day, including ambulation. The consensus was that patients were overwhelmed with the amount of information and, oftentimes, the severity of their diagnosis, so the information regarding ambulation was not retained. Nurses commented that patients frequently stated that they did not think their surgeon wanted them to get out of bed postoperatively.
Electronic Orders. There was confusion within the nursing staff regarding orders in the electronic health record compared to physician expectations. Orders stated patients should ambulate 3 times daily, but did not specify on which postoperative day this should start. Often, nursing verbal sign-out from the post-anesthesia care unit (PACU) would be an order for bedrest, despite no clear origin of this order. This created confusion among the nursing staff as to what the appropriate ambulation orders should be.
Nursing Workflow. The initial state of the nursing workflow was not conducive to evaluating for, or assisting with, ambulation. With no set time to assist and evaluate patients for ambulation, it turned into a task nurses needed to accomplish when they had extra time. With increasing demands of charting in the electronic health record, nurses often had to skip ambulation in order to accomplish other tasks.
Family Expectations. In addition to patient expectations, family members often had expectations that were not congruent with the planned postoperative course. Nurses stated family members would often tell them that they did not feel that their family member should be ambulating so soon after surgery. Often these family members had not attended preoperative education sessions with the patient. This was compounded by the uncertainty among the nursing staff regarding what exactly the ambulation orders were.
Interventions
Targeted interventions were created to address these 4 barriers to ambulation identified by staff.
Preoperative Education. Although all elective patients received a printed operative pathway booklet describing daily goals, including ambulation, patients still did not have a sufficient understanding of what was expected of them. The education session was modified to increase the time spent on both the expectation for and the rationale behind ambulation. That section of the education session ended with a verbal commitment and read-back of the expectations for ambulation by the patient.
Clarification of Electronic Orders. Postoperative orders within the colorectal standard pathway were changed, including specific time frames and frequency, to match the information provided in the patient education booklet. These orders were for ambulation within 4 hours of arrival to the floor, and the orders also noted that no patient should be on bedrest unless explicitly stated. From POD 1, all patients were to ambulate at least twice daily for the remainder of the hospital stay (patients were encouraged to walk 4 times daily, but we set a minimum expectation of twice daily for the order set). These orders were clarified with in-person meetings with the nursing staff and leadership from the PACU and the colorectal surgical ward.
Adjusted Nursing Workflow. Nurses were interviewed and asked to create a plan regarding how they could better incorporate ambulation into their daily workflow. Ambulation assessment was incorporated into the twice-per-shift recording of vital signs and patient safety assessment. This was recorded into the electronic health record at the same time as the patients’ vital signs. This allowed nurses to keep track of which patients would need extra assistance in ambulation and which patients were doing well on their own with the assistance of family. It also helped focus the resources of physical therapy and the single ambulation technician on the floor and to assist patients who needed more assistance.
Creation of Ambulation Encouragement Signs. The authors discovered that despite patients being told preoperatively about ambulation expectations, friends and family are not always included in these conversations. As nurses frequently cited both patients and family as reasons patients thought they should not walk, multiple signs inviting patients to take an active role in their recovery by ambulating were created and placed around the unit. The signs outlined the expectations of being out of bed and taking at least 1 step on the day of surgery and walking at least 4 times per day thereafter. In addition, we addressed frequently asked questions around issues such as walking with intravenous poles and urinary catheters. The posters were signed by all staff colorectal surgeons.
Results
Over the course of 7 months (June 2018 to December 2018), 253 postintervention patients were identified (Table 2). There was no difference between the pre-intervention group (n = 1762) and the postintervention group in terms of sex, race, origin, emergency status, operative time, and the majority of medical comorbidities (with the exception of smoking status and congestive heart failure). The postintervention group was slightly older (60 versus 57 years) and had a higher percentage of patients with an American Society of Anesthesiologists physical status score greater than 2 (66.8% versus 51.2%). The postintervention group also had higher rates of both malignancy (53.4% versus 33.3%) and inflammatory bowel disease (18.2% versus 14.4%).
The fidelity of the PDSA cycle was measured by pre-intervention and postintervention ambulation rates. Ambulation rates on POD 0, 1, and 2 improved from 36.4%, 47.3%, and 50.2% to 36.8%, 74.7%, and 82.6%, respectively (Table 3). The VTE rate decreased from 2.7% to 0.4% (P = 0.02), with 1 DVT and 0 PEs. It should be noted that the only patient who developed a VTE postintervention did not ambulate on PODs 0, 1, or 2.
Discussion
Postoperative VTE is a severe complication for postoperative colorectal surgery patients. Previous studies have demonstrated that increasing ambulation is associated with a lower rate of overall complications, and, when incorporated into a bundle, is associated with decreased rates of VTE.11,15 However, this is the first study to our knowledge demonstrating that creation of an ambulation protocol alone is associated with a decrease in VTE.
Analysis of pre-intervention data demonstrated a strong association between ambulation and an absence of VTE. No patient who ambulated on PODs 0, 1, and 2 developed a VTE. Based on those results, we moved forward with creating the ambulation protocol. While ambulation stayed stable on POD 0, there were 60% and 65% increases on PODs 1 and 2, respectively. Nurses cited late arrival to the floor for second and third start cases as the primary difficulty in getting patients to ambulate more on POD 0.
We believe the key to the success of the ambulation protocol was its multidisciplinary nature. Certainly, the easiest way to create an ambulation protocol is to change the postoperative orders to state patients must walk 4 times per day. However, if the nursing staff is unable or unwilling to carry out these orders, the orders serve little purpose. In order to make lasting changes, all stakeholders in the process must be identified. In our case, stakeholders included surgery and nursing leadership, surgeons, nurse practitioners, nurses, medical assistants, physical therapists, patient care technicians, and patients. This is where we utilized kaizen, a core principle of Lean methodology that empowers employees at the level of the work being carried out to propose ideas for improvement.16 From the beginning of the patient experience, the health care practitioners who were carrying out each step of the process were best able to identify the problems and create solutions. In addition, stakeholders were given regular updates regarding how their efforts were increasing ambulation rates and the results at the end of the study period.
This study also demonstrates that, in a health care system increasingly focused on both quality and cost, significant improvements in quality can be made without increasing cost or resource utilization. Early in the process, it was proposed that the only way to increase the ambulation rate would be to increase the number of physical therapists, nurses, and nursing assistants. However, after identifying the root causes of the problem, the solutions had more to do with improving workflow and fixing problem areas identified by the staff.
In addition to having a positive effect on the outcome studied, collaborative projects such as this between physicians and nurses may lead to increased nursing job satisfaction. A meta-analysis of 31 studies identified nurse-physician collaboration and autonomy as 2 factors that correlate most strongly with nursing satisfaction.17 A Cochrane review also suggests that practice-based interprofessional collaboration may lead to improved health care processes and outcomes.18
This study has several limitations. Pre-intervention ambulation rates were abstracted from institution-specific NSQIP data, and missing data were excluded from analysis. Also, due to the retrospective collection of the pre-intervention data, the distance of ambulation could not be quantified. The bar for ambulation is low, as patients were only required to get out of bed and walk 1 step. However, we feel that getting out of bed and taking even 1 step is substantially better than complete bedrest. It is likely that once patients cross the threshold of taking 1 step, they are more likely to ambulate. An area of future study may be to more precisely define the relationship between the quantity of ambulation in steps and its effect on VTE. Finally, we acknowledge that while there is no direct increase in costs, implementing an ambulation protocol does take time from all who participate in the project.
Conclusion
Creation of an ambulation protocol is associated with a decrease in postoperative VTE rates in colorectal surgery patients. A multidisciplinary approach is critical to identify the underlying problems and propose effective solutions. Further studies are required to better correlate the distance of ambulation and its effect on VTE. However, this study shows that even a minimum of 1 step is associated with decreased VTE rates.
Corresponding author: Aneel Damle, MD, MBA, Colon & Rectal Surgery Associates, 3433 Broadway St. NE, Suite 115, Minneapolis, MN 55413; adamle@CRSAL.org.
Financial disclosures: None.
1. Gangireddy C, Rectenwald JR, Upchurch GR, et al. Risk factors and clinical impact of postoperative symptomatic venous thromboembolism. J Vasc Surg. 2007;45:341-342.
2. Newhook TE, LaPar DJ, Walters DM, et al. Impact of postoperative venous thromboembolism on postoperative morbidity, mortality, and resource utilization after hepatectomy. Am Surg. 2015;81:1216-1223.
3. Bergqvist D. Venous thromboembolism: a review of risk and prevention in colorectal surgery patients. Dis Colon Rectum. 2006;49:1620-1628.
4. Fleming F, Gaertner W, Ternent CA, et al. The American society of colon and rectal surgeons clinical practice guideline for the prevention of venous thromboembolic disease in colorectal surgery. Dis Colon Rectum. 2018;61:14-20.
5. McLeod RS, Geerts WH, Sniderman KW, et al. Canadian Colorectal Surgery DVT Prophylaxis Trial investigators. Subcutaneous heparin versus low-molecular-weight heparin as thromboprophylaxis in patients undergoing colorectal surgery: results of the Canadian colorectal DV prophylaxis trial: a randomized, double-blind trial. Ann Surg. 2001;233:438-444.
6. Shapiro R, Vogel JD, Kiran RP. Risk of postoperative venous thromboembolism after laparoscopic and open colorectal surgery: an additional benefit of the minimally invasive approach? Dis Colon Rectum. 2011;54:1496-1502.
7. Dimick JB, Chen SL, Taheri PA, et al. Hospital costs associated with surgical complications: a report from the private-sector National Surgical Quality Improvement Program. J Am Coll Surg. 2004;199:531-537.
8. Fleming FJ, Kim MJ, Salloum RM, et al. How much do we need to worry about venous thromboembolism after hospital discharge? A study of colorectal surgery patients using the National Surgical Quality Improvement Program database. Dis Colon Rectum. 2010;53:1355-1360.
9. ACS NSQIP. User guide for the 2016 ACS NSQIP participant use data file (PUF). 2017. www.facs.org/~/media/files/quality%20programs/nsqip/nsqip_puf_userguide_2016.ashx Accessed July 10, 2020.
10. Caprini JA. Risk assessment as a guide for the prevention of the many faces of venous thromboembolism. Am J Surg. 2010;199(1 Suppl):S3-S10.
11. Cassidy MR, Rosenkranz P, McAney D. Reducing postoperative venous thromboembolism complications with a standardized risk-stratified prophylaxis protocol and mobilization protocol. J Am Coll Surg. 2014;218:1095-1104.
12. Lau BD, Streiff MB, Kraus PS, et al. No evidence to support ambulation for reducing postoperative venous thromboembolism. J Am Coll Surg. 2014;219:1101-1103.
13. McNicholas C, Lennox L, Woodcock T, et al. Evolving quality improvement support strategies to improve Plan–Do–Study–Act cycle fidelity: a retrospective mixed-methods study. BMJ Qual Saf. 2019;28:356-365.
14. Taylor MJ, McNicholas C, Nicolay C, et al. Systematic review of the application of the plan–do–study–act method to improve quality in healthcare. BMC Qual Saf. 2014;23:290-298.
15. Nevo Y, Shaltiel T, Constantini N, et al. Effect of ambulation and physical activity on postoperative complications. J Am Coll Surg. 2016;223(Suppl 1):S61.
16. Mazzocato P, Stenfors-Hayes T, von Thiele Schwarz U, et al. Kaizen practice in healthcare: a qualitative analysis of hospital employees’ suggestions for improvement. BMJ Open. 2016;6:e012256.
17. Zangaro GA, Soeken KL. A meta-analysis of studies of nurses’ job satisfaction. Res Nursing Health. 2007;30:445-458.
18. Reeves S, Pelone F, Harrison R, et al. Interprofessional collaboration to improve professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2017;6(6):CD000072.
1. Gangireddy C, Rectenwald JR, Upchurch GR, et al. Risk factors and clinical impact of postoperative symptomatic venous thromboembolism. J Vasc Surg. 2007;45:341-342.
2. Newhook TE, LaPar DJ, Walters DM, et al. Impact of postoperative venous thromboembolism on postoperative morbidity, mortality, and resource utilization after hepatectomy. Am Surg. 2015;81:1216-1223.
3. Bergqvist D. Venous thromboembolism: a review of risk and prevention in colorectal surgery patients. Dis Colon Rectum. 2006;49:1620-1628.
4. Fleming F, Gaertner W, Ternent CA, et al. The American society of colon and rectal surgeons clinical practice guideline for the prevention of venous thromboembolic disease in colorectal surgery. Dis Colon Rectum. 2018;61:14-20.
5. McLeod RS, Geerts WH, Sniderman KW, et al. Canadian Colorectal Surgery DVT Prophylaxis Trial investigators. Subcutaneous heparin versus low-molecular-weight heparin as thromboprophylaxis in patients undergoing colorectal surgery: results of the Canadian colorectal DV prophylaxis trial: a randomized, double-blind trial. Ann Surg. 2001;233:438-444.
6. Shapiro R, Vogel JD, Kiran RP. Risk of postoperative venous thromboembolism after laparoscopic and open colorectal surgery: an additional benefit of the minimally invasive approach? Dis Colon Rectum. 2011;54:1496-1502.
7. Dimick JB, Chen SL, Taheri PA, et al. Hospital costs associated with surgical complications: a report from the private-sector National Surgical Quality Improvement Program. J Am Coll Surg. 2004;199:531-537.
8. Fleming FJ, Kim MJ, Salloum RM, et al. How much do we need to worry about venous thromboembolism after hospital discharge? A study of colorectal surgery patients using the National Surgical Quality Improvement Program database. Dis Colon Rectum. 2010;53:1355-1360.
9. ACS NSQIP. User guide for the 2016 ACS NSQIP participant use data file (PUF). 2017. www.facs.org/~/media/files/quality%20programs/nsqip/nsqip_puf_userguide_2016.ashx Accessed July 10, 2020.
10. Caprini JA. Risk assessment as a guide for the prevention of the many faces of venous thromboembolism. Am J Surg. 2010;199(1 Suppl):S3-S10.
11. Cassidy MR, Rosenkranz P, McAney D. Reducing postoperative venous thromboembolism complications with a standardized risk-stratified prophylaxis protocol and mobilization protocol. J Am Coll Surg. 2014;218:1095-1104.
12. Lau BD, Streiff MB, Kraus PS, et al. No evidence to support ambulation for reducing postoperative venous thromboembolism. J Am Coll Surg. 2014;219:1101-1103.
13. McNicholas C, Lennox L, Woodcock T, et al. Evolving quality improvement support strategies to improve Plan–Do–Study–Act cycle fidelity: a retrospective mixed-methods study. BMJ Qual Saf. 2019;28:356-365.
14. Taylor MJ, McNicholas C, Nicolay C, et al. Systematic review of the application of the plan–do–study–act method to improve quality in healthcare. BMC Qual Saf. 2014;23:290-298.
15. Nevo Y, Shaltiel T, Constantini N, et al. Effect of ambulation and physical activity on postoperative complications. J Am Coll Surg. 2016;223(Suppl 1):S61.
16. Mazzocato P, Stenfors-Hayes T, von Thiele Schwarz U, et al. Kaizen practice in healthcare: a qualitative analysis of hospital employees’ suggestions for improvement. BMJ Open. 2016;6:e012256.
17. Zangaro GA, Soeken KL. A meta-analysis of studies of nurses’ job satisfaction. Res Nursing Health. 2007;30:445-458.
18. Reeves S, Pelone F, Harrison R, et al. Interprofessional collaboration to improve professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2017;6(6):CD000072.
eConsult Data Shed Light on Care Coordination Decisions During the COVID-19 Pandemic
From the Multi-County eConsult Initiative, Rancho Cucamonga, CA.
The COVID-19 pandemic has forced many health care professionals and their patients to use telehealth and virtual care to address care needs in new ways.1 To shed light on care coordination decisions with respect to specialty resource access, we analyzed data collected from the Multi-County eConsult Initiative (MCeI)—the second-largest electronic consultation (eConsult) program in the United States—before and during the COVID-19 pandemic. Our analysis of these data suggests opportunities for improving access to care and reducing unnecessary costs in the health system nationally.
The Inland Empire Health Plan (IEHP) launched MCeI (econsultie.com) in 2018. The initiative is a partnership between IEHP, Arrowhead Regional Medical Center, and Riverside University Health System aimed at improving access to specialty care for the safety-net population across San Bernardino and Riverside counties. IEHP is 1 of the 10 largest Medicaid health plans and the largest not-for-profit Medicare-Medicaid plan in the country, serving more than 1.2 million members.2 Data from MCel reveal the impacts of COVID-19 on eConsult use and offer insights into specialty resource availability during and outside of a crisis.
At the time of this analysis, 86 IEHP clinics in rural and urban settings across 38 specialties used the eConsult process to provide and obtain virtual specialty care, as well as timely appointments for in-person specialty care.3 eConsults are facilitated through a HIPAA-secure web-based portal that enables communication and sharing of information between the primary care provider (PCP) and a specialist. eConsult gives PCPs virtual access to specialists to coordinate care for their patients and determine the need for in-person specialty visits. Through the PCP-specialist eConsult dialogue, patients gain virtual access to specialty care. If a PCP-specialist care team determines the patient needs an in-person visit, that specialty referral is automatically authorized by IEHP, without the need for further review. At IEHP, eConsult is the primary method used for obtaining outpatient specialty referrals.
To analyze eConsult utilization before and during the pandemic, we gathered data from the MCeI program for the periods February 20–March 19, 2020, and March 20–April 19, 2020. Measures included eConsult volume and outcomes of eConsults (eConsults closed as referrals for face-to-face specialist visits versus eConsults closed without resulting in referrals for face-to-face specialist visits). Statistical analysis using chi-square tests for independence was performed using IBM SPSS Statistics 25 (IBM, Armonk, NY).
The data show that after California’s stay-at-home order, issued on March 19, 2020,4 eConsult volumes initially decreased, reflecting a similar decrease in clinic visits and authorization requests submitted to IEHP. We observed a 4-week average of 1100 eConsults processed before the pandemic, and then a steep drop to a 4-week average of 500 eConsults processed after the stay-at-home order was issued. Despite the overall drop in the volume of eConsults submitted, demand for specialties like hematology and neurology remained high throughout the pandemic.
During the pandemic, certain specialties displayed rising rates of eConsults completed with specialists providing care recommendations to the PCP instead of resulting in a recommendation for a face-to-face (in-person or via telehealth) visit with a specialist (see Figure and Table). The trend of increasing eConsults that concluded without a face-to-face visit suggests newfound clinical consideration of limited medical resources, along with the desire to eliminate unnecessary risks of infection.
eConsults between PCPs and specialist reviewers via the IEHP portal resulted in higher rates of non-face-to-face recommendations. The specialist reviewers were able to provide treatment plans for PCPs to take care of patients without having to refer their patients to a specialist. This increase was significant across most of the specialties live on the MCeI program.
We believe that clinicians’ heightened awareness of the limitations of the US health care system should remain a key consideration and factor in medical decision-making about appropriate referrals after the pandemic has passed. The data demonstrate that the pandemic drove clinicians to make different decisions about referrals and care coordination. Physicians scrutinized individual cases more keenly and were not as quick to recommend a face-to-face visit. This awareness and consideration of specialty access before making a referral provides a valuable lesson. If this approach is applied to health care delivery post-pandemic, eConsults will help reduce unnecessary in-person specialist visits and will free up space and time for patients who genuinely do need in-person specialty care. In this way, eConsult will improve appropriate access to care for everyone and reduce unnecessary costs to the health care system at large.
An examination of eConsult utilization trends across Riverside and San Bernardino counties before and during the COVID-19 pandemic provides useful insights into how to reduce costs and improve access to care. Although the risk of exposure to COVID-19 currently presents a significant obstacle to obtaining in-person specialty care, pre-existing and long-standing barriers, such as long wait times and scarcity of specialists, remain critical issues to receiving care during and after the pandemic. The pandemic has proven eConsult’s value as a tool for effective care coordination. Leveraging provider-to-provider asynchronous communication offers an opportunity to reduce unnecessary utilization of scarce resources during and beyond the pandemic.
Corresponding author: Lisa Aubry, Aubry-L@iehp.org.
Financial disclosures: None.
Keywords: electronic consultation; care coordination; telehealth; telemedicine; virtual care.
1. Wosik J, Fudim M, Cameron B, et al. Telehealth transformation: COVID-19 and the rise of virtual care. J Am Med Inform Assoc. 2020;27:957-962.
2. Nash-Wong K. Inland Empire Health Plan Multi-county eConsult Initiative with Safety Net Connect improves specialty care for Southern California residents. [Press Release]. (July 24, 2019). www.businesswire.com/news/home/20190724005208/en/Inland-Empire-Health-Plan-Multi-county-eConsult-Initiative. Accessed July 16, 2020.
3. The Multi-County eConsult Initiative (March 2018). https://www.eConsultie.com. Accessed July 16, 2020.
4. Executive Department State of California. Exec. Order No. N-33-20 of March 19, 2020. Safer at Home, Stay at Home. www.gov.ca.gov. Accessed July 16, 2020.
From the Multi-County eConsult Initiative, Rancho Cucamonga, CA.
The COVID-19 pandemic has forced many health care professionals and their patients to use telehealth and virtual care to address care needs in new ways.1 To shed light on care coordination decisions with respect to specialty resource access, we analyzed data collected from the Multi-County eConsult Initiative (MCeI)—the second-largest electronic consultation (eConsult) program in the United States—before and during the COVID-19 pandemic. Our analysis of these data suggests opportunities for improving access to care and reducing unnecessary costs in the health system nationally.
The Inland Empire Health Plan (IEHP) launched MCeI (econsultie.com) in 2018. The initiative is a partnership between IEHP, Arrowhead Regional Medical Center, and Riverside University Health System aimed at improving access to specialty care for the safety-net population across San Bernardino and Riverside counties. IEHP is 1 of the 10 largest Medicaid health plans and the largest not-for-profit Medicare-Medicaid plan in the country, serving more than 1.2 million members.2 Data from MCel reveal the impacts of COVID-19 on eConsult use and offer insights into specialty resource availability during and outside of a crisis.
At the time of this analysis, 86 IEHP clinics in rural and urban settings across 38 specialties used the eConsult process to provide and obtain virtual specialty care, as well as timely appointments for in-person specialty care.3 eConsults are facilitated through a HIPAA-secure web-based portal that enables communication and sharing of information between the primary care provider (PCP) and a specialist. eConsult gives PCPs virtual access to specialists to coordinate care for their patients and determine the need for in-person specialty visits. Through the PCP-specialist eConsult dialogue, patients gain virtual access to specialty care. If a PCP-specialist care team determines the patient needs an in-person visit, that specialty referral is automatically authorized by IEHP, without the need for further review. At IEHP, eConsult is the primary method used for obtaining outpatient specialty referrals.
To analyze eConsult utilization before and during the pandemic, we gathered data from the MCeI program for the periods February 20–March 19, 2020, and March 20–April 19, 2020. Measures included eConsult volume and outcomes of eConsults (eConsults closed as referrals for face-to-face specialist visits versus eConsults closed without resulting in referrals for face-to-face specialist visits). Statistical analysis using chi-square tests for independence was performed using IBM SPSS Statistics 25 (IBM, Armonk, NY).
The data show that after California’s stay-at-home order, issued on March 19, 2020,4 eConsult volumes initially decreased, reflecting a similar decrease in clinic visits and authorization requests submitted to IEHP. We observed a 4-week average of 1100 eConsults processed before the pandemic, and then a steep drop to a 4-week average of 500 eConsults processed after the stay-at-home order was issued. Despite the overall drop in the volume of eConsults submitted, demand for specialties like hematology and neurology remained high throughout the pandemic.
During the pandemic, certain specialties displayed rising rates of eConsults completed with specialists providing care recommendations to the PCP instead of resulting in a recommendation for a face-to-face (in-person or via telehealth) visit with a specialist (see Figure and Table). The trend of increasing eConsults that concluded without a face-to-face visit suggests newfound clinical consideration of limited medical resources, along with the desire to eliminate unnecessary risks of infection.
eConsults between PCPs and specialist reviewers via the IEHP portal resulted in higher rates of non-face-to-face recommendations. The specialist reviewers were able to provide treatment plans for PCPs to take care of patients without having to refer their patients to a specialist. This increase was significant across most of the specialties live on the MCeI program.
We believe that clinicians’ heightened awareness of the limitations of the US health care system should remain a key consideration and factor in medical decision-making about appropriate referrals after the pandemic has passed. The data demonstrate that the pandemic drove clinicians to make different decisions about referrals and care coordination. Physicians scrutinized individual cases more keenly and were not as quick to recommend a face-to-face visit. This awareness and consideration of specialty access before making a referral provides a valuable lesson. If this approach is applied to health care delivery post-pandemic, eConsults will help reduce unnecessary in-person specialist visits and will free up space and time for patients who genuinely do need in-person specialty care. In this way, eConsult will improve appropriate access to care for everyone and reduce unnecessary costs to the health care system at large.
An examination of eConsult utilization trends across Riverside and San Bernardino counties before and during the COVID-19 pandemic provides useful insights into how to reduce costs and improve access to care. Although the risk of exposure to COVID-19 currently presents a significant obstacle to obtaining in-person specialty care, pre-existing and long-standing barriers, such as long wait times and scarcity of specialists, remain critical issues to receiving care during and after the pandemic. The pandemic has proven eConsult’s value as a tool for effective care coordination. Leveraging provider-to-provider asynchronous communication offers an opportunity to reduce unnecessary utilization of scarce resources during and beyond the pandemic.
Corresponding author: Lisa Aubry, Aubry-L@iehp.org.
Financial disclosures: None.
Keywords: electronic consultation; care coordination; telehealth; telemedicine; virtual care.
From the Multi-County eConsult Initiative, Rancho Cucamonga, CA.
The COVID-19 pandemic has forced many health care professionals and their patients to use telehealth and virtual care to address care needs in new ways.1 To shed light on care coordination decisions with respect to specialty resource access, we analyzed data collected from the Multi-County eConsult Initiative (MCeI)—the second-largest electronic consultation (eConsult) program in the United States—before and during the COVID-19 pandemic. Our analysis of these data suggests opportunities for improving access to care and reducing unnecessary costs in the health system nationally.
The Inland Empire Health Plan (IEHP) launched MCeI (econsultie.com) in 2018. The initiative is a partnership between IEHP, Arrowhead Regional Medical Center, and Riverside University Health System aimed at improving access to specialty care for the safety-net population across San Bernardino and Riverside counties. IEHP is 1 of the 10 largest Medicaid health plans and the largest not-for-profit Medicare-Medicaid plan in the country, serving more than 1.2 million members.2 Data from MCel reveal the impacts of COVID-19 on eConsult use and offer insights into specialty resource availability during and outside of a crisis.
At the time of this analysis, 86 IEHP clinics in rural and urban settings across 38 specialties used the eConsult process to provide and obtain virtual specialty care, as well as timely appointments for in-person specialty care.3 eConsults are facilitated through a HIPAA-secure web-based portal that enables communication and sharing of information between the primary care provider (PCP) and a specialist. eConsult gives PCPs virtual access to specialists to coordinate care for their patients and determine the need for in-person specialty visits. Through the PCP-specialist eConsult dialogue, patients gain virtual access to specialty care. If a PCP-specialist care team determines the patient needs an in-person visit, that specialty referral is automatically authorized by IEHP, without the need for further review. At IEHP, eConsult is the primary method used for obtaining outpatient specialty referrals.
To analyze eConsult utilization before and during the pandemic, we gathered data from the MCeI program for the periods February 20–March 19, 2020, and March 20–April 19, 2020. Measures included eConsult volume and outcomes of eConsults (eConsults closed as referrals for face-to-face specialist visits versus eConsults closed without resulting in referrals for face-to-face specialist visits). Statistical analysis using chi-square tests for independence was performed using IBM SPSS Statistics 25 (IBM, Armonk, NY).
The data show that after California’s stay-at-home order, issued on March 19, 2020,4 eConsult volumes initially decreased, reflecting a similar decrease in clinic visits and authorization requests submitted to IEHP. We observed a 4-week average of 1100 eConsults processed before the pandemic, and then a steep drop to a 4-week average of 500 eConsults processed after the stay-at-home order was issued. Despite the overall drop in the volume of eConsults submitted, demand for specialties like hematology and neurology remained high throughout the pandemic.
During the pandemic, certain specialties displayed rising rates of eConsults completed with specialists providing care recommendations to the PCP instead of resulting in a recommendation for a face-to-face (in-person or via telehealth) visit with a specialist (see Figure and Table). The trend of increasing eConsults that concluded without a face-to-face visit suggests newfound clinical consideration of limited medical resources, along with the desire to eliminate unnecessary risks of infection.
eConsults between PCPs and specialist reviewers via the IEHP portal resulted in higher rates of non-face-to-face recommendations. The specialist reviewers were able to provide treatment plans for PCPs to take care of patients without having to refer their patients to a specialist. This increase was significant across most of the specialties live on the MCeI program.
We believe that clinicians’ heightened awareness of the limitations of the US health care system should remain a key consideration and factor in medical decision-making about appropriate referrals after the pandemic has passed. The data demonstrate that the pandemic drove clinicians to make different decisions about referrals and care coordination. Physicians scrutinized individual cases more keenly and were not as quick to recommend a face-to-face visit. This awareness and consideration of specialty access before making a referral provides a valuable lesson. If this approach is applied to health care delivery post-pandemic, eConsults will help reduce unnecessary in-person specialist visits and will free up space and time for patients who genuinely do need in-person specialty care. In this way, eConsult will improve appropriate access to care for everyone and reduce unnecessary costs to the health care system at large.
An examination of eConsult utilization trends across Riverside and San Bernardino counties before and during the COVID-19 pandemic provides useful insights into how to reduce costs and improve access to care. Although the risk of exposure to COVID-19 currently presents a significant obstacle to obtaining in-person specialty care, pre-existing and long-standing barriers, such as long wait times and scarcity of specialists, remain critical issues to receiving care during and after the pandemic. The pandemic has proven eConsult’s value as a tool for effective care coordination. Leveraging provider-to-provider asynchronous communication offers an opportunity to reduce unnecessary utilization of scarce resources during and beyond the pandemic.
Corresponding author: Lisa Aubry, Aubry-L@iehp.org.
Financial disclosures: None.
Keywords: electronic consultation; care coordination; telehealth; telemedicine; virtual care.
1. Wosik J, Fudim M, Cameron B, et al. Telehealth transformation: COVID-19 and the rise of virtual care. J Am Med Inform Assoc. 2020;27:957-962.
2. Nash-Wong K. Inland Empire Health Plan Multi-county eConsult Initiative with Safety Net Connect improves specialty care for Southern California residents. [Press Release]. (July 24, 2019). www.businesswire.com/news/home/20190724005208/en/Inland-Empire-Health-Plan-Multi-county-eConsult-Initiative. Accessed July 16, 2020.
3. The Multi-County eConsult Initiative (March 2018). https://www.eConsultie.com. Accessed July 16, 2020.
4. Executive Department State of California. Exec. Order No. N-33-20 of March 19, 2020. Safer at Home, Stay at Home. www.gov.ca.gov. Accessed July 16, 2020.
1. Wosik J, Fudim M, Cameron B, et al. Telehealth transformation: COVID-19 and the rise of virtual care. J Am Med Inform Assoc. 2020;27:957-962.
2. Nash-Wong K. Inland Empire Health Plan Multi-county eConsult Initiative with Safety Net Connect improves specialty care for Southern California residents. [Press Release]. (July 24, 2019). www.businesswire.com/news/home/20190724005208/en/Inland-Empire-Health-Plan-Multi-county-eConsult-Initiative. Accessed July 16, 2020.
3. The Multi-County eConsult Initiative (March 2018). https://www.eConsultie.com. Accessed July 16, 2020.
4. Executive Department State of California. Exec. Order No. N-33-20 of March 19, 2020. Safer at Home, Stay at Home. www.gov.ca.gov. Accessed July 16, 2020.
Implementation of a Patient Blood Management Program in a Large, Diverse Multi-Hospital System
From BJC HealthCare, St. Louis, MO.
Abstract
Background: There is limited literature relating to patient blood management (PBM) programs in large multi-hospital systems or addressing challenges of implementation across diverse systems comprised of community and academic hospitals.
Objective: To establish a PBM program to improve utilization of blood transfusion units at a multi-hospital system in the Midwest (BJC HealthCare).
Methods: High-impact strategies in establishing the PBM program included formation of Clinical Expert Councils (CECs) of providers, establishment of consensus utilization guidelines, and development of a robust reporting tool. CECs enabled collaboration and facilitated standardization across a complex system of academic, private practice, and tertiary facilities with a diverse community of medical providers. Consensus guidelines and the PBM reporting tool were key to creating meaningful reports to drive provider practice change.
Results: Over the 5 years following implementation of the PBM program, there has been a steady decrease in red blood cell (RBC) utilization. Noticeable changes have taken place at individual hospitals in the system, including reductions in transfusions falling outside guideline parameters from 300 per quarter to less than 8 per quarter at 1 of our community hospitals. No negative impact on patient care has been identified.
Conclusion: In response to current transfusion guidelines and the need for optimizing stewardship of blood product resources, this hospital system successfully implemented a robust PBM program that engaged academic and non-academic community providers and decreased utilization of blood transfusion resources in line with consensus guidelines.
Keywords: quality improvement; RBC transfusion; transfusion practices; provider practice change; utilization trends.
Evidence from clinical trials and published clinical guidelines support the adoption of a restrictive blood transfusion approach in hospitalized, stable patients as best practice.1-5 As such, the development and implementation of patient blood management (PBM) programs has become an increasingly important process improvement for reducing variability in transfusion practices and clinical outcomes.
As recently as 2013, BJC HealthCare, a multi-hospital system in the Midwest, had no standardized, system-wide blood management program, and transfusion practices varied widely across providers and between individual hospitals based on size, patient population, and resources. The system consisted of 13 hospitals, ranging from large tertiary to smaller community and academic hospitals. Although adults constituted the vast majority of the patient population, the hospital system also included a pediatric specialty hospital, St. Louis Children’s Hospital. In addition, some sites were staffed by private practice providers and others by university-based providers, including blood bank medical directors. Due to the diversity of settings and populations, efforts to align transfusion and other practices often faced multiple challenges. However, improving the management of blood transfusions was identified as a key resource stewardship priority in 2013, and implementation of a system-wide program began after extensive discussions and consensus approval by senior hospital system and medical leadership. The primary aim of the program was to optimize overall blood product resource stewardship. Specifically, we sought to control or reduce costs per patient-care episode using strategies that would not negatively impact patient care and could potentially even improve patient outcomes (eg, by avoiding unnecessary transfusions and their attendant risks).
There is a plethora of literature related to the implemention of PBM programs in individual hospitals,6-18 but few reports specifically relate to large multi-hospital health systems,19-21 or directly address the unique challenges of implementation across a diverse system of community and academic hospitals and providers.19 Here, we discuss our experience with establishing a PBM program in a large, diverse, multi-hospital health system, provide examples of innovative strategies, and address challenges faced and lessons learned. Future endeavors of the PBM program at BJC HealthCare are also described.
Setting
BJC HealthCare is one of the largest nonprofit health care organizations in the United States, delivering services to the greater St. Louis, southern Illinois, and mid-Missouri regions, and addressing the health care needs of urban, suburban, and rural communities. As of 2018, the system included 15 hospitals and multiple community health locations comprising more than 3400 staffed beds, 31,500 employees, and 4300 physicians with privileges. The system annually has more than 151,000 hospital admissions, 81,000 outpatient surgery visits, and 537,000 emergency department visits. In addition to inpatient and outpatient care, services include primary care, community health and wellness, workplace health, home health, community mental health, rehabilitation, long-term care, and hospice. As a nonprofit system, BJC is the largest provider of charity care, unreimbursed care, and community benefit in Missouri, highlighting the fact that resource stewardship is a critical issue across the entire system and the communities served.22
PBM Project
Preparation for large-scale change across several hospitals began with creating a framework for the initiative, which consisted of a “burning platform,” a guiding vision, and a coalition. The burning platform identifies the importance and urgency of a change and helps to establish commitment. Between 2012 and 2014, the American Association of Blood Banks (AABB) released new evidence-based guidelines and recommendations calling for more restrictive transfusion practices pertaining to red blood cells (RBCs; ie, a hemoglobin threshold of 7 to 8 g/dL) in both inpatient and outpatient care.2 In addition, use of single-unit transfusions was recognized as best practice by the AABB in the Choosing Wisely campaign.23 Historically, adult patients requiring transfusions were given 2 units in succession. The new recommendations provided a strong basis for changing transfusion practices at BJC. It was believed that aligning transfusion practices with the new guidelines was consistent with the mission and vision of the work: that these changes could lead to optimization of resources, cost control, reductions in unnecessary blood transfusions, and potentially improved care (eg, fewer transfusion-related complications). We used the national guidelines to initiate discussions and to identify clinical conditions and associated laboratory parameters for transfusion therapy.
Once this burning platform was established, a team comprised of physicians, blood bank experts, quality consultants, data analysts, and supply managers, referred to as the Outcomes Team, was formed to lead the change efforts across the system. Initial projects for the team included developing system-wide consensus-based transfusion guidelines, providing education to providers on the new evidence in transfusion practice, and sharing BJC-specific historical utilization data. The guiding principle for the group was that “blood is a valuable resource, but not without risk, and less is more.” In order to disseminate the vision of the initiative across the system, campaign signs with the slogans “7 is the new 10” (referring to the g/dL transfusion threshold) and “1 is the new 2” (referring to the new practice of the preferential transfusion of single units rather than 2 at a time) were displayed in system hospitals.
Last, a guiding coalition of system leaders was needed to help push the initiative forward and sustain the program once fully implemented. Thus, a multidisciplinary PBM Clinical Expert Counciel (CEC) was formed to assist with implementation and maintenance of the program.
Role of PBM Clinical Expert Council
The PBM CEC was designed to improve overall physician and expert engagement and provide a forum where stakeholders from across the system could participate to voice their expert opinion. CECs (which BJC formed in other clinical areas as well) are multidisciplinary teams consisting of clinical, administrative, and technical staff. The open, multidisciplinary structure of the councils allows for collaboration that promotes change across a complex multi-hospital system. Each hospital is represented by key physicians and technical leaders, opening opportunity for both horizontal and vertical partnership.
As part of the overall physician engagement strategy, the PBM CEC was launched across BJC in November 2013 as a decision-making body for gaining system consensus on matters relating to blood management. The initial goals for the PBM CEC were to share information and educate providers and others on the latest evidence, to subsequently debate and develop consensus for guidelines to be applied across BJC, and to identify and adopt gold standard practices to drive and sustain compliance across the system. More specifically, we wanted to focus on how to avoid unnecessary blood transfusions known to be associated with increased risk for adverse reactions, other morbidity, mortality, and longer length of stay. Council members met quarterly to address 6 key drivers: patient safety, informatics and data, quality improvement, efficiencies and workflows, education and competency, and communication and engagement. Members then voted to approve guidelines, policies, and procedures. The group continues to assist in updating and standardizing guidelines and providing input on improving the functionality of the PBM reporting tool.
Development of the PBM Reporting Tool
Providing and sharing data on blood utilization and practices with the CEC and hospital leaders was imperative to driving change. The Outcomes Team deliberated on how best to generate and provide such information, conducting comparisons between selected vendor-based tools and potential internal BJC solutions. After investigation, BJC leadership approved the development of an in-house PBM dashboard tool using Tableau Desktop (Tableau Software, Inc.). The tool consists of an executive page with 5 additional tabs for navigating to the appropriate information (Figure 1 and Figure 2); data within the tool are organized by facility, service, provider, ICD diagnosis, transfusion indication, and the Clinical Classifications Software category, as defined by the Agency for Healthcare Research and Quality.
The PBM reporting tool was launched on December 31, 2014. The next priority after the launch was to validate the tool’s blood utilization data and implement enhancements to make the tool more effective for users. A super-user group consisting of blood bank supervisors and managers was established. The goals of the user group were to preview any enhancements before presenting the tool to the larger CEC, test and validate data once new information was added, and share and prioritize future enhancements. User group meetings were held monthly to share best practices and discuss individual facilities’ blood utilization data. In addition, each facility’s representative(s) shared how they were driving changes in provider practice and discussed challenges specific to their facility. Enhancements suggested through the user group included: incorporation of additional lab values into the tool to correspond with other blood products (eg, fibrinogen, hematocrit, international normalized ratio, and platelet count), addition of the specific location where the blood product was administered, and standard naming conventions of locations to allow comparisons across facilities (eg, Emergency Department instead of ED, ER, or EU).
All hospital users were given access to a test version of the reporting tool where they could review enhancements, identify what worked well and what could be done better, and suggest corrections. As changes were made to the hospital lab systems, a sample of data was reviewed and validated with affected facilities to confirm the continued accuracy of the data. To ensure its practicality to users, the tool continues to be improved upon with input from council stakeholders and subject-matter experts.
Measurements
To monitor blood utilization across the health system, we tracked the total RBC units administered by hospital, service, and provider and also tracked pre- and post-transfusion hemoglobin values.
Results
Overall, the system has seen a steady decrease in RBC utilization over the 5 years since the PBM program was implemented (Table
In addition to system-wide improvement, noticeable changes have taken place at individual hospitals in the BJC system. For example, Boone Hospital Center in Columbia, Missouri, began critically reviewing all RBC transfusions starting in 2015 and, to raise awareness, communicating with any provider who transfused a patient outside of transfusion guidelines. Since then, Boone Hospital has seen a dramatic reduction in transfusions considered noncompliant (ie, falling outside guideline parameters), from 300 transfusions per quarter, down to less than 8 per quarter. St. Louis Children’s Hospital also began reviewing blood products utilized by providers that fell outside of the standardized guidelines. At this hospital, physician champions discuss any outliers with the providers involved and use multiple methods for disseminating information to providers, including grand rounds, faculty meetings, and new resident orientations.
Another success has been the partnership between Barnes Jewish St. Peters and Progress West Hospitals in providing PBM education. Their joint effort resulted in implementation of education modules in BJC’s internal learning system, and has provided PBM-related education to more than 367 nurses, blood bank staff, and physicians.
Challenges and Lessons Learned
Implementation of the PBM program was generally successful, but it was not without challenges. One of the biggest challenges was addressing the variation in care and practices across the hospital enterprise. Due to the varying sizes and service goals of individual hospitals, lack of standardization was a significant barrier to change. Gaining trust and buy-in was imperative to increasing compliance with new transfusion policies. The primary concern was finding a balance between respecting physician autonomy and emphasizing and aligning practices with new evidence in the literature. Thus, understanding and applying principles of thoughtful change management was imperative to advancing the framework of the PBM program. The CEC venue enabled collaboration among hospitals and staff and was ultimately used to facilitate the necessary standardization process. To gain the trust of hospital and medical staff, the Outcomes Team conducted several site visits, enabling face-to-face interaction with frontline staff and operational leaders. Moreover, the team’s emphasis on the use of the latest evidence-based guidelines in discussions with hospital and medical staff underscored the need for change.
Frank et al19 describes using an approach similar to our Outcomes Team at the Johns Hopkins Health System. A designated multidisciplinary quality improvement team, referred to as the “clinical community,” worked on implementing best practices for blood management across a system of 5 hospitals. The authors reported similar results, with an overall decrease in number of units transfused, as well as substantial cost savings.19 Our project, along with the project implemented by Frank et al, shows how a “consensus-community” approach, involving stakeholders and various experts across the system, can be be used to align practices among multiple hospitals.
Development of a robust PBM reporting tool was key to creating meaningful monthly reports and driving provider practice change. However, this did require several training sessions, site visits, and computer-based training. Members of the Outcomes Team engaged in one-on-one sessions with tool users as a way of addressing specific areas of concern raised by staff at individual blood banks, and also took part in system-wide initiatives. The team also attended blood bank staff meetings and hospital transfusion committee meetings to educate staff on the evidence and initiative, provide demos of the reporting tool, and allow for a more robust discussion of how the data could be used and shared with other departments. These sessions provided opportunities to identify and prioritize future enhancements, as well as opportunities for continued education and discussion at hospitals, which were critical to ongoing improvement of the reporting tool.
Conclusion and Future Directions
Blood products remain extremely valuable and scarce resources, and all health care professionals must work to prevent unnecessary transfusions and improve clinical outcomes by adhering to the latest evidence-based guidelines. In response to current transfusion guidelines and the need to optimize blood product resources, our system successfully implemented a robust PBM program that engaged both academic and non-academic providers and communities. Several elements of the program helped us overcome the challenges relating to standardization of transfusion practices: consensus-based development of guidelines using the latest scientific evidence; formation and utilization of the CEC venue to gain system-wide consensus around both guidelines and approaches to change; development of a trustworthy and accessible PBM reporting tool (as well as continuing education sessions to improve adoption and utilization of the tool); and ongoing multidisciplinary discussions and support of thoughtful change and sustaining activities. We have seen a system-wide decrease in the number of RBC units transfused (absolute and per case mix-adjusted patient day) since implementing the PBM program, and in the following years have noted a trending decrease in transfusion-related safety events. Although there was a slight increase in reported safety events from 2018 to 2019, this was likely due to the systematic implementation of a new electronic medical record system and improved reporting infrastructure.
Upcoming phases of our system-wide PBM program will include looking at opportunities to improve blood utilization in other specific clinical areas. For example, we have begun discussions with hematology and oncology experts across the system to expand their patient population data within the PBM reporting tool, and to identify areas of opportunity for provider practice change within their specialty. We are also reviewing cardiothoracic surgery transfusion data to identify opportunities for reducing blood utilization in specific clinical scenarios. In addition, we are working to incorporate our 2 newest hospital system members (Memorial Hospital East and Memorial Hospital Belleville) into the PBM program. In collaboration with perioperative leaders across the system, the surgical blood ordering process is being reviewed. The goal of this effort is to reduce blood products ordered in preparation for surgical procedures. We are also currently investigating whether an impact on safety events (ie, reduction in transfusion reactions) can yet be detected. Last, our health care system recently launched a system-wide electronic medical record, and we are eager to see how this will provide us with new methods to monitor and analyze blood administration and utilization data. We look forward to reporting on the expansion of our program and on any clinical outcome improvements gained through avoidance of unnecessary transfusions.
Acknowledgment: The authors thank the leadership within the Center for Clinical Excellence and Supply Chain at BJC HealthCare for their support of this manuscript, as well as all system participants who have contributed to these efforts, especially Mohammad Agha, MD, MHA, current physician leader of the PBM CEC, for his thoughtful edits of this manuscript.
Corresponding author: Audrey A. Gronemeyer, MPH, Center for Clinical Excellence, BJC HealthCare, 8300 Eager Road, Suite 400A, St. Louis, MO 63144; audrey.gronemeyer@bjc.org.
Financial disclosures: None.
1. Carson JL, Grossman BJ, Kleinman S, et al. Red blood cell transfusion: A clinical practice guideline from the AABB*. Ann Intern Med. 2012;157:49-58.
2. Goodnough LT, Levy JH, Murphy MF. Concepts of blood transfusion in adults. Lancet. 2013;381:1845-1854.
3. Hébert PC, Carson JL. Transfusion threshold of 7 g per deciliter—The new normal. N Engl J Med. 2014;371:1459-1461.
4. Gani F, Cerullo M, Ejaz A, et al. Implementation of a blood management program at a tertiary care hospital: Effect on transfusion practices and clinical outcomes among patients undergoing surgery. Ann Surg. 2019;269:1073-1079.
5. Podlasek SJ, Thakkar RN, Rotello LC, et al. Implementing a “why give 2 when 1 will do?” Choosing Wisely campaign. Transfusion. 2016;56:2164.
6. Boral LI, Bernard A, Hjorth T, et al. How do I implement a more restrictive transfusion trigger of hemoglobin level of 7 g/dL at my hospital? Transfusion. 2015;55:937-945.
7. Geissler RG, Kosters C, Franz D, et al. Utilization of blood components in trauma surgery: A single-center, retrospective analysis before and after the implementation of an educative PBM initiative. Transfuse Med Hemother. 2015;42:83-89.
8. Goel R, Cushing MM, Tobian AA. Pediatric patient blood management programs: Not just transfusing little adults. Transfus Med Rev. 2016;30:235-241.
9. Gupta PB, DeMario VM, Amin RM, et al. Patient blood management program improves blood use and clinical outcomes in orthopedic surgery. Anesthesiology. 2018;129;1082-1091.
10. Leahy MF, Roberts H, Mukhtar SA, et al. A pragmatic approach to embedding patient blood management in a tertiary hospital. Transfusion. 2014;54:1133-1145.
11. Leahy MF, Hofmann A, Towler S, et al. Improved outcomes and reduced costs associated with a health-system-wide patient blood management program: A retrospective observational study in four major adult tertiary-care hospitals. Transfusion. 2017;57:1347-1358.
12. Meybohm P, Herrmann E, Steinbicker AU, et al. Patient blood management is associated with a substantial reduction of red blood cell utilization and safe for patient’s outcome: A prospective, multicenter cohort study with a noninferiority design. Ann Surg. 2016;264:203-211.
13. Morgan PN, Coleman PL, Martinez-Garduno CM, et al. Implementation of a patient blood management program in an Australian private hospital orthopedic unit. J Blood Med. 2018;9;83-90.
14. Norgaard A, Stensballe J, de Lichtenberg TH, et al. Three-year follow-up of implementation of evidence-based transfusion practice in a tertiary hospital. Vox Sang. 2017;112:229-239.
15. Meuller MM, Van Remoortel H, Meybohm P, et al. Patient blood management: Recommendations from the 2018 Frankfurt Consensus Conference. JAMA. 2019;321:983-997.
16. Oliver JC, Griffin RL, Hannon T, Marques MB. The success of our patient blood management program depended on an institution-wide change in transfusion practices. Transfusion. 2014;54:2617-2624.
17. Thakkar RN, Lee KH, Ness PM, et al. Relative impact of a patient blood management program on utilization of all three major blood components. Transfusion. 2016;56:2212-2220.
18. Yang WW, Thakkar RN, Gehrie EA, et al. Single-unit transfusions and hemoglobin trigger: relative impact on red cell utilization. Transfusion. 2017;57:1163-1170.
19. Frank SM, Thakkar RN, Podlasek SJ, et al. Implementing a health system-wide patient blood management program with a clinical community approach. Anesthesiology. 2017;127;754-764.
20. Verdecchia NM, Wisniewski MK, Waters JH, et al. Changes in blood product utilization in a seven-hospital system after the implementation of a patient blood management program: A 9-year follow-up. Hematology. 2016;21:490-499.
21. Yazer MH, Waters JH. How do I implement a hospital-based blood management program? Transfusion. 2012;52:1640-1645.
22. BJC HealthCare. Facts and Figures.. BJC HealthCare website. www.bjc.org/About-Us/Facts-Figures. Accessed November 18, 2019.
23. Callum JL, Waters JH, Shaz BH, et al. The AABB recommendations for the Choosing Wisely campaign of the American Board of Internal Medicine. Transfusion. 2014;54:2344-2352.
From BJC HealthCare, St. Louis, MO.
Abstract
Background: There is limited literature relating to patient blood management (PBM) programs in large multi-hospital systems or addressing challenges of implementation across diverse systems comprised of community and academic hospitals.
Objective: To establish a PBM program to improve utilization of blood transfusion units at a multi-hospital system in the Midwest (BJC HealthCare).
Methods: High-impact strategies in establishing the PBM program included formation of Clinical Expert Councils (CECs) of providers, establishment of consensus utilization guidelines, and development of a robust reporting tool. CECs enabled collaboration and facilitated standardization across a complex system of academic, private practice, and tertiary facilities with a diverse community of medical providers. Consensus guidelines and the PBM reporting tool were key to creating meaningful reports to drive provider practice change.
Results: Over the 5 years following implementation of the PBM program, there has been a steady decrease in red blood cell (RBC) utilization. Noticeable changes have taken place at individual hospitals in the system, including reductions in transfusions falling outside guideline parameters from 300 per quarter to less than 8 per quarter at 1 of our community hospitals. No negative impact on patient care has been identified.
Conclusion: In response to current transfusion guidelines and the need for optimizing stewardship of blood product resources, this hospital system successfully implemented a robust PBM program that engaged academic and non-academic community providers and decreased utilization of blood transfusion resources in line with consensus guidelines.
Keywords: quality improvement; RBC transfusion; transfusion practices; provider practice change; utilization trends.
Evidence from clinical trials and published clinical guidelines support the adoption of a restrictive blood transfusion approach in hospitalized, stable patients as best practice.1-5 As such, the development and implementation of patient blood management (PBM) programs has become an increasingly important process improvement for reducing variability in transfusion practices and clinical outcomes.
As recently as 2013, BJC HealthCare, a multi-hospital system in the Midwest, had no standardized, system-wide blood management program, and transfusion practices varied widely across providers and between individual hospitals based on size, patient population, and resources. The system consisted of 13 hospitals, ranging from large tertiary to smaller community and academic hospitals. Although adults constituted the vast majority of the patient population, the hospital system also included a pediatric specialty hospital, St. Louis Children’s Hospital. In addition, some sites were staffed by private practice providers and others by university-based providers, including blood bank medical directors. Due to the diversity of settings and populations, efforts to align transfusion and other practices often faced multiple challenges. However, improving the management of blood transfusions was identified as a key resource stewardship priority in 2013, and implementation of a system-wide program began after extensive discussions and consensus approval by senior hospital system and medical leadership. The primary aim of the program was to optimize overall blood product resource stewardship. Specifically, we sought to control or reduce costs per patient-care episode using strategies that would not negatively impact patient care and could potentially even improve patient outcomes (eg, by avoiding unnecessary transfusions and their attendant risks).
There is a plethora of literature related to the implemention of PBM programs in individual hospitals,6-18 but few reports specifically relate to large multi-hospital health systems,19-21 or directly address the unique challenges of implementation across a diverse system of community and academic hospitals and providers.19 Here, we discuss our experience with establishing a PBM program in a large, diverse, multi-hospital health system, provide examples of innovative strategies, and address challenges faced and lessons learned. Future endeavors of the PBM program at BJC HealthCare are also described.
Setting
BJC HealthCare is one of the largest nonprofit health care organizations in the United States, delivering services to the greater St. Louis, southern Illinois, and mid-Missouri regions, and addressing the health care needs of urban, suburban, and rural communities. As of 2018, the system included 15 hospitals and multiple community health locations comprising more than 3400 staffed beds, 31,500 employees, and 4300 physicians with privileges. The system annually has more than 151,000 hospital admissions, 81,000 outpatient surgery visits, and 537,000 emergency department visits. In addition to inpatient and outpatient care, services include primary care, community health and wellness, workplace health, home health, community mental health, rehabilitation, long-term care, and hospice. As a nonprofit system, BJC is the largest provider of charity care, unreimbursed care, and community benefit in Missouri, highlighting the fact that resource stewardship is a critical issue across the entire system and the communities served.22
PBM Project
Preparation for large-scale change across several hospitals began with creating a framework for the initiative, which consisted of a “burning platform,” a guiding vision, and a coalition. The burning platform identifies the importance and urgency of a change and helps to establish commitment. Between 2012 and 2014, the American Association of Blood Banks (AABB) released new evidence-based guidelines and recommendations calling for more restrictive transfusion practices pertaining to red blood cells (RBCs; ie, a hemoglobin threshold of 7 to 8 g/dL) in both inpatient and outpatient care.2 In addition, use of single-unit transfusions was recognized as best practice by the AABB in the Choosing Wisely campaign.23 Historically, adult patients requiring transfusions were given 2 units in succession. The new recommendations provided a strong basis for changing transfusion practices at BJC. It was believed that aligning transfusion practices with the new guidelines was consistent with the mission and vision of the work: that these changes could lead to optimization of resources, cost control, reductions in unnecessary blood transfusions, and potentially improved care (eg, fewer transfusion-related complications). We used the national guidelines to initiate discussions and to identify clinical conditions and associated laboratory parameters for transfusion therapy.
Once this burning platform was established, a team comprised of physicians, blood bank experts, quality consultants, data analysts, and supply managers, referred to as the Outcomes Team, was formed to lead the change efforts across the system. Initial projects for the team included developing system-wide consensus-based transfusion guidelines, providing education to providers on the new evidence in transfusion practice, and sharing BJC-specific historical utilization data. The guiding principle for the group was that “blood is a valuable resource, but not without risk, and less is more.” In order to disseminate the vision of the initiative across the system, campaign signs with the slogans “7 is the new 10” (referring to the g/dL transfusion threshold) and “1 is the new 2” (referring to the new practice of the preferential transfusion of single units rather than 2 at a time) were displayed in system hospitals.
Last, a guiding coalition of system leaders was needed to help push the initiative forward and sustain the program once fully implemented. Thus, a multidisciplinary PBM Clinical Expert Counciel (CEC) was formed to assist with implementation and maintenance of the program.
Role of PBM Clinical Expert Council
The PBM CEC was designed to improve overall physician and expert engagement and provide a forum where stakeholders from across the system could participate to voice their expert opinion. CECs (which BJC formed in other clinical areas as well) are multidisciplinary teams consisting of clinical, administrative, and technical staff. The open, multidisciplinary structure of the councils allows for collaboration that promotes change across a complex multi-hospital system. Each hospital is represented by key physicians and technical leaders, opening opportunity for both horizontal and vertical partnership.
As part of the overall physician engagement strategy, the PBM CEC was launched across BJC in November 2013 as a decision-making body for gaining system consensus on matters relating to blood management. The initial goals for the PBM CEC were to share information and educate providers and others on the latest evidence, to subsequently debate and develop consensus for guidelines to be applied across BJC, and to identify and adopt gold standard practices to drive and sustain compliance across the system. More specifically, we wanted to focus on how to avoid unnecessary blood transfusions known to be associated with increased risk for adverse reactions, other morbidity, mortality, and longer length of stay. Council members met quarterly to address 6 key drivers: patient safety, informatics and data, quality improvement, efficiencies and workflows, education and competency, and communication and engagement. Members then voted to approve guidelines, policies, and procedures. The group continues to assist in updating and standardizing guidelines and providing input on improving the functionality of the PBM reporting tool.
Development of the PBM Reporting Tool
Providing and sharing data on blood utilization and practices with the CEC and hospital leaders was imperative to driving change. The Outcomes Team deliberated on how best to generate and provide such information, conducting comparisons between selected vendor-based tools and potential internal BJC solutions. After investigation, BJC leadership approved the development of an in-house PBM dashboard tool using Tableau Desktop (Tableau Software, Inc.). The tool consists of an executive page with 5 additional tabs for navigating to the appropriate information (Figure 1 and Figure 2); data within the tool are organized by facility, service, provider, ICD diagnosis, transfusion indication, and the Clinical Classifications Software category, as defined by the Agency for Healthcare Research and Quality.
The PBM reporting tool was launched on December 31, 2014. The next priority after the launch was to validate the tool’s blood utilization data and implement enhancements to make the tool more effective for users. A super-user group consisting of blood bank supervisors and managers was established. The goals of the user group were to preview any enhancements before presenting the tool to the larger CEC, test and validate data once new information was added, and share and prioritize future enhancements. User group meetings were held monthly to share best practices and discuss individual facilities’ blood utilization data. In addition, each facility’s representative(s) shared how they were driving changes in provider practice and discussed challenges specific to their facility. Enhancements suggested through the user group included: incorporation of additional lab values into the tool to correspond with other blood products (eg, fibrinogen, hematocrit, international normalized ratio, and platelet count), addition of the specific location where the blood product was administered, and standard naming conventions of locations to allow comparisons across facilities (eg, Emergency Department instead of ED, ER, or EU).
All hospital users were given access to a test version of the reporting tool where they could review enhancements, identify what worked well and what could be done better, and suggest corrections. As changes were made to the hospital lab systems, a sample of data was reviewed and validated with affected facilities to confirm the continued accuracy of the data. To ensure its practicality to users, the tool continues to be improved upon with input from council stakeholders and subject-matter experts.
Measurements
To monitor blood utilization across the health system, we tracked the total RBC units administered by hospital, service, and provider and also tracked pre- and post-transfusion hemoglobin values.
Results
Overall, the system has seen a steady decrease in RBC utilization over the 5 years since the PBM program was implemented (Table
In addition to system-wide improvement, noticeable changes have taken place at individual hospitals in the BJC system. For example, Boone Hospital Center in Columbia, Missouri, began critically reviewing all RBC transfusions starting in 2015 and, to raise awareness, communicating with any provider who transfused a patient outside of transfusion guidelines. Since then, Boone Hospital has seen a dramatic reduction in transfusions considered noncompliant (ie, falling outside guideline parameters), from 300 transfusions per quarter, down to less than 8 per quarter. St. Louis Children’s Hospital also began reviewing blood products utilized by providers that fell outside of the standardized guidelines. At this hospital, physician champions discuss any outliers with the providers involved and use multiple methods for disseminating information to providers, including grand rounds, faculty meetings, and new resident orientations.
Another success has been the partnership between Barnes Jewish St. Peters and Progress West Hospitals in providing PBM education. Their joint effort resulted in implementation of education modules in BJC’s internal learning system, and has provided PBM-related education to more than 367 nurses, blood bank staff, and physicians.
Challenges and Lessons Learned
Implementation of the PBM program was generally successful, but it was not without challenges. One of the biggest challenges was addressing the variation in care and practices across the hospital enterprise. Due to the varying sizes and service goals of individual hospitals, lack of standardization was a significant barrier to change. Gaining trust and buy-in was imperative to increasing compliance with new transfusion policies. The primary concern was finding a balance between respecting physician autonomy and emphasizing and aligning practices with new evidence in the literature. Thus, understanding and applying principles of thoughtful change management was imperative to advancing the framework of the PBM program. The CEC venue enabled collaboration among hospitals and staff and was ultimately used to facilitate the necessary standardization process. To gain the trust of hospital and medical staff, the Outcomes Team conducted several site visits, enabling face-to-face interaction with frontline staff and operational leaders. Moreover, the team’s emphasis on the use of the latest evidence-based guidelines in discussions with hospital and medical staff underscored the need for change.
Frank et al19 describes using an approach similar to our Outcomes Team at the Johns Hopkins Health System. A designated multidisciplinary quality improvement team, referred to as the “clinical community,” worked on implementing best practices for blood management across a system of 5 hospitals. The authors reported similar results, with an overall decrease in number of units transfused, as well as substantial cost savings.19 Our project, along with the project implemented by Frank et al, shows how a “consensus-community” approach, involving stakeholders and various experts across the system, can be be used to align practices among multiple hospitals.
Development of a robust PBM reporting tool was key to creating meaningful monthly reports and driving provider practice change. However, this did require several training sessions, site visits, and computer-based training. Members of the Outcomes Team engaged in one-on-one sessions with tool users as a way of addressing specific areas of concern raised by staff at individual blood banks, and also took part in system-wide initiatives. The team also attended blood bank staff meetings and hospital transfusion committee meetings to educate staff on the evidence and initiative, provide demos of the reporting tool, and allow for a more robust discussion of how the data could be used and shared with other departments. These sessions provided opportunities to identify and prioritize future enhancements, as well as opportunities for continued education and discussion at hospitals, which were critical to ongoing improvement of the reporting tool.
Conclusion and Future Directions
Blood products remain extremely valuable and scarce resources, and all health care professionals must work to prevent unnecessary transfusions and improve clinical outcomes by adhering to the latest evidence-based guidelines. In response to current transfusion guidelines and the need to optimize blood product resources, our system successfully implemented a robust PBM program that engaged both academic and non-academic providers and communities. Several elements of the program helped us overcome the challenges relating to standardization of transfusion practices: consensus-based development of guidelines using the latest scientific evidence; formation and utilization of the CEC venue to gain system-wide consensus around both guidelines and approaches to change; development of a trustworthy and accessible PBM reporting tool (as well as continuing education sessions to improve adoption and utilization of the tool); and ongoing multidisciplinary discussions and support of thoughtful change and sustaining activities. We have seen a system-wide decrease in the number of RBC units transfused (absolute and per case mix-adjusted patient day) since implementing the PBM program, and in the following years have noted a trending decrease in transfusion-related safety events. Although there was a slight increase in reported safety events from 2018 to 2019, this was likely due to the systematic implementation of a new electronic medical record system and improved reporting infrastructure.
Upcoming phases of our system-wide PBM program will include looking at opportunities to improve blood utilization in other specific clinical areas. For example, we have begun discussions with hematology and oncology experts across the system to expand their patient population data within the PBM reporting tool, and to identify areas of opportunity for provider practice change within their specialty. We are also reviewing cardiothoracic surgery transfusion data to identify opportunities for reducing blood utilization in specific clinical scenarios. In addition, we are working to incorporate our 2 newest hospital system members (Memorial Hospital East and Memorial Hospital Belleville) into the PBM program. In collaboration with perioperative leaders across the system, the surgical blood ordering process is being reviewed. The goal of this effort is to reduce blood products ordered in preparation for surgical procedures. We are also currently investigating whether an impact on safety events (ie, reduction in transfusion reactions) can yet be detected. Last, our health care system recently launched a system-wide electronic medical record, and we are eager to see how this will provide us with new methods to monitor and analyze blood administration and utilization data. We look forward to reporting on the expansion of our program and on any clinical outcome improvements gained through avoidance of unnecessary transfusions.
Acknowledgment: The authors thank the leadership within the Center for Clinical Excellence and Supply Chain at BJC HealthCare for their support of this manuscript, as well as all system participants who have contributed to these efforts, especially Mohammad Agha, MD, MHA, current physician leader of the PBM CEC, for his thoughtful edits of this manuscript.
Corresponding author: Audrey A. Gronemeyer, MPH, Center for Clinical Excellence, BJC HealthCare, 8300 Eager Road, Suite 400A, St. Louis, MO 63144; audrey.gronemeyer@bjc.org.
Financial disclosures: None.
From BJC HealthCare, St. Louis, MO.
Abstract
Background: There is limited literature relating to patient blood management (PBM) programs in large multi-hospital systems or addressing challenges of implementation across diverse systems comprised of community and academic hospitals.
Objective: To establish a PBM program to improve utilization of blood transfusion units at a multi-hospital system in the Midwest (BJC HealthCare).
Methods: High-impact strategies in establishing the PBM program included formation of Clinical Expert Councils (CECs) of providers, establishment of consensus utilization guidelines, and development of a robust reporting tool. CECs enabled collaboration and facilitated standardization across a complex system of academic, private practice, and tertiary facilities with a diverse community of medical providers. Consensus guidelines and the PBM reporting tool were key to creating meaningful reports to drive provider practice change.
Results: Over the 5 years following implementation of the PBM program, there has been a steady decrease in red blood cell (RBC) utilization. Noticeable changes have taken place at individual hospitals in the system, including reductions in transfusions falling outside guideline parameters from 300 per quarter to less than 8 per quarter at 1 of our community hospitals. No negative impact on patient care has been identified.
Conclusion: In response to current transfusion guidelines and the need for optimizing stewardship of blood product resources, this hospital system successfully implemented a robust PBM program that engaged academic and non-academic community providers and decreased utilization of blood transfusion resources in line with consensus guidelines.
Keywords: quality improvement; RBC transfusion; transfusion practices; provider practice change; utilization trends.
Evidence from clinical trials and published clinical guidelines support the adoption of a restrictive blood transfusion approach in hospitalized, stable patients as best practice.1-5 As such, the development and implementation of patient blood management (PBM) programs has become an increasingly important process improvement for reducing variability in transfusion practices and clinical outcomes.
As recently as 2013, BJC HealthCare, a multi-hospital system in the Midwest, had no standardized, system-wide blood management program, and transfusion practices varied widely across providers and between individual hospitals based on size, patient population, and resources. The system consisted of 13 hospitals, ranging from large tertiary to smaller community and academic hospitals. Although adults constituted the vast majority of the patient population, the hospital system also included a pediatric specialty hospital, St. Louis Children’s Hospital. In addition, some sites were staffed by private practice providers and others by university-based providers, including blood bank medical directors. Due to the diversity of settings and populations, efforts to align transfusion and other practices often faced multiple challenges. However, improving the management of blood transfusions was identified as a key resource stewardship priority in 2013, and implementation of a system-wide program began after extensive discussions and consensus approval by senior hospital system and medical leadership. The primary aim of the program was to optimize overall blood product resource stewardship. Specifically, we sought to control or reduce costs per patient-care episode using strategies that would not negatively impact patient care and could potentially even improve patient outcomes (eg, by avoiding unnecessary transfusions and their attendant risks).
There is a plethora of literature related to the implemention of PBM programs in individual hospitals,6-18 but few reports specifically relate to large multi-hospital health systems,19-21 or directly address the unique challenges of implementation across a diverse system of community and academic hospitals and providers.19 Here, we discuss our experience with establishing a PBM program in a large, diverse, multi-hospital health system, provide examples of innovative strategies, and address challenges faced and lessons learned. Future endeavors of the PBM program at BJC HealthCare are also described.
Setting
BJC HealthCare is one of the largest nonprofit health care organizations in the United States, delivering services to the greater St. Louis, southern Illinois, and mid-Missouri regions, and addressing the health care needs of urban, suburban, and rural communities. As of 2018, the system included 15 hospitals and multiple community health locations comprising more than 3400 staffed beds, 31,500 employees, and 4300 physicians with privileges. The system annually has more than 151,000 hospital admissions, 81,000 outpatient surgery visits, and 537,000 emergency department visits. In addition to inpatient and outpatient care, services include primary care, community health and wellness, workplace health, home health, community mental health, rehabilitation, long-term care, and hospice. As a nonprofit system, BJC is the largest provider of charity care, unreimbursed care, and community benefit in Missouri, highlighting the fact that resource stewardship is a critical issue across the entire system and the communities served.22
PBM Project
Preparation for large-scale change across several hospitals began with creating a framework for the initiative, which consisted of a “burning platform,” a guiding vision, and a coalition. The burning platform identifies the importance and urgency of a change and helps to establish commitment. Between 2012 and 2014, the American Association of Blood Banks (AABB) released new evidence-based guidelines and recommendations calling for more restrictive transfusion practices pertaining to red blood cells (RBCs; ie, a hemoglobin threshold of 7 to 8 g/dL) in both inpatient and outpatient care.2 In addition, use of single-unit transfusions was recognized as best practice by the AABB in the Choosing Wisely campaign.23 Historically, adult patients requiring transfusions were given 2 units in succession. The new recommendations provided a strong basis for changing transfusion practices at BJC. It was believed that aligning transfusion practices with the new guidelines was consistent with the mission and vision of the work: that these changes could lead to optimization of resources, cost control, reductions in unnecessary blood transfusions, and potentially improved care (eg, fewer transfusion-related complications). We used the national guidelines to initiate discussions and to identify clinical conditions and associated laboratory parameters for transfusion therapy.
Once this burning platform was established, a team comprised of physicians, blood bank experts, quality consultants, data analysts, and supply managers, referred to as the Outcomes Team, was formed to lead the change efforts across the system. Initial projects for the team included developing system-wide consensus-based transfusion guidelines, providing education to providers on the new evidence in transfusion practice, and sharing BJC-specific historical utilization data. The guiding principle for the group was that “blood is a valuable resource, but not without risk, and less is more.” In order to disseminate the vision of the initiative across the system, campaign signs with the slogans “7 is the new 10” (referring to the g/dL transfusion threshold) and “1 is the new 2” (referring to the new practice of the preferential transfusion of single units rather than 2 at a time) were displayed in system hospitals.
Last, a guiding coalition of system leaders was needed to help push the initiative forward and sustain the program once fully implemented. Thus, a multidisciplinary PBM Clinical Expert Counciel (CEC) was formed to assist with implementation and maintenance of the program.
Role of PBM Clinical Expert Council
The PBM CEC was designed to improve overall physician and expert engagement and provide a forum where stakeholders from across the system could participate to voice their expert opinion. CECs (which BJC formed in other clinical areas as well) are multidisciplinary teams consisting of clinical, administrative, and technical staff. The open, multidisciplinary structure of the councils allows for collaboration that promotes change across a complex multi-hospital system. Each hospital is represented by key physicians and technical leaders, opening opportunity for both horizontal and vertical partnership.
As part of the overall physician engagement strategy, the PBM CEC was launched across BJC in November 2013 as a decision-making body for gaining system consensus on matters relating to blood management. The initial goals for the PBM CEC were to share information and educate providers and others on the latest evidence, to subsequently debate and develop consensus for guidelines to be applied across BJC, and to identify and adopt gold standard practices to drive and sustain compliance across the system. More specifically, we wanted to focus on how to avoid unnecessary blood transfusions known to be associated with increased risk for adverse reactions, other morbidity, mortality, and longer length of stay. Council members met quarterly to address 6 key drivers: patient safety, informatics and data, quality improvement, efficiencies and workflows, education and competency, and communication and engagement. Members then voted to approve guidelines, policies, and procedures. The group continues to assist in updating and standardizing guidelines and providing input on improving the functionality of the PBM reporting tool.
Development of the PBM Reporting Tool
Providing and sharing data on blood utilization and practices with the CEC and hospital leaders was imperative to driving change. The Outcomes Team deliberated on how best to generate and provide such information, conducting comparisons between selected vendor-based tools and potential internal BJC solutions. After investigation, BJC leadership approved the development of an in-house PBM dashboard tool using Tableau Desktop (Tableau Software, Inc.). The tool consists of an executive page with 5 additional tabs for navigating to the appropriate information (Figure 1 and Figure 2); data within the tool are organized by facility, service, provider, ICD diagnosis, transfusion indication, and the Clinical Classifications Software category, as defined by the Agency for Healthcare Research and Quality.
The PBM reporting tool was launched on December 31, 2014. The next priority after the launch was to validate the tool’s blood utilization data and implement enhancements to make the tool more effective for users. A super-user group consisting of blood bank supervisors and managers was established. The goals of the user group were to preview any enhancements before presenting the tool to the larger CEC, test and validate data once new information was added, and share and prioritize future enhancements. User group meetings were held monthly to share best practices and discuss individual facilities’ blood utilization data. In addition, each facility’s representative(s) shared how they were driving changes in provider practice and discussed challenges specific to their facility. Enhancements suggested through the user group included: incorporation of additional lab values into the tool to correspond with other blood products (eg, fibrinogen, hematocrit, international normalized ratio, and platelet count), addition of the specific location where the blood product was administered, and standard naming conventions of locations to allow comparisons across facilities (eg, Emergency Department instead of ED, ER, or EU).
All hospital users were given access to a test version of the reporting tool where they could review enhancements, identify what worked well and what could be done better, and suggest corrections. As changes were made to the hospital lab systems, a sample of data was reviewed and validated with affected facilities to confirm the continued accuracy of the data. To ensure its practicality to users, the tool continues to be improved upon with input from council stakeholders and subject-matter experts.
Measurements
To monitor blood utilization across the health system, we tracked the total RBC units administered by hospital, service, and provider and also tracked pre- and post-transfusion hemoglobin values.
Results
Overall, the system has seen a steady decrease in RBC utilization over the 5 years since the PBM program was implemented (Table
In addition to system-wide improvement, noticeable changes have taken place at individual hospitals in the BJC system. For example, Boone Hospital Center in Columbia, Missouri, began critically reviewing all RBC transfusions starting in 2015 and, to raise awareness, communicating with any provider who transfused a patient outside of transfusion guidelines. Since then, Boone Hospital has seen a dramatic reduction in transfusions considered noncompliant (ie, falling outside guideline parameters), from 300 transfusions per quarter, down to less than 8 per quarter. St. Louis Children’s Hospital also began reviewing blood products utilized by providers that fell outside of the standardized guidelines. At this hospital, physician champions discuss any outliers with the providers involved and use multiple methods for disseminating information to providers, including grand rounds, faculty meetings, and new resident orientations.
Another success has been the partnership between Barnes Jewish St. Peters and Progress West Hospitals in providing PBM education. Their joint effort resulted in implementation of education modules in BJC’s internal learning system, and has provided PBM-related education to more than 367 nurses, blood bank staff, and physicians.
Challenges and Lessons Learned
Implementation of the PBM program was generally successful, but it was not without challenges. One of the biggest challenges was addressing the variation in care and practices across the hospital enterprise. Due to the varying sizes and service goals of individual hospitals, lack of standardization was a significant barrier to change. Gaining trust and buy-in was imperative to increasing compliance with new transfusion policies. The primary concern was finding a balance between respecting physician autonomy and emphasizing and aligning practices with new evidence in the literature. Thus, understanding and applying principles of thoughtful change management was imperative to advancing the framework of the PBM program. The CEC venue enabled collaboration among hospitals and staff and was ultimately used to facilitate the necessary standardization process. To gain the trust of hospital and medical staff, the Outcomes Team conducted several site visits, enabling face-to-face interaction with frontline staff and operational leaders. Moreover, the team’s emphasis on the use of the latest evidence-based guidelines in discussions with hospital and medical staff underscored the need for change.
Frank et al19 describes using an approach similar to our Outcomes Team at the Johns Hopkins Health System. A designated multidisciplinary quality improvement team, referred to as the “clinical community,” worked on implementing best practices for blood management across a system of 5 hospitals. The authors reported similar results, with an overall decrease in number of units transfused, as well as substantial cost savings.19 Our project, along with the project implemented by Frank et al, shows how a “consensus-community” approach, involving stakeholders and various experts across the system, can be be used to align practices among multiple hospitals.
Development of a robust PBM reporting tool was key to creating meaningful monthly reports and driving provider practice change. However, this did require several training sessions, site visits, and computer-based training. Members of the Outcomes Team engaged in one-on-one sessions with tool users as a way of addressing specific areas of concern raised by staff at individual blood banks, and also took part in system-wide initiatives. The team also attended blood bank staff meetings and hospital transfusion committee meetings to educate staff on the evidence and initiative, provide demos of the reporting tool, and allow for a more robust discussion of how the data could be used and shared with other departments. These sessions provided opportunities to identify and prioritize future enhancements, as well as opportunities for continued education and discussion at hospitals, which were critical to ongoing improvement of the reporting tool.
Conclusion and Future Directions
Blood products remain extremely valuable and scarce resources, and all health care professionals must work to prevent unnecessary transfusions and improve clinical outcomes by adhering to the latest evidence-based guidelines. In response to current transfusion guidelines and the need to optimize blood product resources, our system successfully implemented a robust PBM program that engaged both academic and non-academic providers and communities. Several elements of the program helped us overcome the challenges relating to standardization of transfusion practices: consensus-based development of guidelines using the latest scientific evidence; formation and utilization of the CEC venue to gain system-wide consensus around both guidelines and approaches to change; development of a trustworthy and accessible PBM reporting tool (as well as continuing education sessions to improve adoption and utilization of the tool); and ongoing multidisciplinary discussions and support of thoughtful change and sustaining activities. We have seen a system-wide decrease in the number of RBC units transfused (absolute and per case mix-adjusted patient day) since implementing the PBM program, and in the following years have noted a trending decrease in transfusion-related safety events. Although there was a slight increase in reported safety events from 2018 to 2019, this was likely due to the systematic implementation of a new electronic medical record system and improved reporting infrastructure.
Upcoming phases of our system-wide PBM program will include looking at opportunities to improve blood utilization in other specific clinical areas. For example, we have begun discussions with hematology and oncology experts across the system to expand their patient population data within the PBM reporting tool, and to identify areas of opportunity for provider practice change within their specialty. We are also reviewing cardiothoracic surgery transfusion data to identify opportunities for reducing blood utilization in specific clinical scenarios. In addition, we are working to incorporate our 2 newest hospital system members (Memorial Hospital East and Memorial Hospital Belleville) into the PBM program. In collaboration with perioperative leaders across the system, the surgical blood ordering process is being reviewed. The goal of this effort is to reduce blood products ordered in preparation for surgical procedures. We are also currently investigating whether an impact on safety events (ie, reduction in transfusion reactions) can yet be detected. Last, our health care system recently launched a system-wide electronic medical record, and we are eager to see how this will provide us with new methods to monitor and analyze blood administration and utilization data. We look forward to reporting on the expansion of our program and on any clinical outcome improvements gained through avoidance of unnecessary transfusions.
Acknowledgment: The authors thank the leadership within the Center for Clinical Excellence and Supply Chain at BJC HealthCare for their support of this manuscript, as well as all system participants who have contributed to these efforts, especially Mohammad Agha, MD, MHA, current physician leader of the PBM CEC, for his thoughtful edits of this manuscript.
Corresponding author: Audrey A. Gronemeyer, MPH, Center for Clinical Excellence, BJC HealthCare, 8300 Eager Road, Suite 400A, St. Louis, MO 63144; audrey.gronemeyer@bjc.org.
Financial disclosures: None.
1. Carson JL, Grossman BJ, Kleinman S, et al. Red blood cell transfusion: A clinical practice guideline from the AABB*. Ann Intern Med. 2012;157:49-58.
2. Goodnough LT, Levy JH, Murphy MF. Concepts of blood transfusion in adults. Lancet. 2013;381:1845-1854.
3. Hébert PC, Carson JL. Transfusion threshold of 7 g per deciliter—The new normal. N Engl J Med. 2014;371:1459-1461.
4. Gani F, Cerullo M, Ejaz A, et al. Implementation of a blood management program at a tertiary care hospital: Effect on transfusion practices and clinical outcomes among patients undergoing surgery. Ann Surg. 2019;269:1073-1079.
5. Podlasek SJ, Thakkar RN, Rotello LC, et al. Implementing a “why give 2 when 1 will do?” Choosing Wisely campaign. Transfusion. 2016;56:2164.
6. Boral LI, Bernard A, Hjorth T, et al. How do I implement a more restrictive transfusion trigger of hemoglobin level of 7 g/dL at my hospital? Transfusion. 2015;55:937-945.
7. Geissler RG, Kosters C, Franz D, et al. Utilization of blood components in trauma surgery: A single-center, retrospective analysis before and after the implementation of an educative PBM initiative. Transfuse Med Hemother. 2015;42:83-89.
8. Goel R, Cushing MM, Tobian AA. Pediatric patient blood management programs: Not just transfusing little adults. Transfus Med Rev. 2016;30:235-241.
9. Gupta PB, DeMario VM, Amin RM, et al. Patient blood management program improves blood use and clinical outcomes in orthopedic surgery. Anesthesiology. 2018;129;1082-1091.
10. Leahy MF, Roberts H, Mukhtar SA, et al. A pragmatic approach to embedding patient blood management in a tertiary hospital. Transfusion. 2014;54:1133-1145.
11. Leahy MF, Hofmann A, Towler S, et al. Improved outcomes and reduced costs associated with a health-system-wide patient blood management program: A retrospective observational study in four major adult tertiary-care hospitals. Transfusion. 2017;57:1347-1358.
12. Meybohm P, Herrmann E, Steinbicker AU, et al. Patient blood management is associated with a substantial reduction of red blood cell utilization and safe for patient’s outcome: A prospective, multicenter cohort study with a noninferiority design. Ann Surg. 2016;264:203-211.
13. Morgan PN, Coleman PL, Martinez-Garduno CM, et al. Implementation of a patient blood management program in an Australian private hospital orthopedic unit. J Blood Med. 2018;9;83-90.
14. Norgaard A, Stensballe J, de Lichtenberg TH, et al. Three-year follow-up of implementation of evidence-based transfusion practice in a tertiary hospital. Vox Sang. 2017;112:229-239.
15. Meuller MM, Van Remoortel H, Meybohm P, et al. Patient blood management: Recommendations from the 2018 Frankfurt Consensus Conference. JAMA. 2019;321:983-997.
16. Oliver JC, Griffin RL, Hannon T, Marques MB. The success of our patient blood management program depended on an institution-wide change in transfusion practices. Transfusion. 2014;54:2617-2624.
17. Thakkar RN, Lee KH, Ness PM, et al. Relative impact of a patient blood management program on utilization of all three major blood components. Transfusion. 2016;56:2212-2220.
18. Yang WW, Thakkar RN, Gehrie EA, et al. Single-unit transfusions and hemoglobin trigger: relative impact on red cell utilization. Transfusion. 2017;57:1163-1170.
19. Frank SM, Thakkar RN, Podlasek SJ, et al. Implementing a health system-wide patient blood management program with a clinical community approach. Anesthesiology. 2017;127;754-764.
20. Verdecchia NM, Wisniewski MK, Waters JH, et al. Changes in blood product utilization in a seven-hospital system after the implementation of a patient blood management program: A 9-year follow-up. Hematology. 2016;21:490-499.
21. Yazer MH, Waters JH. How do I implement a hospital-based blood management program? Transfusion. 2012;52:1640-1645.
22. BJC HealthCare. Facts and Figures.. BJC HealthCare website. www.bjc.org/About-Us/Facts-Figures. Accessed November 18, 2019.
23. Callum JL, Waters JH, Shaz BH, et al. The AABB recommendations for the Choosing Wisely campaign of the American Board of Internal Medicine. Transfusion. 2014;54:2344-2352.
1. Carson JL, Grossman BJ, Kleinman S, et al. Red blood cell transfusion: A clinical practice guideline from the AABB*. Ann Intern Med. 2012;157:49-58.
2. Goodnough LT, Levy JH, Murphy MF. Concepts of blood transfusion in adults. Lancet. 2013;381:1845-1854.
3. Hébert PC, Carson JL. Transfusion threshold of 7 g per deciliter—The new normal. N Engl J Med. 2014;371:1459-1461.
4. Gani F, Cerullo M, Ejaz A, et al. Implementation of a blood management program at a tertiary care hospital: Effect on transfusion practices and clinical outcomes among patients undergoing surgery. Ann Surg. 2019;269:1073-1079.
5. Podlasek SJ, Thakkar RN, Rotello LC, et al. Implementing a “why give 2 when 1 will do?” Choosing Wisely campaign. Transfusion. 2016;56:2164.
6. Boral LI, Bernard A, Hjorth T, et al. How do I implement a more restrictive transfusion trigger of hemoglobin level of 7 g/dL at my hospital? Transfusion. 2015;55:937-945.
7. Geissler RG, Kosters C, Franz D, et al. Utilization of blood components in trauma surgery: A single-center, retrospective analysis before and after the implementation of an educative PBM initiative. Transfuse Med Hemother. 2015;42:83-89.
8. Goel R, Cushing MM, Tobian AA. Pediatric patient blood management programs: Not just transfusing little adults. Transfus Med Rev. 2016;30:235-241.
9. Gupta PB, DeMario VM, Amin RM, et al. Patient blood management program improves blood use and clinical outcomes in orthopedic surgery. Anesthesiology. 2018;129;1082-1091.
10. Leahy MF, Roberts H, Mukhtar SA, et al. A pragmatic approach to embedding patient blood management in a tertiary hospital. Transfusion. 2014;54:1133-1145.
11. Leahy MF, Hofmann A, Towler S, et al. Improved outcomes and reduced costs associated with a health-system-wide patient blood management program: A retrospective observational study in four major adult tertiary-care hospitals. Transfusion. 2017;57:1347-1358.
12. Meybohm P, Herrmann E, Steinbicker AU, et al. Patient blood management is associated with a substantial reduction of red blood cell utilization and safe for patient’s outcome: A prospective, multicenter cohort study with a noninferiority design. Ann Surg. 2016;264:203-211.
13. Morgan PN, Coleman PL, Martinez-Garduno CM, et al. Implementation of a patient blood management program in an Australian private hospital orthopedic unit. J Blood Med. 2018;9;83-90.
14. Norgaard A, Stensballe J, de Lichtenberg TH, et al. Three-year follow-up of implementation of evidence-based transfusion practice in a tertiary hospital. Vox Sang. 2017;112:229-239.
15. Meuller MM, Van Remoortel H, Meybohm P, et al. Patient blood management: Recommendations from the 2018 Frankfurt Consensus Conference. JAMA. 2019;321:983-997.
16. Oliver JC, Griffin RL, Hannon T, Marques MB. The success of our patient blood management program depended on an institution-wide change in transfusion practices. Transfusion. 2014;54:2617-2624.
17. Thakkar RN, Lee KH, Ness PM, et al. Relative impact of a patient blood management program on utilization of all three major blood components. Transfusion. 2016;56:2212-2220.
18. Yang WW, Thakkar RN, Gehrie EA, et al. Single-unit transfusions and hemoglobin trigger: relative impact on red cell utilization. Transfusion. 2017;57:1163-1170.
19. Frank SM, Thakkar RN, Podlasek SJ, et al. Implementing a health system-wide patient blood management program with a clinical community approach. Anesthesiology. 2017;127;754-764.
20. Verdecchia NM, Wisniewski MK, Waters JH, et al. Changes in blood product utilization in a seven-hospital system after the implementation of a patient blood management program: A 9-year follow-up. Hematology. 2016;21:490-499.
21. Yazer MH, Waters JH. How do I implement a hospital-based blood management program? Transfusion. 2012;52:1640-1645.
22. BJC HealthCare. Facts and Figures.. BJC HealthCare website. www.bjc.org/About-Us/Facts-Figures. Accessed November 18, 2019.
23. Callum JL, Waters JH, Shaz BH, et al. The AABB recommendations for the Choosing Wisely campaign of the American Board of Internal Medicine. Transfusion. 2014;54:2344-2352.
An eConsults Program to Improve Patient Access to Specialty Care in an Academic Health System
From the Department of Medicine, University of California, Irvine, Orange, CA.
Abstract
Background: Orange County’s residents have difficulty accessing timely, quality, affordable specialty care services. As the county’s only academic health system, the University of California, Irvine (UCI) aimed to improve specialty care access for the communities it serves by implementing an electronic consultations (eConsults) program that allows primary care providers (PCPs) to efficiently receive specialist recommendations on referral problems that do not require an in-person evaluation.
Objective: To implement an eConsults program at the UCI that enhances access to and the delivery of coordinated specialty care for lower-complexity referral problems.
Methods: We developed custom solutions to integrate eConsults into UCI’s 2 electronic health record platforms. The impact of the eConsults program was assessed by continuously evaluating usage and outcomes. Measures used to track usage included the number of submitted eConsult requests per PCP, the number of completed responses per specialty, and the response time for eConsult requests. Outcome measures included the specialist recommendation (eg, in-office visit, consultation avoided) and physician feedback.
Results: Over 4.5 years, more than 1400 successful eConsults have been completed, and the program has expanded to 17 specialties. The average turnaround time for an eConsult response across all specialties was 1 business day. Moreover, more than 50% of the eConsults received specialty responses within the same day of the eConsult request. Most important, about 80% of eConsult requests were addressed without the need for an in-office visit with a specialist.
Conclusion: The enhanced access to and the delivery of coordinated specialty care provided by eConsults resulted in improved efficiency and specialty access, while likely reducing costs and improving patient satisfaction. The improved communication and collaboration among providers with eConsults has also led to overwhelmingly positive feedback from both PCPs and specialists.
Keywords: electronic consultation; access to care; primary care; specialty referral; telehealth.
Orange County’s growing, aging, and diverse population is driving an increased demand for health care.1 But with the county’s high cost of living and worsening shortage of physicians,1-3 many of its residents are struggling to access timely, quality, affordable care. Access to specialty care services is especially frustrating for many patients and their providers, both primary care providers (PCPs) and specialists, due to problems with the referral process. Many patients experience increased wait times for a visit with a specialist due to poor communication between providers, insufficient guidance on the information or diagnostic results needed by specialists, and lack of care coordination.4-6 One promising approach to overcome these challenges is the use of an electronic consultation, or eConsult, in place of a standard in-person referral. An eConsult is an asynchronous, non-face-to-face, provider-to-provider exchange using a secure electronic communication platform. For appropriate referral problems, the patient is able to receive timely access to specialist expertise through electronic referral by their PCP,7-9 and avoid the time and costs associated with a visit to the specialist,10,11 such as travel, missed work, co-pays, and child-care expenses. Clinical questions addressed using an eConsult system subsequently free up office visit appointment slots, improving access for patients requiring in-office evaluation.8,12
Orange County’s only academic health system, the University of California, Irvine (UCI), serves a population of 3.5 million, and its principal priority is providing the communities in the county (which is the sixth largest in United States) and the surrounding region with the highest quality health care possible. Thus, UCI aimed to improve its referral processes and provide timely access to specialty care for its patients by implementing an eConsults program that allows PCPs to efficiently receive specialist recommendations on referral problems that do not require the specialist to evaluate the patient in person. This report describes our experiences with developing and implementing a custom-built eConsults workflow in UCI’s prior electronic health record (EHR) platform, Allscripts, and subsequently transitioning our mature eConsults program to a new EHR system when UCI adopted Epic. UCI is likely the only academic medical center to have experience in successfully implementing eConsults into 2 different EHR systems.
Setting
UCI’s medical center is a 417-bed acute care hospital providing tertiary and quaternary care, ambulatory and specialty medical clinics, behavioral health care, and rehabilitation services. It is located in Orange, CA, and serves a diverse population of 3.5 million persons with broad health care needs. With more than 400 specialty and primary care physicians, UCI offers a full scope of acute and general care services. It is also the primary teaching location for UCI medical and nursing students, medical residents, and fellows, and is home to Orange County’s only adult Level I and pediatric Level II trauma centers and the regional burn center.
eConsults Program
We designed the initial eConsults program within UCI’s Allscripts EHR platform. Our information technology (IT) build team developed unique “documents-based” eConsults workflows that simplified the process of initiating requests directly from the EHR and facilitated rapid responses from participating specialties. The requesting provider’s eConsults interface was user-friendly, and referring providers were able to initiate an eConsult easily by selecting the customized eConsult icon from the Allscripts main toolbar. To ensure that all relevant information is provided to the specialists, condition-specific templates are embedded in the requesting provider’s eConsults workflow that allow PCPs to enter a focused, patient-specific clinical question and provide guidance on recommended patient information (eg, health history, laboratory results, and digital images) that may help the specialist provide an informed response. The eConsult templates were adapted from standardized forms developed by partner University of California Health Systems in an initiative funded by the University of California Center for Health Quality and Innovation.
To facilitate timely responses from specialists, an innovative notification system was created in the responding provider’s eConsults workflow to automatically send an email to participating specialists when a new eConsult is requested. The responding provider’s workflow also includes an option for the specialist to decline the eConsult if the case is deemed too complex to be addressed electronically. For every completed eConsult that does not result in an in-person patient evaluation, the requesting provider and responding specialist each receives a modest reimbursement, which was initially paid by UCI Health System funds.
Implementation
The design and implementation of the eConsults program began in November 2014, and was guided by a steering committee that included the chair of the department of medicine, chief medical information officer, primary care and specialty physician leads, IT build team, and a project manager. Early on, members of this committee engaged UCI leadership to affirm support for the program and obtain the IT resources needed to build the eConsults workflow. Regular steering committee meetings were established to discuss the design of the workflow, adapt the clinical content of the referral templates, and develop a provider reimbursement plan. After completion of the workflow build, the eConsults system was tested to identify failure points and obtain feedback from users. Prior to going live, the eConsults program was publicized by members of the steering committee through meetings with primary care groups and email communications. Committee members also hosted in-person training and orientation sessions with PCPs and participating specialists, and distributed tip sheets summarizing the steps to complete the PCP and specialist eConsult workflows.
The eConsults workflow build, testing, and launch were completed within 5 months (April 2015; Figure 1). eConsults went live in the 3 initial specialties (endocrinology, cardiology, and rheumatology) that were interested in participating in the first wave of the program. UCI’s eConsults service has subsequently expanded to 17 total specialties (allergy, cardiology, dermatology, endocrinology, gastroenterology, geriatrics, gynecology, hematology, hepatology, infectious disease, nephrology, neurology, palliative care, psychiatry, pulmonary, rheumatology, and sports medicine).
Two and half years after the eConsults program was implemented in Allscripts, UCI adopted a new EHR platform, Epic. By this time, the eConsults service had grown into a mature program with greater numbers of PCP users and submitted eConsults (Figure 2). Using our experience with the Allscripts build, our IT team was able to efficiently transition the eConsults service to the new EHR system. In contrast to the “documents-based” eConsult workflows on Allscripts, our IT team utilized an “orders-based” strategy on Epic, which followed a more traditional approach to requesting a consultation. We re-launched the service in Epic within 3 months (February 2018). However, both platforms utilized user-friendly workflows to achieve similar goals, and the program has continued to grow with respect to the number of users and eConsults.
Measurement/Analysis
The impact of the program was assessed by continuously evaluating usage and outcomes. Measures used to track usage included the number of PCP users, the number of submitted eConsult requests per PCP, and the number of requests per specialty. The response time for eConsult requests and the self-reported amount of time spent by specialists on the response were also tracked. Outcome measures included the specialist recommendation (eg, in-office visit, consultation avoided) and physician feedback. Provider satisfaction was primarily obtained by soliciting feedback from individual eConsult users.
Implementation of this eConsults program constituted a quality improvement activity and did not require Institutional Review Board review.
Results
Since the program was launched in April 2015, more than 1400 eConsults have been completed across 17 specialties (Figure 3). There were 654 completed eConsults on the Allscripts platform, and 808 eConsults have been completed using the Epic platform to date. The busiest eConsult specialties were endocrinology (receiving 276, or 19%, of the eConsults requests), hematology (receiving 249 requests, or 17%), infectious disease (receiving 244 requests, or 17% ), and cardiology (receiving 148 requests, or 10%).
The self-reported amount of time specialists spent on the response was different between the 2 EHR systems (Figure 4). On Allscripts, specialists reported that 23% of eConsults took 10 minutes or less to complete, 47% took 11 to 20 minutes, 23% took 21 to 30 minutes, and 7% took more than 30 minutes. On Epic, specialists reported that 42% of eConsults took 10 minutes or less to complete, 44% took 11 to 20 minutes, 12% took 21 to 30 minutes, and 2% took more than 30 minutes. This difference in time spent fielding eConsults likely represents the subtle nuances between Allscripts’ “documents-based” and Epic’s “orders-based” workflows.
As a result of the automated notification system that was introduced early in the eConsults implementation process on Allscripts, the specialty response times were much faster than the expected 3 business days’ turnaround goal instituted by the Center for Health Quality and Innovation initiative, regardless of the EHR platform used. In fact, the average turnaround time for an eConsult response across all specialties was 1 business day, which was similar for both EHR systems (Figure 5). Furthermore, more than 50% of the eConsults on both EHR systems received specialist responses within the same day of the eConsult request (63% on Allscripts, 54% on Epic). There was a small decrease in the percentage of same-day responses when we transitioned to Epic, likely because the functionality of an automated notification email could not be restored in Epic. Regardless, the specialty response times on Epic remained expeditious, likely because the automated notifications on Allscripts instilled good practices for the specialists, and regularly checking for new eConsult requests became an ingrained behavior.
Our most important finding was that approximately 80% of eConsult requests were addressed without the need for an in-office visit with a specialist. This measure was similar for both EHR platforms (83% on Allscripts and 78% on Epic).
Provider feedback has been overwhelmingly positive. PCPs are impressed with the robust educational content of the eConsult responses, since the goal for specialists is to justify their recommendations. Specialists appreciate the convenience and efficiency that eConsults offer, as well as the improved communication and collaboration among physicians. eConsults have been especially beneficial to PCPs at UCI’s Family Health Centers, who are now able to receive subspecialty consultations from UCI specialists despite insurance barriers.
Discussion
Our eConsults program uniquely contrasts with other programs because UCI is likely the only academic medical center to have experience in successfully incorporating eConsults into 2 different EHR systems: initial development of the eConsults workflow in UCI’s existing Allscripts EHR platform, and subsequently transitioning a mature eConsults program to a new EHR system when the institution adopted Epic.
We measured the impact of the eConsults program on access to care by the response time for eConsult requests and the percentage of eConsults that averted an in-office visit with a specialist. We found that the eConsults program at UCI provided our PCPs access to specialist consultations in a timely manner, with much shorter response times than standard in-person referrals. The average turnaround time for an eConsult response we reported is consistent with findings from other studies.12-15 Additionally, our program was able to address about 80% of its eConsults electronically, helping to reduce unnecessary in-person specialist referrals. In the literature, the percentage of eConsults that avoided an in-person specialist visit varies widely.8,12-16
We reported very positive feedback from both PCPs and specialists on UCI’s eConsults service. Similarly, other studies described PCP satisfaction with their respective eConsults programs to be uniformly high,8,9,13,14,17-19 though some reported that the level of satisfaction among specialists was more varied.18-21
Lessons Learned
The successful design and implementation of our eConsults program began with assembling the right clinical champions and technology partners for our steering committee. Establishing regular steering committee meetings helped maintain an appropriate timeline for completion of different aspects of the project. Engaging support from UCI’s leadership also provided us with a dedicated IT team that helped us with the build, training resources, troubleshooting issues, and reporting for the project.
Our experience with implementing the eConsults program on 2 different EHR systems highlighted the importance of creating efficient, user-friendly workflows to foster provider adoption and achieve sustainability. Allscripts’ open platform gave our IT team the ability to create a homegrown solution to implementing an eConsult model that was simple and easy to use. The Epic platform’s interoperability allowed us to leverage our learnings from the Allscripts build to efficiently implement eConsults in Epic.
We also found that providing modest incentive payments or reimbursements to both PCPs and specialists for each completed eConsult helps with both adoption and program sustainability. Initially, credit for the eConsult work was paid by internal UCI Health System funds. Two payers, UC Care (a preferred provider organization plan created just for the University of California) and more recently, the Centers for Medicare & Medicaid Services, have agreed to reimburse for outpatient eConsults. Securing additional payers for reimbursement of the eConsult service will not only ensure the program’s long-term sustainability, but also represents an acknowledgment of the value of eConsults in supporting access to care.
Applicability
Other health care settings that are experiencing issues with specialty care access can successfully implement their own eConsults program by employing strategies similar to those described in this report—assembling the right team, creating user-friendly workflows, and providing incentives. Our advice for successful implementation is to clearly communicate your goals to all involved, including primary care, specialists, leadership, and IT partners, and establish with these stakeholders the appropriate support and resources needed to facilitate the development of the program and overcome any barriers to adoption.
Current Status and Future Directions
Our future plans include continuing to optimize the Epic eConsult backend build and workflows using our experience in Allscripts. We have implemented eConsult workflows for use by graduate medical education trainees and advanced practice providers, with attending supervision. Further work is in progress to optimize these workflows, which will allow for appropriate education and supervision without delaying care. Furthermore, we plan to expand the program to include inpatient-to-inpatient and emergency department-to-inpatient eConsults. We will continue to expand the eConsults program by offering additional specialties, engage providers to encourage ongoing participation, and maximize PCP use by continuing to market the program through regular newsletters and email communications. Finally, the eConsults has served as an effective, important resource in the current era of COVID-19 in several ways: it allows for optimization of specialty input in patient care delivery without subjecting more health care workers to unnecessary exposure; saves on utilization of precious personal protective equipment; and enhances our ability to deal with a potential surge by providing access to specialists remotely and electronically all hours of the day, thus expanding care to the evening and weekend hours.
Acknowledgment: The authors thank our steering committee members (Dr. Ralph Cygan, Dr. Andrew Reikes, Dr. Byron Allen, Dr. George Lawry) and IT build team (Lori Bocchicchio, Meghan van Witsen, Jaymee Zillgitt, Tanya Sickles, Dennis Hoang, Jeanette Lisak-Phillips) for their contributions in the design and implementation of our eConsults program. We also thank additional team members Kurt McArthur and Neaktisia Lee for their assistance with generating reports, and Kathy LaPierre, Jennifer Rios, and Debra Webb Torres for their guidance with compliance and billing issues.
Corresponding author: Alpesh N. Amin, MD, MBA, University of California, Irvine, 101 The City Drive South, Building 26, Room 1000, ZC-4076H, Orange, CA 92868; anamin@uci.edu.
Financial disclosures: None.
1. County of Orange, Health Care Agency, Public Health Services. Orange County Health Profile 2013.
2. Coffman JM, Fix M Ko, M. California physician supply and distribution: headed for a drought? California Health Care Foundation, June 2018.
3. Spetz J, Coffman J, Geyn I. California’s primary care workforce: forecasted supply, demand, and pipeline of trainees, 2016-2030. Healthforce Center at the University of California, San Francisco, August 2017.
4. Gandhi TK, Sittig DF, Franklin M, et al. Communication breakdown in the outpatient referral process. J Gen Intern Med. 2000;15:626-631.
5. McPhee SJ, Lo B, Saika GY, Meltzer R. How good is communication between primary care physicians and subspecialty consultants? Arch Intern Med. 1984;144:1265-1268.
6. Mehrotra A, Forrest CB, Lin CY. Dropping the baton: specialty referrals in the United States. Milbank Q. 2011;89:39-68.
7. Wrenn K, Catschegn S, Cruz M, et al. Analysis of an electronic consultation program at an academic medical centre: Primary care provider questions, specialist responses, and primary care provider actions. J Telemed Telecare. 2017;23: 217-224.
8. Gleason N, Prasad PA, Ackerman S, et al. Adoption and impact of an eConsult system in a fee-for-service setting. Healthc (Amst). 2017;5(1-2):40-45.
9. Stoves J, Connolly J, Cheung CK, et al. Electronic consultation as an alternative to hospital referral for patients with chronic kidney disease: a novel application for networked electronic health records to improve the accessibility and efficiency of healthcare. Qual Saf Health Care. 2010;19: e54.
10. Datta SK, Warshaw EM, Edison KE, et al. Cost and utility analysis of a store-and-forward teledermatology referral system: a randomized clinical trial. JAMA Dermatol. 2015;151:1323-1329.
11. Liddy C, Drosinis P, Deri Armstrong C, et al. What are the cost savings associated with providing access to specialist care through the Champlain BASE eConsult service? A costing evaluation. BMJ Open. 2016;6:e010920.
12. Barnett ML, Yee HF Jr, Mehrotra A, Giboney P. Los Angeles safety-net program eConsult system was rapidly adopted and decreased wait times to see specialists. Health Aff. 2017;36:492-499.
13. Malagrino GD, Chaudhry R, Gardner M, et al. A study of 6,000 electronic specialty consultations for person-centered care at The Mayo Clinic. Int J Person Centered Med. 2012;2:458-466.
14. Keely E, Liddy C, Afkham A. Utilization, benefits, and impact of an e-consultation service across diverse specialties and primary care providers. Telemed J E Health. 2013;19:733-738.
15. Scherpbier-de Haan ND, van Gelder VA, Van Weel C, et al. Initial implementation of a web-based consultation process for patients with chronic kidney disease. Ann Fam Med. 2013;11:151-156.
16. Palen TE, Price D, Shetterly S, Wallace KB. Comparing virtual consults to traditional consults using an electronic health record: an observational case-control study. BMC Med Inform Decis Mak. 2012;12:65.
17. Liddy C, Afkham A, Drosinis P, et al. Impact of and satisfaction with a new eConsult service: a mixed methods study of primary care providers. J Am Board Fam Med. 2015;28:394-403.
18. Angstman KB, Adamson SC, Furst JW, et al. Provider satisfaction with virtual specialist consultations in a family medicine department. Health Care Manag (Frederick). 2009;28:14-18.
19. McAdams M, Cannavo L, Orlander JD. A medical specialty e-consult program in a VA health care system. Fed Pract. 2014; 31:26–31.
20. Keely E, Williams R, Epstein G, et al. Specialist perspectives on Ontario Provincial electronic consultation services. Telemed J E Health. 2019;25:3-10.
21. Kim-Hwang JE, Chen AH, Bell DS, et al. Evaluating electronic referrals for specialty care at a public hospital. J Gen Intern Med. 2010;25:1123-1128.
From the Department of Medicine, University of California, Irvine, Orange, CA.
Abstract
Background: Orange County’s residents have difficulty accessing timely, quality, affordable specialty care services. As the county’s only academic health system, the University of California, Irvine (UCI) aimed to improve specialty care access for the communities it serves by implementing an electronic consultations (eConsults) program that allows primary care providers (PCPs) to efficiently receive specialist recommendations on referral problems that do not require an in-person evaluation.
Objective: To implement an eConsults program at the UCI that enhances access to and the delivery of coordinated specialty care for lower-complexity referral problems.
Methods: We developed custom solutions to integrate eConsults into UCI’s 2 electronic health record platforms. The impact of the eConsults program was assessed by continuously evaluating usage and outcomes. Measures used to track usage included the number of submitted eConsult requests per PCP, the number of completed responses per specialty, and the response time for eConsult requests. Outcome measures included the specialist recommendation (eg, in-office visit, consultation avoided) and physician feedback.
Results: Over 4.5 years, more than 1400 successful eConsults have been completed, and the program has expanded to 17 specialties. The average turnaround time for an eConsult response across all specialties was 1 business day. Moreover, more than 50% of the eConsults received specialty responses within the same day of the eConsult request. Most important, about 80% of eConsult requests were addressed without the need for an in-office visit with a specialist.
Conclusion: The enhanced access to and the delivery of coordinated specialty care provided by eConsults resulted in improved efficiency and specialty access, while likely reducing costs and improving patient satisfaction. The improved communication and collaboration among providers with eConsults has also led to overwhelmingly positive feedback from both PCPs and specialists.
Keywords: electronic consultation; access to care; primary care; specialty referral; telehealth.
Orange County’s growing, aging, and diverse population is driving an increased demand for health care.1 But with the county’s high cost of living and worsening shortage of physicians,1-3 many of its residents are struggling to access timely, quality, affordable care. Access to specialty care services is especially frustrating for many patients and their providers, both primary care providers (PCPs) and specialists, due to problems with the referral process. Many patients experience increased wait times for a visit with a specialist due to poor communication between providers, insufficient guidance on the information or diagnostic results needed by specialists, and lack of care coordination.4-6 One promising approach to overcome these challenges is the use of an electronic consultation, or eConsult, in place of a standard in-person referral. An eConsult is an asynchronous, non-face-to-face, provider-to-provider exchange using a secure electronic communication platform. For appropriate referral problems, the patient is able to receive timely access to specialist expertise through electronic referral by their PCP,7-9 and avoid the time and costs associated with a visit to the specialist,10,11 such as travel, missed work, co-pays, and child-care expenses. Clinical questions addressed using an eConsult system subsequently free up office visit appointment slots, improving access for patients requiring in-office evaluation.8,12
Orange County’s only academic health system, the University of California, Irvine (UCI), serves a population of 3.5 million, and its principal priority is providing the communities in the county (which is the sixth largest in United States) and the surrounding region with the highest quality health care possible. Thus, UCI aimed to improve its referral processes and provide timely access to specialty care for its patients by implementing an eConsults program that allows PCPs to efficiently receive specialist recommendations on referral problems that do not require the specialist to evaluate the patient in person. This report describes our experiences with developing and implementing a custom-built eConsults workflow in UCI’s prior electronic health record (EHR) platform, Allscripts, and subsequently transitioning our mature eConsults program to a new EHR system when UCI adopted Epic. UCI is likely the only academic medical center to have experience in successfully implementing eConsults into 2 different EHR systems.
Setting
UCI’s medical center is a 417-bed acute care hospital providing tertiary and quaternary care, ambulatory and specialty medical clinics, behavioral health care, and rehabilitation services. It is located in Orange, CA, and serves a diverse population of 3.5 million persons with broad health care needs. With more than 400 specialty and primary care physicians, UCI offers a full scope of acute and general care services. It is also the primary teaching location for UCI medical and nursing students, medical residents, and fellows, and is home to Orange County’s only adult Level I and pediatric Level II trauma centers and the regional burn center.
eConsults Program
We designed the initial eConsults program within UCI’s Allscripts EHR platform. Our information technology (IT) build team developed unique “documents-based” eConsults workflows that simplified the process of initiating requests directly from the EHR and facilitated rapid responses from participating specialties. The requesting provider’s eConsults interface was user-friendly, and referring providers were able to initiate an eConsult easily by selecting the customized eConsult icon from the Allscripts main toolbar. To ensure that all relevant information is provided to the specialists, condition-specific templates are embedded in the requesting provider’s eConsults workflow that allow PCPs to enter a focused, patient-specific clinical question and provide guidance on recommended patient information (eg, health history, laboratory results, and digital images) that may help the specialist provide an informed response. The eConsult templates were adapted from standardized forms developed by partner University of California Health Systems in an initiative funded by the University of California Center for Health Quality and Innovation.
To facilitate timely responses from specialists, an innovative notification system was created in the responding provider’s eConsults workflow to automatically send an email to participating specialists when a new eConsult is requested. The responding provider’s workflow also includes an option for the specialist to decline the eConsult if the case is deemed too complex to be addressed electronically. For every completed eConsult that does not result in an in-person patient evaluation, the requesting provider and responding specialist each receives a modest reimbursement, which was initially paid by UCI Health System funds.
Implementation
The design and implementation of the eConsults program began in November 2014, and was guided by a steering committee that included the chair of the department of medicine, chief medical information officer, primary care and specialty physician leads, IT build team, and a project manager. Early on, members of this committee engaged UCI leadership to affirm support for the program and obtain the IT resources needed to build the eConsults workflow. Regular steering committee meetings were established to discuss the design of the workflow, adapt the clinical content of the referral templates, and develop a provider reimbursement plan. After completion of the workflow build, the eConsults system was tested to identify failure points and obtain feedback from users. Prior to going live, the eConsults program was publicized by members of the steering committee through meetings with primary care groups and email communications. Committee members also hosted in-person training and orientation sessions with PCPs and participating specialists, and distributed tip sheets summarizing the steps to complete the PCP and specialist eConsult workflows.
The eConsults workflow build, testing, and launch were completed within 5 months (April 2015; Figure 1). eConsults went live in the 3 initial specialties (endocrinology, cardiology, and rheumatology) that were interested in participating in the first wave of the program. UCI’s eConsults service has subsequently expanded to 17 total specialties (allergy, cardiology, dermatology, endocrinology, gastroenterology, geriatrics, gynecology, hematology, hepatology, infectious disease, nephrology, neurology, palliative care, psychiatry, pulmonary, rheumatology, and sports medicine).
Two and half years after the eConsults program was implemented in Allscripts, UCI adopted a new EHR platform, Epic. By this time, the eConsults service had grown into a mature program with greater numbers of PCP users and submitted eConsults (Figure 2). Using our experience with the Allscripts build, our IT team was able to efficiently transition the eConsults service to the new EHR system. In contrast to the “documents-based” eConsult workflows on Allscripts, our IT team utilized an “orders-based” strategy on Epic, which followed a more traditional approach to requesting a consultation. We re-launched the service in Epic within 3 months (February 2018). However, both platforms utilized user-friendly workflows to achieve similar goals, and the program has continued to grow with respect to the number of users and eConsults.
Measurement/Analysis
The impact of the program was assessed by continuously evaluating usage and outcomes. Measures used to track usage included the number of PCP users, the number of submitted eConsult requests per PCP, and the number of requests per specialty. The response time for eConsult requests and the self-reported amount of time spent by specialists on the response were also tracked. Outcome measures included the specialist recommendation (eg, in-office visit, consultation avoided) and physician feedback. Provider satisfaction was primarily obtained by soliciting feedback from individual eConsult users.
Implementation of this eConsults program constituted a quality improvement activity and did not require Institutional Review Board review.
Results
Since the program was launched in April 2015, more than 1400 eConsults have been completed across 17 specialties (Figure 3). There were 654 completed eConsults on the Allscripts platform, and 808 eConsults have been completed using the Epic platform to date. The busiest eConsult specialties were endocrinology (receiving 276, or 19%, of the eConsults requests), hematology (receiving 249 requests, or 17%), infectious disease (receiving 244 requests, or 17% ), and cardiology (receiving 148 requests, or 10%).
The self-reported amount of time specialists spent on the response was different between the 2 EHR systems (Figure 4). On Allscripts, specialists reported that 23% of eConsults took 10 minutes or less to complete, 47% took 11 to 20 minutes, 23% took 21 to 30 minutes, and 7% took more than 30 minutes. On Epic, specialists reported that 42% of eConsults took 10 minutes or less to complete, 44% took 11 to 20 minutes, 12% took 21 to 30 minutes, and 2% took more than 30 minutes. This difference in time spent fielding eConsults likely represents the subtle nuances between Allscripts’ “documents-based” and Epic’s “orders-based” workflows.
As a result of the automated notification system that was introduced early in the eConsults implementation process on Allscripts, the specialty response times were much faster than the expected 3 business days’ turnaround goal instituted by the Center for Health Quality and Innovation initiative, regardless of the EHR platform used. In fact, the average turnaround time for an eConsult response across all specialties was 1 business day, which was similar for both EHR systems (Figure 5). Furthermore, more than 50% of the eConsults on both EHR systems received specialist responses within the same day of the eConsult request (63% on Allscripts, 54% on Epic). There was a small decrease in the percentage of same-day responses when we transitioned to Epic, likely because the functionality of an automated notification email could not be restored in Epic. Regardless, the specialty response times on Epic remained expeditious, likely because the automated notifications on Allscripts instilled good practices for the specialists, and regularly checking for new eConsult requests became an ingrained behavior.
Our most important finding was that approximately 80% of eConsult requests were addressed without the need for an in-office visit with a specialist. This measure was similar for both EHR platforms (83% on Allscripts and 78% on Epic).
Provider feedback has been overwhelmingly positive. PCPs are impressed with the robust educational content of the eConsult responses, since the goal for specialists is to justify their recommendations. Specialists appreciate the convenience and efficiency that eConsults offer, as well as the improved communication and collaboration among physicians. eConsults have been especially beneficial to PCPs at UCI’s Family Health Centers, who are now able to receive subspecialty consultations from UCI specialists despite insurance barriers.
Discussion
Our eConsults program uniquely contrasts with other programs because UCI is likely the only academic medical center to have experience in successfully incorporating eConsults into 2 different EHR systems: initial development of the eConsults workflow in UCI’s existing Allscripts EHR platform, and subsequently transitioning a mature eConsults program to a new EHR system when the institution adopted Epic.
We measured the impact of the eConsults program on access to care by the response time for eConsult requests and the percentage of eConsults that averted an in-office visit with a specialist. We found that the eConsults program at UCI provided our PCPs access to specialist consultations in a timely manner, with much shorter response times than standard in-person referrals. The average turnaround time for an eConsult response we reported is consistent with findings from other studies.12-15 Additionally, our program was able to address about 80% of its eConsults electronically, helping to reduce unnecessary in-person specialist referrals. In the literature, the percentage of eConsults that avoided an in-person specialist visit varies widely.8,12-16
We reported very positive feedback from both PCPs and specialists on UCI’s eConsults service. Similarly, other studies described PCP satisfaction with their respective eConsults programs to be uniformly high,8,9,13,14,17-19 though some reported that the level of satisfaction among specialists was more varied.18-21
Lessons Learned
The successful design and implementation of our eConsults program began with assembling the right clinical champions and technology partners for our steering committee. Establishing regular steering committee meetings helped maintain an appropriate timeline for completion of different aspects of the project. Engaging support from UCI’s leadership also provided us with a dedicated IT team that helped us with the build, training resources, troubleshooting issues, and reporting for the project.
Our experience with implementing the eConsults program on 2 different EHR systems highlighted the importance of creating efficient, user-friendly workflows to foster provider adoption and achieve sustainability. Allscripts’ open platform gave our IT team the ability to create a homegrown solution to implementing an eConsult model that was simple and easy to use. The Epic platform’s interoperability allowed us to leverage our learnings from the Allscripts build to efficiently implement eConsults in Epic.
We also found that providing modest incentive payments or reimbursements to both PCPs and specialists for each completed eConsult helps with both adoption and program sustainability. Initially, credit for the eConsult work was paid by internal UCI Health System funds. Two payers, UC Care (a preferred provider organization plan created just for the University of California) and more recently, the Centers for Medicare & Medicaid Services, have agreed to reimburse for outpatient eConsults. Securing additional payers for reimbursement of the eConsult service will not only ensure the program’s long-term sustainability, but also represents an acknowledgment of the value of eConsults in supporting access to care.
Applicability
Other health care settings that are experiencing issues with specialty care access can successfully implement their own eConsults program by employing strategies similar to those described in this report—assembling the right team, creating user-friendly workflows, and providing incentives. Our advice for successful implementation is to clearly communicate your goals to all involved, including primary care, specialists, leadership, and IT partners, and establish with these stakeholders the appropriate support and resources needed to facilitate the development of the program and overcome any barriers to adoption.
Current Status and Future Directions
Our future plans include continuing to optimize the Epic eConsult backend build and workflows using our experience in Allscripts. We have implemented eConsult workflows for use by graduate medical education trainees and advanced practice providers, with attending supervision. Further work is in progress to optimize these workflows, which will allow for appropriate education and supervision without delaying care. Furthermore, we plan to expand the program to include inpatient-to-inpatient and emergency department-to-inpatient eConsults. We will continue to expand the eConsults program by offering additional specialties, engage providers to encourage ongoing participation, and maximize PCP use by continuing to market the program through regular newsletters and email communications. Finally, the eConsults has served as an effective, important resource in the current era of COVID-19 in several ways: it allows for optimization of specialty input in patient care delivery without subjecting more health care workers to unnecessary exposure; saves on utilization of precious personal protective equipment; and enhances our ability to deal with a potential surge by providing access to specialists remotely and electronically all hours of the day, thus expanding care to the evening and weekend hours.
Acknowledgment: The authors thank our steering committee members (Dr. Ralph Cygan, Dr. Andrew Reikes, Dr. Byron Allen, Dr. George Lawry) and IT build team (Lori Bocchicchio, Meghan van Witsen, Jaymee Zillgitt, Tanya Sickles, Dennis Hoang, Jeanette Lisak-Phillips) for their contributions in the design and implementation of our eConsults program. We also thank additional team members Kurt McArthur and Neaktisia Lee for their assistance with generating reports, and Kathy LaPierre, Jennifer Rios, and Debra Webb Torres for their guidance with compliance and billing issues.
Corresponding author: Alpesh N. Amin, MD, MBA, University of California, Irvine, 101 The City Drive South, Building 26, Room 1000, ZC-4076H, Orange, CA 92868; anamin@uci.edu.
Financial disclosures: None.
From the Department of Medicine, University of California, Irvine, Orange, CA.
Abstract
Background: Orange County’s residents have difficulty accessing timely, quality, affordable specialty care services. As the county’s only academic health system, the University of California, Irvine (UCI) aimed to improve specialty care access for the communities it serves by implementing an electronic consultations (eConsults) program that allows primary care providers (PCPs) to efficiently receive specialist recommendations on referral problems that do not require an in-person evaluation.
Objective: To implement an eConsults program at the UCI that enhances access to and the delivery of coordinated specialty care for lower-complexity referral problems.
Methods: We developed custom solutions to integrate eConsults into UCI’s 2 electronic health record platforms. The impact of the eConsults program was assessed by continuously evaluating usage and outcomes. Measures used to track usage included the number of submitted eConsult requests per PCP, the number of completed responses per specialty, and the response time for eConsult requests. Outcome measures included the specialist recommendation (eg, in-office visit, consultation avoided) and physician feedback.
Results: Over 4.5 years, more than 1400 successful eConsults have been completed, and the program has expanded to 17 specialties. The average turnaround time for an eConsult response across all specialties was 1 business day. Moreover, more than 50% of the eConsults received specialty responses within the same day of the eConsult request. Most important, about 80% of eConsult requests were addressed without the need for an in-office visit with a specialist.
Conclusion: The enhanced access to and the delivery of coordinated specialty care provided by eConsults resulted in improved efficiency and specialty access, while likely reducing costs and improving patient satisfaction. The improved communication and collaboration among providers with eConsults has also led to overwhelmingly positive feedback from both PCPs and specialists.
Keywords: electronic consultation; access to care; primary care; specialty referral; telehealth.
Orange County’s growing, aging, and diverse population is driving an increased demand for health care.1 But with the county’s high cost of living and worsening shortage of physicians,1-3 many of its residents are struggling to access timely, quality, affordable care. Access to specialty care services is especially frustrating for many patients and their providers, both primary care providers (PCPs) and specialists, due to problems with the referral process. Many patients experience increased wait times for a visit with a specialist due to poor communication between providers, insufficient guidance on the information or diagnostic results needed by specialists, and lack of care coordination.4-6 One promising approach to overcome these challenges is the use of an electronic consultation, or eConsult, in place of a standard in-person referral. An eConsult is an asynchronous, non-face-to-face, provider-to-provider exchange using a secure electronic communication platform. For appropriate referral problems, the patient is able to receive timely access to specialist expertise through electronic referral by their PCP,7-9 and avoid the time and costs associated with a visit to the specialist,10,11 such as travel, missed work, co-pays, and child-care expenses. Clinical questions addressed using an eConsult system subsequently free up office visit appointment slots, improving access for patients requiring in-office evaluation.8,12
Orange County’s only academic health system, the University of California, Irvine (UCI), serves a population of 3.5 million, and its principal priority is providing the communities in the county (which is the sixth largest in United States) and the surrounding region with the highest quality health care possible. Thus, UCI aimed to improve its referral processes and provide timely access to specialty care for its patients by implementing an eConsults program that allows PCPs to efficiently receive specialist recommendations on referral problems that do not require the specialist to evaluate the patient in person. This report describes our experiences with developing and implementing a custom-built eConsults workflow in UCI’s prior electronic health record (EHR) platform, Allscripts, and subsequently transitioning our mature eConsults program to a new EHR system when UCI adopted Epic. UCI is likely the only academic medical center to have experience in successfully implementing eConsults into 2 different EHR systems.
Setting
UCI’s medical center is a 417-bed acute care hospital providing tertiary and quaternary care, ambulatory and specialty medical clinics, behavioral health care, and rehabilitation services. It is located in Orange, CA, and serves a diverse population of 3.5 million persons with broad health care needs. With more than 400 specialty and primary care physicians, UCI offers a full scope of acute and general care services. It is also the primary teaching location for UCI medical and nursing students, medical residents, and fellows, and is home to Orange County’s only adult Level I and pediatric Level II trauma centers and the regional burn center.
eConsults Program
We designed the initial eConsults program within UCI’s Allscripts EHR platform. Our information technology (IT) build team developed unique “documents-based” eConsults workflows that simplified the process of initiating requests directly from the EHR and facilitated rapid responses from participating specialties. The requesting provider’s eConsults interface was user-friendly, and referring providers were able to initiate an eConsult easily by selecting the customized eConsult icon from the Allscripts main toolbar. To ensure that all relevant information is provided to the specialists, condition-specific templates are embedded in the requesting provider’s eConsults workflow that allow PCPs to enter a focused, patient-specific clinical question and provide guidance on recommended patient information (eg, health history, laboratory results, and digital images) that may help the specialist provide an informed response. The eConsult templates were adapted from standardized forms developed by partner University of California Health Systems in an initiative funded by the University of California Center for Health Quality and Innovation.
To facilitate timely responses from specialists, an innovative notification system was created in the responding provider’s eConsults workflow to automatically send an email to participating specialists when a new eConsult is requested. The responding provider’s workflow also includes an option for the specialist to decline the eConsult if the case is deemed too complex to be addressed electronically. For every completed eConsult that does not result in an in-person patient evaluation, the requesting provider and responding specialist each receives a modest reimbursement, which was initially paid by UCI Health System funds.
Implementation
The design and implementation of the eConsults program began in November 2014, and was guided by a steering committee that included the chair of the department of medicine, chief medical information officer, primary care and specialty physician leads, IT build team, and a project manager. Early on, members of this committee engaged UCI leadership to affirm support for the program and obtain the IT resources needed to build the eConsults workflow. Regular steering committee meetings were established to discuss the design of the workflow, adapt the clinical content of the referral templates, and develop a provider reimbursement plan. After completion of the workflow build, the eConsults system was tested to identify failure points and obtain feedback from users. Prior to going live, the eConsults program was publicized by members of the steering committee through meetings with primary care groups and email communications. Committee members also hosted in-person training and orientation sessions with PCPs and participating specialists, and distributed tip sheets summarizing the steps to complete the PCP and specialist eConsult workflows.
The eConsults workflow build, testing, and launch were completed within 5 months (April 2015; Figure 1). eConsults went live in the 3 initial specialties (endocrinology, cardiology, and rheumatology) that were interested in participating in the first wave of the program. UCI’s eConsults service has subsequently expanded to 17 total specialties (allergy, cardiology, dermatology, endocrinology, gastroenterology, geriatrics, gynecology, hematology, hepatology, infectious disease, nephrology, neurology, palliative care, psychiatry, pulmonary, rheumatology, and sports medicine).
Two and half years after the eConsults program was implemented in Allscripts, UCI adopted a new EHR platform, Epic. By this time, the eConsults service had grown into a mature program with greater numbers of PCP users and submitted eConsults (Figure 2). Using our experience with the Allscripts build, our IT team was able to efficiently transition the eConsults service to the new EHR system. In contrast to the “documents-based” eConsult workflows on Allscripts, our IT team utilized an “orders-based” strategy on Epic, which followed a more traditional approach to requesting a consultation. We re-launched the service in Epic within 3 months (February 2018). However, both platforms utilized user-friendly workflows to achieve similar goals, and the program has continued to grow with respect to the number of users and eConsults.
Measurement/Analysis
The impact of the program was assessed by continuously evaluating usage and outcomes. Measures used to track usage included the number of PCP users, the number of submitted eConsult requests per PCP, and the number of requests per specialty. The response time for eConsult requests and the self-reported amount of time spent by specialists on the response were also tracked. Outcome measures included the specialist recommendation (eg, in-office visit, consultation avoided) and physician feedback. Provider satisfaction was primarily obtained by soliciting feedback from individual eConsult users.
Implementation of this eConsults program constituted a quality improvement activity and did not require Institutional Review Board review.
Results
Since the program was launched in April 2015, more than 1400 eConsults have been completed across 17 specialties (Figure 3). There were 654 completed eConsults on the Allscripts platform, and 808 eConsults have been completed using the Epic platform to date. The busiest eConsult specialties were endocrinology (receiving 276, or 19%, of the eConsults requests), hematology (receiving 249 requests, or 17%), infectious disease (receiving 244 requests, or 17% ), and cardiology (receiving 148 requests, or 10%).
The self-reported amount of time specialists spent on the response was different between the 2 EHR systems (Figure 4). On Allscripts, specialists reported that 23% of eConsults took 10 minutes or less to complete, 47% took 11 to 20 minutes, 23% took 21 to 30 minutes, and 7% took more than 30 minutes. On Epic, specialists reported that 42% of eConsults took 10 minutes or less to complete, 44% took 11 to 20 minutes, 12% took 21 to 30 minutes, and 2% took more than 30 minutes. This difference in time spent fielding eConsults likely represents the subtle nuances between Allscripts’ “documents-based” and Epic’s “orders-based” workflows.
As a result of the automated notification system that was introduced early in the eConsults implementation process on Allscripts, the specialty response times were much faster than the expected 3 business days’ turnaround goal instituted by the Center for Health Quality and Innovation initiative, regardless of the EHR platform used. In fact, the average turnaround time for an eConsult response across all specialties was 1 business day, which was similar for both EHR systems (Figure 5). Furthermore, more than 50% of the eConsults on both EHR systems received specialist responses within the same day of the eConsult request (63% on Allscripts, 54% on Epic). There was a small decrease in the percentage of same-day responses when we transitioned to Epic, likely because the functionality of an automated notification email could not be restored in Epic. Regardless, the specialty response times on Epic remained expeditious, likely because the automated notifications on Allscripts instilled good practices for the specialists, and regularly checking for new eConsult requests became an ingrained behavior.
Our most important finding was that approximately 80% of eConsult requests were addressed without the need for an in-office visit with a specialist. This measure was similar for both EHR platforms (83% on Allscripts and 78% on Epic).
Provider feedback has been overwhelmingly positive. PCPs are impressed with the robust educational content of the eConsult responses, since the goal for specialists is to justify their recommendations. Specialists appreciate the convenience and efficiency that eConsults offer, as well as the improved communication and collaboration among physicians. eConsults have been especially beneficial to PCPs at UCI’s Family Health Centers, who are now able to receive subspecialty consultations from UCI specialists despite insurance barriers.
Discussion
Our eConsults program uniquely contrasts with other programs because UCI is likely the only academic medical center to have experience in successfully incorporating eConsults into 2 different EHR systems: initial development of the eConsults workflow in UCI’s existing Allscripts EHR platform, and subsequently transitioning a mature eConsults program to a new EHR system when the institution adopted Epic.
We measured the impact of the eConsults program on access to care by the response time for eConsult requests and the percentage of eConsults that averted an in-office visit with a specialist. We found that the eConsults program at UCI provided our PCPs access to specialist consultations in a timely manner, with much shorter response times than standard in-person referrals. The average turnaround time for an eConsult response we reported is consistent with findings from other studies.12-15 Additionally, our program was able to address about 80% of its eConsults electronically, helping to reduce unnecessary in-person specialist referrals. In the literature, the percentage of eConsults that avoided an in-person specialist visit varies widely.8,12-16
We reported very positive feedback from both PCPs and specialists on UCI’s eConsults service. Similarly, other studies described PCP satisfaction with their respective eConsults programs to be uniformly high,8,9,13,14,17-19 though some reported that the level of satisfaction among specialists was more varied.18-21
Lessons Learned
The successful design and implementation of our eConsults program began with assembling the right clinical champions and technology partners for our steering committee. Establishing regular steering committee meetings helped maintain an appropriate timeline for completion of different aspects of the project. Engaging support from UCI’s leadership also provided us with a dedicated IT team that helped us with the build, training resources, troubleshooting issues, and reporting for the project.
Our experience with implementing the eConsults program on 2 different EHR systems highlighted the importance of creating efficient, user-friendly workflows to foster provider adoption and achieve sustainability. Allscripts’ open platform gave our IT team the ability to create a homegrown solution to implementing an eConsult model that was simple and easy to use. The Epic platform’s interoperability allowed us to leverage our learnings from the Allscripts build to efficiently implement eConsults in Epic.
We also found that providing modest incentive payments or reimbursements to both PCPs and specialists for each completed eConsult helps with both adoption and program sustainability. Initially, credit for the eConsult work was paid by internal UCI Health System funds. Two payers, UC Care (a preferred provider organization plan created just for the University of California) and more recently, the Centers for Medicare & Medicaid Services, have agreed to reimburse for outpatient eConsults. Securing additional payers for reimbursement of the eConsult service will not only ensure the program’s long-term sustainability, but also represents an acknowledgment of the value of eConsults in supporting access to care.
Applicability
Other health care settings that are experiencing issues with specialty care access can successfully implement their own eConsults program by employing strategies similar to those described in this report—assembling the right team, creating user-friendly workflows, and providing incentives. Our advice for successful implementation is to clearly communicate your goals to all involved, including primary care, specialists, leadership, and IT partners, and establish with these stakeholders the appropriate support and resources needed to facilitate the development of the program and overcome any barriers to adoption.
Current Status and Future Directions
Our future plans include continuing to optimize the Epic eConsult backend build and workflows using our experience in Allscripts. We have implemented eConsult workflows for use by graduate medical education trainees and advanced practice providers, with attending supervision. Further work is in progress to optimize these workflows, which will allow for appropriate education and supervision without delaying care. Furthermore, we plan to expand the program to include inpatient-to-inpatient and emergency department-to-inpatient eConsults. We will continue to expand the eConsults program by offering additional specialties, engage providers to encourage ongoing participation, and maximize PCP use by continuing to market the program through regular newsletters and email communications. Finally, the eConsults has served as an effective, important resource in the current era of COVID-19 in several ways: it allows for optimization of specialty input in patient care delivery without subjecting more health care workers to unnecessary exposure; saves on utilization of precious personal protective equipment; and enhances our ability to deal with a potential surge by providing access to specialists remotely and electronically all hours of the day, thus expanding care to the evening and weekend hours.
Acknowledgment: The authors thank our steering committee members (Dr. Ralph Cygan, Dr. Andrew Reikes, Dr. Byron Allen, Dr. George Lawry) and IT build team (Lori Bocchicchio, Meghan van Witsen, Jaymee Zillgitt, Tanya Sickles, Dennis Hoang, Jeanette Lisak-Phillips) for their contributions in the design and implementation of our eConsults program. We also thank additional team members Kurt McArthur and Neaktisia Lee for their assistance with generating reports, and Kathy LaPierre, Jennifer Rios, and Debra Webb Torres for their guidance with compliance and billing issues.
Corresponding author: Alpesh N. Amin, MD, MBA, University of California, Irvine, 101 The City Drive South, Building 26, Room 1000, ZC-4076H, Orange, CA 92868; anamin@uci.edu.
Financial disclosures: None.
1. County of Orange, Health Care Agency, Public Health Services. Orange County Health Profile 2013.
2. Coffman JM, Fix M Ko, M. California physician supply and distribution: headed for a drought? California Health Care Foundation, June 2018.
3. Spetz J, Coffman J, Geyn I. California’s primary care workforce: forecasted supply, demand, and pipeline of trainees, 2016-2030. Healthforce Center at the University of California, San Francisco, August 2017.
4. Gandhi TK, Sittig DF, Franklin M, et al. Communication breakdown in the outpatient referral process. J Gen Intern Med. 2000;15:626-631.
5. McPhee SJ, Lo B, Saika GY, Meltzer R. How good is communication between primary care physicians and subspecialty consultants? Arch Intern Med. 1984;144:1265-1268.
6. Mehrotra A, Forrest CB, Lin CY. Dropping the baton: specialty referrals in the United States. Milbank Q. 2011;89:39-68.
7. Wrenn K, Catschegn S, Cruz M, et al. Analysis of an electronic consultation program at an academic medical centre: Primary care provider questions, specialist responses, and primary care provider actions. J Telemed Telecare. 2017;23: 217-224.
8. Gleason N, Prasad PA, Ackerman S, et al. Adoption and impact of an eConsult system in a fee-for-service setting. Healthc (Amst). 2017;5(1-2):40-45.
9. Stoves J, Connolly J, Cheung CK, et al. Electronic consultation as an alternative to hospital referral for patients with chronic kidney disease: a novel application for networked electronic health records to improve the accessibility and efficiency of healthcare. Qual Saf Health Care. 2010;19: e54.
10. Datta SK, Warshaw EM, Edison KE, et al. Cost and utility analysis of a store-and-forward teledermatology referral system: a randomized clinical trial. JAMA Dermatol. 2015;151:1323-1329.
11. Liddy C, Drosinis P, Deri Armstrong C, et al. What are the cost savings associated with providing access to specialist care through the Champlain BASE eConsult service? A costing evaluation. BMJ Open. 2016;6:e010920.
12. Barnett ML, Yee HF Jr, Mehrotra A, Giboney P. Los Angeles safety-net program eConsult system was rapidly adopted and decreased wait times to see specialists. Health Aff. 2017;36:492-499.
13. Malagrino GD, Chaudhry R, Gardner M, et al. A study of 6,000 electronic specialty consultations for person-centered care at The Mayo Clinic. Int J Person Centered Med. 2012;2:458-466.
14. Keely E, Liddy C, Afkham A. Utilization, benefits, and impact of an e-consultation service across diverse specialties and primary care providers. Telemed J E Health. 2013;19:733-738.
15. Scherpbier-de Haan ND, van Gelder VA, Van Weel C, et al. Initial implementation of a web-based consultation process for patients with chronic kidney disease. Ann Fam Med. 2013;11:151-156.
16. Palen TE, Price D, Shetterly S, Wallace KB. Comparing virtual consults to traditional consults using an electronic health record: an observational case-control study. BMC Med Inform Decis Mak. 2012;12:65.
17. Liddy C, Afkham A, Drosinis P, et al. Impact of and satisfaction with a new eConsult service: a mixed methods study of primary care providers. J Am Board Fam Med. 2015;28:394-403.
18. Angstman KB, Adamson SC, Furst JW, et al. Provider satisfaction with virtual specialist consultations in a family medicine department. Health Care Manag (Frederick). 2009;28:14-18.
19. McAdams M, Cannavo L, Orlander JD. A medical specialty e-consult program in a VA health care system. Fed Pract. 2014; 31:26–31.
20. Keely E, Williams R, Epstein G, et al. Specialist perspectives on Ontario Provincial electronic consultation services. Telemed J E Health. 2019;25:3-10.
21. Kim-Hwang JE, Chen AH, Bell DS, et al. Evaluating electronic referrals for specialty care at a public hospital. J Gen Intern Med. 2010;25:1123-1128.
1. County of Orange, Health Care Agency, Public Health Services. Orange County Health Profile 2013.
2. Coffman JM, Fix M Ko, M. California physician supply and distribution: headed for a drought? California Health Care Foundation, June 2018.
3. Spetz J, Coffman J, Geyn I. California’s primary care workforce: forecasted supply, demand, and pipeline of trainees, 2016-2030. Healthforce Center at the University of California, San Francisco, August 2017.
4. Gandhi TK, Sittig DF, Franklin M, et al. Communication breakdown in the outpatient referral process. J Gen Intern Med. 2000;15:626-631.
5. McPhee SJ, Lo B, Saika GY, Meltzer R. How good is communication between primary care physicians and subspecialty consultants? Arch Intern Med. 1984;144:1265-1268.
6. Mehrotra A, Forrest CB, Lin CY. Dropping the baton: specialty referrals in the United States. Milbank Q. 2011;89:39-68.
7. Wrenn K, Catschegn S, Cruz M, et al. Analysis of an electronic consultation program at an academic medical centre: Primary care provider questions, specialist responses, and primary care provider actions. J Telemed Telecare. 2017;23: 217-224.
8. Gleason N, Prasad PA, Ackerman S, et al. Adoption and impact of an eConsult system in a fee-for-service setting. Healthc (Amst). 2017;5(1-2):40-45.
9. Stoves J, Connolly J, Cheung CK, et al. Electronic consultation as an alternative to hospital referral for patients with chronic kidney disease: a novel application for networked electronic health records to improve the accessibility and efficiency of healthcare. Qual Saf Health Care. 2010;19: e54.
10. Datta SK, Warshaw EM, Edison KE, et al. Cost and utility analysis of a store-and-forward teledermatology referral system: a randomized clinical trial. JAMA Dermatol. 2015;151:1323-1329.
11. Liddy C, Drosinis P, Deri Armstrong C, et al. What are the cost savings associated with providing access to specialist care through the Champlain BASE eConsult service? A costing evaluation. BMJ Open. 2016;6:e010920.
12. Barnett ML, Yee HF Jr, Mehrotra A, Giboney P. Los Angeles safety-net program eConsult system was rapidly adopted and decreased wait times to see specialists. Health Aff. 2017;36:492-499.
13. Malagrino GD, Chaudhry R, Gardner M, et al. A study of 6,000 electronic specialty consultations for person-centered care at The Mayo Clinic. Int J Person Centered Med. 2012;2:458-466.
14. Keely E, Liddy C, Afkham A. Utilization, benefits, and impact of an e-consultation service across diverse specialties and primary care providers. Telemed J E Health. 2013;19:733-738.
15. Scherpbier-de Haan ND, van Gelder VA, Van Weel C, et al. Initial implementation of a web-based consultation process for patients with chronic kidney disease. Ann Fam Med. 2013;11:151-156.
16. Palen TE, Price D, Shetterly S, Wallace KB. Comparing virtual consults to traditional consults using an electronic health record: an observational case-control study. BMC Med Inform Decis Mak. 2012;12:65.
17. Liddy C, Afkham A, Drosinis P, et al. Impact of and satisfaction with a new eConsult service: a mixed methods study of primary care providers. J Am Board Fam Med. 2015;28:394-403.
18. Angstman KB, Adamson SC, Furst JW, et al. Provider satisfaction with virtual specialist consultations in a family medicine department. Health Care Manag (Frederick). 2009;28:14-18.
19. McAdams M, Cannavo L, Orlander JD. A medical specialty e-consult program in a VA health care system. Fed Pract. 2014; 31:26–31.
20. Keely E, Williams R, Epstein G, et al. Specialist perspectives on Ontario Provincial electronic consultation services. Telemed J E Health. 2019;25:3-10.
21. Kim-Hwang JE, Chen AH, Bell DS, et al. Evaluating electronic referrals for specialty care at a public hospital. J Gen Intern Med. 2010;25:1123-1128.
Use of an Electronic Alert Tool to Prevent Readmissions Following Coronary Artery Bypass Graft Surgery
From the University of North Carolina at Wilmington School of Nursing (Dr. Smith and Dr. Turrise), the New Hanover Regional Medical Center Heart Center (Mr. Jordan), the Coastal Carolinas Health Alliance and Coastal Connect Health Information Exchange (Ms. Robertson), and Coastal Thoracic Surgical Associates (Dr. Kane), Wilmington, NC.
Abstract
Objective: Cardiothoracic (CT) surgeons at our medical center were not receiving timely notification when their coronary artery bypass graft (CABG) surgery patients were admitted to the medical center or to other hospitals. The CT surgical team worked with a health alliance in southeastern North Carolina to implement health information exchange (HIE) real-time electronic notifications for their CABG patients who presented to the hospital’s emergency department (ED) or any ED affiliated with the medical center. The alert tool notifies team members about patient encounters, driving timely clinical engagement.
Methods: The CT team provided the HIE team with the names of CABG surgery patients, which were loaded into the alert tool. When a patient on the list presented to the hospital ED or its affiliates, the alert tool sent a real-time electronic notification to the Cardiac Surgical Services nurse coordinator. This intervention prompted the assessment and disposition of CABG patients, while in the ED, by the CT surgical team.
Results: Over a 16-month period (September 2017-December 2018), the names of 614 post-CABG patients were input into the HIE for tracking. Of these patients, 47 were treated and discharged from the ED; 31 were admitted for observation; 44 were readmitted for inpatient care; and 492 did not have a qualifying event requiring a notification alert. Following implementation of this practice change, the 30-day readmission rate for patients who underwent CABG at our institution decreased from 10% to 7.2%.
Conclusion: Utilizing a real-time alert tool resulted in immediate notification of the CT team when 1 of their patients presented to the ED. This afforded the CT surgical team an opportunity to intervene in the care of their patients, which in turn led to improved quality of care, physician communication and collaboration, and patient outcomes, such as preventable 30-day readmissions.
Keywords: electronic health record; real-time electronic notification; CABG; process improvement.
Unplanned 30-day hospital readmissions of patients who have undergone coronary artery bypass graft (CABG) surgery contribute to higher overall health care costs. CABG is 1 of the conditions/procedures that the Centers for Medicare and Medicaid Services (CMS) monitors for excess readmissions.1 Readmission rates for CABG-related conditions at 30 days post-surgery are reported to be between 16% and 20% for US hospitals.2 Readmissions are not only financially costly, but also have been associated with worse patient outcomes and decreased patient satisfaction.3 Common diagnoses for post-CABG admission include atrial fibrillation, pleural effusion, and wound infection.
The facility where this project was implemented had a 10% post-CABG admission rate for patients across all payers. While this rate is below the national average of 13.2%, the cardiothoracic (CT) surgical team was not being notified in a timely manner when their post-CABG patients were readmitted. The Lean team used the A3 problem-solving process to develop strategies that would reduce these readmissions and improve the care of their patients.
We explored the use of electronic alerts in managing post-CABG patients by conducting a literature search using the terms electronic alerts in patient care, patient engagement in the emergency department, electronic alerts in CABG, real-time notifications to prevent readmission, and CABG readmission. Databases searched were PubMed, Google Scholar, Cumulative Index of Nursing and Allied Health Literature, ProQuest, and ScienceDirect. This search resulted in studies focused on the use of electronic health record (EHR) alerts as a clinical decision-support tool; for example, patient demographic and assessment data are entered into the EHR, and the clinician is prompted with “performance” recommendations (eg, consider electrocardiogram and aspirin).4 In a paper by Engelman and Benjamin,5 the authors discuss the importance of the engaged physician and note that, in their emergency department (ED), an electronic notification is sent when a postoperative patient presents; however, the notification goes to the inpatient service for timely review and disposition. There was no literature that discussed the use of an electronic alert tool as a real-time patient engagement strategy that resulted in a practice change specific to the CT surgical team.
Our process improvement project focused on alerting the CT surgical team when a post-CABG patient presented to the ED, allowing them to evaluate the patient in real time and determine whether the chief complaint was related to the CABG and whether further evaluation by the CT surgeon was required. Specifically, we wanted to determine whether a real-time electronic alert that notified the CT surgical team about post-op CABG patients presenting to the ED would result in timely patient engagement, avoidance of readmissions, and an enhanced patient experience. During this project, alerts were sent to the CT surgical team notifying them of a post-CABG patient presenting to the ED or being directly admitted from home on physician orders, a provider’s office, or inpatient rehabilitation; however, the focus of this article is specifically on the notification regarding post-CABG patients presenting to the ED.
Prior to implementing the electronic notification project, the team developed and implemented several internal and external readmission reduction and prevention strategies for CABG patients. An in-house strategy involved a process whereby patients would receive their discharge medications prior to being discharged from the hospital post-CABG, thereby avoiding potential delays in the patient obtaining medications. When examining post-CABG patient readmissions, the primary conditions that led to readmission were fluid overload, pleural effusion, and atrial fibrillation. As such, a second in-house strategy was developed for post-CABG patients presenting to the ED with atrial fibrillation. The newly established protocol allowed patients to be monitored and treated in the cardiac observation unit. In addition, external strategies, including an outpatient furosemide protocol for home health nurses and an outpatient thoracentesis program and order set, were established (eg, for patients with congestive heart failure, shortness of breath).
Methods
Setting
The regional medical center where this project was implemented is the ninth largest hospital in North Carolina and the largest county-owned public hospital in the state. It is a tertiary care center and teaching hospital with 3 hospital campuses and 855 licensed beds. The medical center was included in the 100 Safecare Hospitals list by the Safecare Group; received a grade “A” Hospital Safety Score from the Leapfrog Group; and is 1 of America’s Top 100 Hospitals for Patient Experience.
Real-Time Notification Project
A regional hospital alliance in southeastern North Carolina established a health information exchange (HIE) with its member hospitals and office-based physicians to enable electronic exchange of patient information to improve quality, safety, and efficiency in health care delivery. Our medical center is part of this alliance. The HIE is a digital platform that facilitates the sharing of information between disparate connected EHR systems, and offers a portal for practices and hospitals to access patient information across North Carolina, South Carolina (via SC HIE), and nationwide (select dialysis centers). More specifically, approved providers and team members are able to access, in real time, patient-care encounter documents from other care settings (eg, acute, post-acute, ambulatory) via the HIE. Additionally, approved care entities can query-retrieve web portal information to support patient outcome improvement strategies. A partnership discussion highlighted the opportunity to utilize the HIE’s capabilities, such as real-time notification, to facilitate workflow (eg, when a patient presents to the ED, the HIE can provide access to health information at the point of care). In this capacity, the alert tool notifies care team members about patient encounters to drive timely clinical engagement for care transitions.
In January 2017, we began discussions on using the HIE to facilitate real-time electronic tracking in the Cardiac Surgical Services department at our medical center. Persons involved in these discussions included the cardiovascular (CV) team (comprised of case managers, department managers and coordinators, program coordinators, administrators, and support services [eg, pre-admission testing and home health staff]) and CT surgeons. At that time, CABG readmissions were manually tracked, and the real-time notification tool was being used in other departments (eg, in case management for tracking readmissions). The entire team was part of the initial decision meeting to pursue this possibility. The CV team reached consensus in June 2017 and proposed extending the use of the alert tool to the post-CABG population presenting to the ED (or any ED affiliated with the medical center) or admitted directly to the medical center.
The HIE staff met with the Cardiac Surgical Services team to tailor and develop the logistics of the project, such as who would be notified and how. The goals of the project were to support appropriate care intervention, reduce preventable hospital readmissions, and improve quality of care through enhanced provider communication and engagement. To achieve these goals, on the day of discharge the Cardiac Surgical Services coordinator provided the HIE team with the names of patients who had undergone CABG surgery. This patient list was loaded into the alert tool and continually updated. At 31 days, patient names were removed from the list. When a patient on the list presented to the hospital ED, the alert tool sent 2 real-time electronic notifications, an email and a text message, to the Cardiac Surgical Services coordinator, noting that a patient event occurred. Personal information was not included in the alert in order to protect patient information and comply with Health Insurance Portability and Accountability Act regulations.
The alert prompted the Cardiac Surgical Services coordinator to securely access patient information to identify and, if necessary, visit the patient. Then, based on the information gathered by the Cardiac Surgical Services coordinator, a Situation-Background-Assessment-Recommendation report was relayed to the CT surgeon, who then determined whether intervention by the CT surgical team was warranted. This process, on average, took approximately 30 minutes to complete. This was a key change in processes, one that allowed post-CABG patients to be seen by the CT surgical team while in the ED. If the issue was related to the CABG surgery, the CT surgeons could then determine an appropriate course of action, including admission or implementation of another protocol, such as the home furosemide protocol. For patients directly admitted, the surgeon contacted the admitting provider to discuss the level of care required (ie, observation or inpatient admission and treatment).
Biweekly CV team meetings were conducted during the implementation of the real-time notification alert tool. At each meeting, updates were provided on notifications received, patients who were missed by the notification process, and how well the real-time alerts were working to enhance care and appropriate disposition.
Measurements
Clinical performance data included total notifications, total number of ED visits, ED disposition (inpatient admission, observation, discharge), total number of direct admissions, direct admissions to observation, direct inpatient admissions, and patients missed by the notification process (eg, due to data entry errors, omissions of information [suffix of junior or senior], as well as programming bugs). Finally, the number of observation admissions converted to inpatient admissions was collected and further analyzed to inform needed process changes.
The Cardiac Surgical Services coordinator collected, entered, and maintained data using Excel. Data were obtained from the EHR, recorded in Excel, and analyzed using basic descriptive statistics in an ongoing fashion. Particular attention was focused on problems with the notification process (eg, patients being missed due to errors in data entry) and summarizing information to keep the Cardiac Surgical Services team updated on the progress of the process improvement. This project did not require staff protections or considerations, and because this was not a research study Institutional Review Board approval was not required.
Results
This practice change was implemented in September 2017 and led to improvements in care quality, as evidenced by improved physician communication and collaboration. In the 16-month period from implementation through December 2018, the names of 614 post-CABG patients were input into the HIE for tracking. Of these patients, 47 were treated and discharged from the ED; 31 were admitted for observation; and 44 were readmitted for inpatient care. The remaining 492 patients did not have a qualifying event requiring a notification alert. Clinical performance data from this period included 70 ED visits, 21 direct admissions, 19 direct admissions to observation, 5 patients missed by the notification process, and 4 observation admissions converted to inpatient admissions. A reduction in the CABG readmission rate from 10% in September 2017 to 7.2% in December 2018 was also noted.
Discussion
The aim of this process improvement project was to determine whether a real-time electronic alert that notified the CT surgical team about post-op CABG patients presenting to the ED would result in timely patient engagement, avoidance of readmissions, and an enhanced patient experience. This practice change has been successful, following 16 months of implementation and process refinement. Integrating a real-time electronic alert with a supporting action plan and care protocols resulted in timely patient engagement and avoidance of readmission of post-CABG patients.
Early notification of possible post-CABG readmissions became a standard-of-care process within the Cardiac Surgical Services department, with expansion to all CT post-op patients. Leveraging HIE technology to support quality improvement processes was also viewed by other departments as relevant and beneficial. For example, the hospital stroke and orthopedic-spine teams established their own processes for receiving real-time alerts.
There were several lessons learned during this project. First, gaining 100% physician buy-in to collaborative communication proved to be critical to the project’s success. The CV team was surprised by the length of time (approximately 8-10 months) it took for the practice change to be adopted by the physicians. In part, some of this delay in adoption resulted from medical staff turnover, primarily in the medical resident training rotations. Collaborative communication was key. The CT surgeons spoke with ED leadership and hospitalist services to explain the readmission reduction project and the use of an electronic alert tool. The CT surgeons also communicated to the ED physicians, hospitalists, and cardiologists that the Cardiac Surgical Services coordinator would be involved in the process and discussions regarding patientss care. Additionally, the CT surgeons authored the furosemide protocol and then committed to its use in the home health setting, further highlighting the role of collaborative communication in avoiding readmissions.
Another key step in this quality improvement project was determining who should receive the alert notifications. At the onset of the project, all notifications were sent to 1 person, the Cardiac Surgical Services coordinator. While this seemed logical in the initial stage of the project, it was unsustainable, as the receipt of the alert and the subsequent notification of the CT surgeon depended on 1 person and their availability. Approximately 10 months into the project, the notification process was further refined, with the cardiovascular intensive care unit charge nurse becoming the point of contact for the alerts. The Cardiac Surgical Services coordinator, in collaboration with nursing leaders and CT surgeons, completed a Lean Standard Work template outlining the major steps and the associated responsibilities (for the cardiovascular intensive care unit charge nurse, CT surgeon and on-call surgeon, Cardiac Surgical Services coordinator) in the process of receiving notifications, collecting patient assessment data, and reporting notifications to the CT surgeons.
Establishing adequate support mechanisms during a practice change is also important. For instance, we had to dedicate personnel time for data collection and analysis and involve additional nursing or other qualified personnel in the new process to avoid depending on a single person for the project’s success. Additional considerations were establishing criteria for surgeon notification and defining an appropriate time frame for notification (eg, urgent versus next-day notifications). We accomplished these activities approximately 10 months into the project, after it became apparent at CV team meeting discussions that further clarification of criteria and timelines was needed.
Some aspects of the project unfolded as planned, while others presented opportunities for improvement. For example, the alert notification process worked as envisioned; however, as previously mentioned, the process needed to be more inclusive to ensure there is always a charge nurse on duty to receive the alert notification, rather than just the Cardiac Surgical Services coordinator, who may not always be at the hospital. The outpatient thoracentesis program was well planned and effectively implemented. This program provided an avenue for patients who had symptoms of pleural effusion to be treated in an outpatient setting, rather than requiring an inpatient stay. Opportunities for improvement included addressing the inconsistent use of the home health furosemide protocol (developed in 2016), and the need for continued interprofessional and interdepartmental communication and coordination. For example, we had to inform the ED physicians and staff who rotate or are new to the ED about established processes and protocols in place for managing post-CABG patients who present to the ED.
The primary limitation of this project was the inability to measure the enhanced patient experience, which was 1 of the stated project goals. This goal became secondary because of more pressing issues, specifically, interorganizational collaboration (eg, hospital EHR, HIE, and CT surgical team) and tailoring the functionality of the electronic alert tool to the project. Developing and implementing measures of enhanced patient experience were not feasible during this implementation. Additionally, because this was not a research study, it was not possible to determine cause and effect or to control for confounders, such as a sicker, older cohort with more comorbid conditions, during the comparison period. Finally, although this process improvement project was conducted at a regional medical center that is the only facility performing CABG within the region, patients may have presented to another facility for an event that led to a readmission. Because readmissions to other facilities could not be captured, it is possible that the actual readmission rate was higher than the rate reported here.
Conclusions and Implications
Utilizing a real-time alert from the HIE to the CT surgical team resulted in CT surgeons being immediately made aware when their patients presented to the ED, allowing the CT surgical team the opportunity to intervene, as appropriate, in the care of their patients. Furthermore, this real-time notification and intervention resulted in timely patient engagement and, in some cases, avoidance of readmissions. Currently, patients are monitored for readmission within 30 days of discharge. In the future, the time will expand to 91 days, in preparation for participation in the CMS bundle payment program for CABG surgery.
This practice change can be used in organizations that do not have or participate in a HIE. In fact, these real-time alert applications may be available through an EHR already in use within the organization. The use of the alert requires collaborative communication and having supporting protocols in place to guide decision-making and care of post-CABG patients presenting to the ED.
There appears to be a gap in the literature discussing the use of an electronic alert tool as a real-time patient engagement strategy for post-CABG patients presenting to the ED. As such, this project contributes important results and lessons learned for other hospital service lines/departments that might consider implementing a similar process. Next steps include designing and conducting methodologically rigorous research studies based on this process improvement project to examine mortality rates as an outcome, and designing a more specific measure of patient experience, as the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey only provides hospital-level data.
Corresponding author: Stephanie D. Smith, PhD, RN, UNCW School of Nursing, 601 South College Road, Wilmington, NC 28403; smithsd@uncw.edu.
Funding disclosures: None.
1. Hannan EL, Zhong Y, Lahey SJ, et al. 30-day readmissions after coronary artery bypass graft surgery in New York State. JACC Cardiovasc Interv. 2011;4:569-576.
2. Feng TR, White R, Gaber-Baylis L, et al. Coronary artery bypass graft readmission rates and risk factors- A retrospective cohort study. Int J Surg. 2018;54 (Part A):7-17.
3. Donndorf P, Kaminski A. “Return to sender” or “consider it done”?! The importance of reducing hospital readmission after coronary artery bypass grafting. J Thorac Cardiovasc Surg. 2017;154:1298-1299.
4. Sequist TD, Morong SM, Marston A, et al. Electronic risk alerts to improve primary care management of chest pain: A randomized, controlled trial. J Gen Intern Med. 2012;27:438-444.
5. Engelman D, Benjamin EM. Physician engagement: The “secret sauce” to success in bundled health care. Am J Med Qual. 2018;33:100-102.
From the University of North Carolina at Wilmington School of Nursing (Dr. Smith and Dr. Turrise), the New Hanover Regional Medical Center Heart Center (Mr. Jordan), the Coastal Carolinas Health Alliance and Coastal Connect Health Information Exchange (Ms. Robertson), and Coastal Thoracic Surgical Associates (Dr. Kane), Wilmington, NC.
Abstract
Objective: Cardiothoracic (CT) surgeons at our medical center were not receiving timely notification when their coronary artery bypass graft (CABG) surgery patients were admitted to the medical center or to other hospitals. The CT surgical team worked with a health alliance in southeastern North Carolina to implement health information exchange (HIE) real-time electronic notifications for their CABG patients who presented to the hospital’s emergency department (ED) or any ED affiliated with the medical center. The alert tool notifies team members about patient encounters, driving timely clinical engagement.
Methods: The CT team provided the HIE team with the names of CABG surgery patients, which were loaded into the alert tool. When a patient on the list presented to the hospital ED or its affiliates, the alert tool sent a real-time electronic notification to the Cardiac Surgical Services nurse coordinator. This intervention prompted the assessment and disposition of CABG patients, while in the ED, by the CT surgical team.
Results: Over a 16-month period (September 2017-December 2018), the names of 614 post-CABG patients were input into the HIE for tracking. Of these patients, 47 were treated and discharged from the ED; 31 were admitted for observation; 44 were readmitted for inpatient care; and 492 did not have a qualifying event requiring a notification alert. Following implementation of this practice change, the 30-day readmission rate for patients who underwent CABG at our institution decreased from 10% to 7.2%.
Conclusion: Utilizing a real-time alert tool resulted in immediate notification of the CT team when 1 of their patients presented to the ED. This afforded the CT surgical team an opportunity to intervene in the care of their patients, which in turn led to improved quality of care, physician communication and collaboration, and patient outcomes, such as preventable 30-day readmissions.
Keywords: electronic health record; real-time electronic notification; CABG; process improvement.
Unplanned 30-day hospital readmissions of patients who have undergone coronary artery bypass graft (CABG) surgery contribute to higher overall health care costs. CABG is 1 of the conditions/procedures that the Centers for Medicare and Medicaid Services (CMS) monitors for excess readmissions.1 Readmission rates for CABG-related conditions at 30 days post-surgery are reported to be between 16% and 20% for US hospitals.2 Readmissions are not only financially costly, but also have been associated with worse patient outcomes and decreased patient satisfaction.3 Common diagnoses for post-CABG admission include atrial fibrillation, pleural effusion, and wound infection.
The facility where this project was implemented had a 10% post-CABG admission rate for patients across all payers. While this rate is below the national average of 13.2%, the cardiothoracic (CT) surgical team was not being notified in a timely manner when their post-CABG patients were readmitted. The Lean team used the A3 problem-solving process to develop strategies that would reduce these readmissions and improve the care of their patients.
We explored the use of electronic alerts in managing post-CABG patients by conducting a literature search using the terms electronic alerts in patient care, patient engagement in the emergency department, electronic alerts in CABG, real-time notifications to prevent readmission, and CABG readmission. Databases searched were PubMed, Google Scholar, Cumulative Index of Nursing and Allied Health Literature, ProQuest, and ScienceDirect. This search resulted in studies focused on the use of electronic health record (EHR) alerts as a clinical decision-support tool; for example, patient demographic and assessment data are entered into the EHR, and the clinician is prompted with “performance” recommendations (eg, consider electrocardiogram and aspirin).4 In a paper by Engelman and Benjamin,5 the authors discuss the importance of the engaged physician and note that, in their emergency department (ED), an electronic notification is sent when a postoperative patient presents; however, the notification goes to the inpatient service for timely review and disposition. There was no literature that discussed the use of an electronic alert tool as a real-time patient engagement strategy that resulted in a practice change specific to the CT surgical team.
Our process improvement project focused on alerting the CT surgical team when a post-CABG patient presented to the ED, allowing them to evaluate the patient in real time and determine whether the chief complaint was related to the CABG and whether further evaluation by the CT surgeon was required. Specifically, we wanted to determine whether a real-time electronic alert that notified the CT surgical team about post-op CABG patients presenting to the ED would result in timely patient engagement, avoidance of readmissions, and an enhanced patient experience. During this project, alerts were sent to the CT surgical team notifying them of a post-CABG patient presenting to the ED or being directly admitted from home on physician orders, a provider’s office, or inpatient rehabilitation; however, the focus of this article is specifically on the notification regarding post-CABG patients presenting to the ED.
Prior to implementing the electronic notification project, the team developed and implemented several internal and external readmission reduction and prevention strategies for CABG patients. An in-house strategy involved a process whereby patients would receive their discharge medications prior to being discharged from the hospital post-CABG, thereby avoiding potential delays in the patient obtaining medications. When examining post-CABG patient readmissions, the primary conditions that led to readmission were fluid overload, pleural effusion, and atrial fibrillation. As such, a second in-house strategy was developed for post-CABG patients presenting to the ED with atrial fibrillation. The newly established protocol allowed patients to be monitored and treated in the cardiac observation unit. In addition, external strategies, including an outpatient furosemide protocol for home health nurses and an outpatient thoracentesis program and order set, were established (eg, for patients with congestive heart failure, shortness of breath).
Methods
Setting
The regional medical center where this project was implemented is the ninth largest hospital in North Carolina and the largest county-owned public hospital in the state. It is a tertiary care center and teaching hospital with 3 hospital campuses and 855 licensed beds. The medical center was included in the 100 Safecare Hospitals list by the Safecare Group; received a grade “A” Hospital Safety Score from the Leapfrog Group; and is 1 of America’s Top 100 Hospitals for Patient Experience.
Real-Time Notification Project
A regional hospital alliance in southeastern North Carolina established a health information exchange (HIE) with its member hospitals and office-based physicians to enable electronic exchange of patient information to improve quality, safety, and efficiency in health care delivery. Our medical center is part of this alliance. The HIE is a digital platform that facilitates the sharing of information between disparate connected EHR systems, and offers a portal for practices and hospitals to access patient information across North Carolina, South Carolina (via SC HIE), and nationwide (select dialysis centers). More specifically, approved providers and team members are able to access, in real time, patient-care encounter documents from other care settings (eg, acute, post-acute, ambulatory) via the HIE. Additionally, approved care entities can query-retrieve web portal information to support patient outcome improvement strategies. A partnership discussion highlighted the opportunity to utilize the HIE’s capabilities, such as real-time notification, to facilitate workflow (eg, when a patient presents to the ED, the HIE can provide access to health information at the point of care). In this capacity, the alert tool notifies care team members about patient encounters to drive timely clinical engagement for care transitions.
In January 2017, we began discussions on using the HIE to facilitate real-time electronic tracking in the Cardiac Surgical Services department at our medical center. Persons involved in these discussions included the cardiovascular (CV) team (comprised of case managers, department managers and coordinators, program coordinators, administrators, and support services [eg, pre-admission testing and home health staff]) and CT surgeons. At that time, CABG readmissions were manually tracked, and the real-time notification tool was being used in other departments (eg, in case management for tracking readmissions). The entire team was part of the initial decision meeting to pursue this possibility. The CV team reached consensus in June 2017 and proposed extending the use of the alert tool to the post-CABG population presenting to the ED (or any ED affiliated with the medical center) or admitted directly to the medical center.
The HIE staff met with the Cardiac Surgical Services team to tailor and develop the logistics of the project, such as who would be notified and how. The goals of the project were to support appropriate care intervention, reduce preventable hospital readmissions, and improve quality of care through enhanced provider communication and engagement. To achieve these goals, on the day of discharge the Cardiac Surgical Services coordinator provided the HIE team with the names of patients who had undergone CABG surgery. This patient list was loaded into the alert tool and continually updated. At 31 days, patient names were removed from the list. When a patient on the list presented to the hospital ED, the alert tool sent 2 real-time electronic notifications, an email and a text message, to the Cardiac Surgical Services coordinator, noting that a patient event occurred. Personal information was not included in the alert in order to protect patient information and comply with Health Insurance Portability and Accountability Act regulations.
The alert prompted the Cardiac Surgical Services coordinator to securely access patient information to identify and, if necessary, visit the patient. Then, based on the information gathered by the Cardiac Surgical Services coordinator, a Situation-Background-Assessment-Recommendation report was relayed to the CT surgeon, who then determined whether intervention by the CT surgical team was warranted. This process, on average, took approximately 30 minutes to complete. This was a key change in processes, one that allowed post-CABG patients to be seen by the CT surgical team while in the ED. If the issue was related to the CABG surgery, the CT surgeons could then determine an appropriate course of action, including admission or implementation of another protocol, such as the home furosemide protocol. For patients directly admitted, the surgeon contacted the admitting provider to discuss the level of care required (ie, observation or inpatient admission and treatment).
Biweekly CV team meetings were conducted during the implementation of the real-time notification alert tool. At each meeting, updates were provided on notifications received, patients who were missed by the notification process, and how well the real-time alerts were working to enhance care and appropriate disposition.
Measurements
Clinical performance data included total notifications, total number of ED visits, ED disposition (inpatient admission, observation, discharge), total number of direct admissions, direct admissions to observation, direct inpatient admissions, and patients missed by the notification process (eg, due to data entry errors, omissions of information [suffix of junior or senior], as well as programming bugs). Finally, the number of observation admissions converted to inpatient admissions was collected and further analyzed to inform needed process changes.
The Cardiac Surgical Services coordinator collected, entered, and maintained data using Excel. Data were obtained from the EHR, recorded in Excel, and analyzed using basic descriptive statistics in an ongoing fashion. Particular attention was focused on problems with the notification process (eg, patients being missed due to errors in data entry) and summarizing information to keep the Cardiac Surgical Services team updated on the progress of the process improvement. This project did not require staff protections or considerations, and because this was not a research study Institutional Review Board approval was not required.
Results
This practice change was implemented in September 2017 and led to improvements in care quality, as evidenced by improved physician communication and collaboration. In the 16-month period from implementation through December 2018, the names of 614 post-CABG patients were input into the HIE for tracking. Of these patients, 47 were treated and discharged from the ED; 31 were admitted for observation; and 44 were readmitted for inpatient care. The remaining 492 patients did not have a qualifying event requiring a notification alert. Clinical performance data from this period included 70 ED visits, 21 direct admissions, 19 direct admissions to observation, 5 patients missed by the notification process, and 4 observation admissions converted to inpatient admissions. A reduction in the CABG readmission rate from 10% in September 2017 to 7.2% in December 2018 was also noted.
Discussion
The aim of this process improvement project was to determine whether a real-time electronic alert that notified the CT surgical team about post-op CABG patients presenting to the ED would result in timely patient engagement, avoidance of readmissions, and an enhanced patient experience. This practice change has been successful, following 16 months of implementation and process refinement. Integrating a real-time electronic alert with a supporting action plan and care protocols resulted in timely patient engagement and avoidance of readmission of post-CABG patients.
Early notification of possible post-CABG readmissions became a standard-of-care process within the Cardiac Surgical Services department, with expansion to all CT post-op patients. Leveraging HIE technology to support quality improvement processes was also viewed by other departments as relevant and beneficial. For example, the hospital stroke and orthopedic-spine teams established their own processes for receiving real-time alerts.
There were several lessons learned during this project. First, gaining 100% physician buy-in to collaborative communication proved to be critical to the project’s success. The CV team was surprised by the length of time (approximately 8-10 months) it took for the practice change to be adopted by the physicians. In part, some of this delay in adoption resulted from medical staff turnover, primarily in the medical resident training rotations. Collaborative communication was key. The CT surgeons spoke with ED leadership and hospitalist services to explain the readmission reduction project and the use of an electronic alert tool. The CT surgeons also communicated to the ED physicians, hospitalists, and cardiologists that the Cardiac Surgical Services coordinator would be involved in the process and discussions regarding patientss care. Additionally, the CT surgeons authored the furosemide protocol and then committed to its use in the home health setting, further highlighting the role of collaborative communication in avoiding readmissions.
Another key step in this quality improvement project was determining who should receive the alert notifications. At the onset of the project, all notifications were sent to 1 person, the Cardiac Surgical Services coordinator. While this seemed logical in the initial stage of the project, it was unsustainable, as the receipt of the alert and the subsequent notification of the CT surgeon depended on 1 person and their availability. Approximately 10 months into the project, the notification process was further refined, with the cardiovascular intensive care unit charge nurse becoming the point of contact for the alerts. The Cardiac Surgical Services coordinator, in collaboration with nursing leaders and CT surgeons, completed a Lean Standard Work template outlining the major steps and the associated responsibilities (for the cardiovascular intensive care unit charge nurse, CT surgeon and on-call surgeon, Cardiac Surgical Services coordinator) in the process of receiving notifications, collecting patient assessment data, and reporting notifications to the CT surgeons.
Establishing adequate support mechanisms during a practice change is also important. For instance, we had to dedicate personnel time for data collection and analysis and involve additional nursing or other qualified personnel in the new process to avoid depending on a single person for the project’s success. Additional considerations were establishing criteria for surgeon notification and defining an appropriate time frame for notification (eg, urgent versus next-day notifications). We accomplished these activities approximately 10 months into the project, after it became apparent at CV team meeting discussions that further clarification of criteria and timelines was needed.
Some aspects of the project unfolded as planned, while others presented opportunities for improvement. For example, the alert notification process worked as envisioned; however, as previously mentioned, the process needed to be more inclusive to ensure there is always a charge nurse on duty to receive the alert notification, rather than just the Cardiac Surgical Services coordinator, who may not always be at the hospital. The outpatient thoracentesis program was well planned and effectively implemented. This program provided an avenue for patients who had symptoms of pleural effusion to be treated in an outpatient setting, rather than requiring an inpatient stay. Opportunities for improvement included addressing the inconsistent use of the home health furosemide protocol (developed in 2016), and the need for continued interprofessional and interdepartmental communication and coordination. For example, we had to inform the ED physicians and staff who rotate or are new to the ED about established processes and protocols in place for managing post-CABG patients who present to the ED.
The primary limitation of this project was the inability to measure the enhanced patient experience, which was 1 of the stated project goals. This goal became secondary because of more pressing issues, specifically, interorganizational collaboration (eg, hospital EHR, HIE, and CT surgical team) and tailoring the functionality of the electronic alert tool to the project. Developing and implementing measures of enhanced patient experience were not feasible during this implementation. Additionally, because this was not a research study, it was not possible to determine cause and effect or to control for confounders, such as a sicker, older cohort with more comorbid conditions, during the comparison period. Finally, although this process improvement project was conducted at a regional medical center that is the only facility performing CABG within the region, patients may have presented to another facility for an event that led to a readmission. Because readmissions to other facilities could not be captured, it is possible that the actual readmission rate was higher than the rate reported here.
Conclusions and Implications
Utilizing a real-time alert from the HIE to the CT surgical team resulted in CT surgeons being immediately made aware when their patients presented to the ED, allowing the CT surgical team the opportunity to intervene, as appropriate, in the care of their patients. Furthermore, this real-time notification and intervention resulted in timely patient engagement and, in some cases, avoidance of readmissions. Currently, patients are monitored for readmission within 30 days of discharge. In the future, the time will expand to 91 days, in preparation for participation in the CMS bundle payment program for CABG surgery.
This practice change can be used in organizations that do not have or participate in a HIE. In fact, these real-time alert applications may be available through an EHR already in use within the organization. The use of the alert requires collaborative communication and having supporting protocols in place to guide decision-making and care of post-CABG patients presenting to the ED.
There appears to be a gap in the literature discussing the use of an electronic alert tool as a real-time patient engagement strategy for post-CABG patients presenting to the ED. As such, this project contributes important results and lessons learned for other hospital service lines/departments that might consider implementing a similar process. Next steps include designing and conducting methodologically rigorous research studies based on this process improvement project to examine mortality rates as an outcome, and designing a more specific measure of patient experience, as the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey only provides hospital-level data.
Corresponding author: Stephanie D. Smith, PhD, RN, UNCW School of Nursing, 601 South College Road, Wilmington, NC 28403; smithsd@uncw.edu.
Funding disclosures: None.
From the University of North Carolina at Wilmington School of Nursing (Dr. Smith and Dr. Turrise), the New Hanover Regional Medical Center Heart Center (Mr. Jordan), the Coastal Carolinas Health Alliance and Coastal Connect Health Information Exchange (Ms. Robertson), and Coastal Thoracic Surgical Associates (Dr. Kane), Wilmington, NC.
Abstract
Objective: Cardiothoracic (CT) surgeons at our medical center were not receiving timely notification when their coronary artery bypass graft (CABG) surgery patients were admitted to the medical center or to other hospitals. The CT surgical team worked with a health alliance in southeastern North Carolina to implement health information exchange (HIE) real-time electronic notifications for their CABG patients who presented to the hospital’s emergency department (ED) or any ED affiliated with the medical center. The alert tool notifies team members about patient encounters, driving timely clinical engagement.
Methods: The CT team provided the HIE team with the names of CABG surgery patients, which were loaded into the alert tool. When a patient on the list presented to the hospital ED or its affiliates, the alert tool sent a real-time electronic notification to the Cardiac Surgical Services nurse coordinator. This intervention prompted the assessment and disposition of CABG patients, while in the ED, by the CT surgical team.
Results: Over a 16-month period (September 2017-December 2018), the names of 614 post-CABG patients were input into the HIE for tracking. Of these patients, 47 were treated and discharged from the ED; 31 were admitted for observation; 44 were readmitted for inpatient care; and 492 did not have a qualifying event requiring a notification alert. Following implementation of this practice change, the 30-day readmission rate for patients who underwent CABG at our institution decreased from 10% to 7.2%.
Conclusion: Utilizing a real-time alert tool resulted in immediate notification of the CT team when 1 of their patients presented to the ED. This afforded the CT surgical team an opportunity to intervene in the care of their patients, which in turn led to improved quality of care, physician communication and collaboration, and patient outcomes, such as preventable 30-day readmissions.
Keywords: electronic health record; real-time electronic notification; CABG; process improvement.
Unplanned 30-day hospital readmissions of patients who have undergone coronary artery bypass graft (CABG) surgery contribute to higher overall health care costs. CABG is 1 of the conditions/procedures that the Centers for Medicare and Medicaid Services (CMS) monitors for excess readmissions.1 Readmission rates for CABG-related conditions at 30 days post-surgery are reported to be between 16% and 20% for US hospitals.2 Readmissions are not only financially costly, but also have been associated with worse patient outcomes and decreased patient satisfaction.3 Common diagnoses for post-CABG admission include atrial fibrillation, pleural effusion, and wound infection.
The facility where this project was implemented had a 10% post-CABG admission rate for patients across all payers. While this rate is below the national average of 13.2%, the cardiothoracic (CT) surgical team was not being notified in a timely manner when their post-CABG patients were readmitted. The Lean team used the A3 problem-solving process to develop strategies that would reduce these readmissions and improve the care of their patients.
We explored the use of electronic alerts in managing post-CABG patients by conducting a literature search using the terms electronic alerts in patient care, patient engagement in the emergency department, electronic alerts in CABG, real-time notifications to prevent readmission, and CABG readmission. Databases searched were PubMed, Google Scholar, Cumulative Index of Nursing and Allied Health Literature, ProQuest, and ScienceDirect. This search resulted in studies focused on the use of electronic health record (EHR) alerts as a clinical decision-support tool; for example, patient demographic and assessment data are entered into the EHR, and the clinician is prompted with “performance” recommendations (eg, consider electrocardiogram and aspirin).4 In a paper by Engelman and Benjamin,5 the authors discuss the importance of the engaged physician and note that, in their emergency department (ED), an electronic notification is sent when a postoperative patient presents; however, the notification goes to the inpatient service for timely review and disposition. There was no literature that discussed the use of an electronic alert tool as a real-time patient engagement strategy that resulted in a practice change specific to the CT surgical team.
Our process improvement project focused on alerting the CT surgical team when a post-CABG patient presented to the ED, allowing them to evaluate the patient in real time and determine whether the chief complaint was related to the CABG and whether further evaluation by the CT surgeon was required. Specifically, we wanted to determine whether a real-time electronic alert that notified the CT surgical team about post-op CABG patients presenting to the ED would result in timely patient engagement, avoidance of readmissions, and an enhanced patient experience. During this project, alerts were sent to the CT surgical team notifying them of a post-CABG patient presenting to the ED or being directly admitted from home on physician orders, a provider’s office, or inpatient rehabilitation; however, the focus of this article is specifically on the notification regarding post-CABG patients presenting to the ED.
Prior to implementing the electronic notification project, the team developed and implemented several internal and external readmission reduction and prevention strategies for CABG patients. An in-house strategy involved a process whereby patients would receive their discharge medications prior to being discharged from the hospital post-CABG, thereby avoiding potential delays in the patient obtaining medications. When examining post-CABG patient readmissions, the primary conditions that led to readmission were fluid overload, pleural effusion, and atrial fibrillation. As such, a second in-house strategy was developed for post-CABG patients presenting to the ED with atrial fibrillation. The newly established protocol allowed patients to be monitored and treated in the cardiac observation unit. In addition, external strategies, including an outpatient furosemide protocol for home health nurses and an outpatient thoracentesis program and order set, were established (eg, for patients with congestive heart failure, shortness of breath).
Methods
Setting
The regional medical center where this project was implemented is the ninth largest hospital in North Carolina and the largest county-owned public hospital in the state. It is a tertiary care center and teaching hospital with 3 hospital campuses and 855 licensed beds. The medical center was included in the 100 Safecare Hospitals list by the Safecare Group; received a grade “A” Hospital Safety Score from the Leapfrog Group; and is 1 of America’s Top 100 Hospitals for Patient Experience.
Real-Time Notification Project
A regional hospital alliance in southeastern North Carolina established a health information exchange (HIE) with its member hospitals and office-based physicians to enable electronic exchange of patient information to improve quality, safety, and efficiency in health care delivery. Our medical center is part of this alliance. The HIE is a digital platform that facilitates the sharing of information between disparate connected EHR systems, and offers a portal for practices and hospitals to access patient information across North Carolina, South Carolina (via SC HIE), and nationwide (select dialysis centers). More specifically, approved providers and team members are able to access, in real time, patient-care encounter documents from other care settings (eg, acute, post-acute, ambulatory) via the HIE. Additionally, approved care entities can query-retrieve web portal information to support patient outcome improvement strategies. A partnership discussion highlighted the opportunity to utilize the HIE’s capabilities, such as real-time notification, to facilitate workflow (eg, when a patient presents to the ED, the HIE can provide access to health information at the point of care). In this capacity, the alert tool notifies care team members about patient encounters to drive timely clinical engagement for care transitions.
In January 2017, we began discussions on using the HIE to facilitate real-time electronic tracking in the Cardiac Surgical Services department at our medical center. Persons involved in these discussions included the cardiovascular (CV) team (comprised of case managers, department managers and coordinators, program coordinators, administrators, and support services [eg, pre-admission testing and home health staff]) and CT surgeons. At that time, CABG readmissions were manually tracked, and the real-time notification tool was being used in other departments (eg, in case management for tracking readmissions). The entire team was part of the initial decision meeting to pursue this possibility. The CV team reached consensus in June 2017 and proposed extending the use of the alert tool to the post-CABG population presenting to the ED (or any ED affiliated with the medical center) or admitted directly to the medical center.
The HIE staff met with the Cardiac Surgical Services team to tailor and develop the logistics of the project, such as who would be notified and how. The goals of the project were to support appropriate care intervention, reduce preventable hospital readmissions, and improve quality of care through enhanced provider communication and engagement. To achieve these goals, on the day of discharge the Cardiac Surgical Services coordinator provided the HIE team with the names of patients who had undergone CABG surgery. This patient list was loaded into the alert tool and continually updated. At 31 days, patient names were removed from the list. When a patient on the list presented to the hospital ED, the alert tool sent 2 real-time electronic notifications, an email and a text message, to the Cardiac Surgical Services coordinator, noting that a patient event occurred. Personal information was not included in the alert in order to protect patient information and comply with Health Insurance Portability and Accountability Act regulations.
The alert prompted the Cardiac Surgical Services coordinator to securely access patient information to identify and, if necessary, visit the patient. Then, based on the information gathered by the Cardiac Surgical Services coordinator, a Situation-Background-Assessment-Recommendation report was relayed to the CT surgeon, who then determined whether intervention by the CT surgical team was warranted. This process, on average, took approximately 30 minutes to complete. This was a key change in processes, one that allowed post-CABG patients to be seen by the CT surgical team while in the ED. If the issue was related to the CABG surgery, the CT surgeons could then determine an appropriate course of action, including admission or implementation of another protocol, such as the home furosemide protocol. For patients directly admitted, the surgeon contacted the admitting provider to discuss the level of care required (ie, observation or inpatient admission and treatment).
Biweekly CV team meetings were conducted during the implementation of the real-time notification alert tool. At each meeting, updates were provided on notifications received, patients who were missed by the notification process, and how well the real-time alerts were working to enhance care and appropriate disposition.
Measurements
Clinical performance data included total notifications, total number of ED visits, ED disposition (inpatient admission, observation, discharge), total number of direct admissions, direct admissions to observation, direct inpatient admissions, and patients missed by the notification process (eg, due to data entry errors, omissions of information [suffix of junior or senior], as well as programming bugs). Finally, the number of observation admissions converted to inpatient admissions was collected and further analyzed to inform needed process changes.
The Cardiac Surgical Services coordinator collected, entered, and maintained data using Excel. Data were obtained from the EHR, recorded in Excel, and analyzed using basic descriptive statistics in an ongoing fashion. Particular attention was focused on problems with the notification process (eg, patients being missed due to errors in data entry) and summarizing information to keep the Cardiac Surgical Services team updated on the progress of the process improvement. This project did not require staff protections or considerations, and because this was not a research study Institutional Review Board approval was not required.
Results
This practice change was implemented in September 2017 and led to improvements in care quality, as evidenced by improved physician communication and collaboration. In the 16-month period from implementation through December 2018, the names of 614 post-CABG patients were input into the HIE for tracking. Of these patients, 47 were treated and discharged from the ED; 31 were admitted for observation; and 44 were readmitted for inpatient care. The remaining 492 patients did not have a qualifying event requiring a notification alert. Clinical performance data from this period included 70 ED visits, 21 direct admissions, 19 direct admissions to observation, 5 patients missed by the notification process, and 4 observation admissions converted to inpatient admissions. A reduction in the CABG readmission rate from 10% in September 2017 to 7.2% in December 2018 was also noted.
Discussion
The aim of this process improvement project was to determine whether a real-time electronic alert that notified the CT surgical team about post-op CABG patients presenting to the ED would result in timely patient engagement, avoidance of readmissions, and an enhanced patient experience. This practice change has been successful, following 16 months of implementation and process refinement. Integrating a real-time electronic alert with a supporting action plan and care protocols resulted in timely patient engagement and avoidance of readmission of post-CABG patients.
Early notification of possible post-CABG readmissions became a standard-of-care process within the Cardiac Surgical Services department, with expansion to all CT post-op patients. Leveraging HIE technology to support quality improvement processes was also viewed by other departments as relevant and beneficial. For example, the hospital stroke and orthopedic-spine teams established their own processes for receiving real-time alerts.
There were several lessons learned during this project. First, gaining 100% physician buy-in to collaborative communication proved to be critical to the project’s success. The CV team was surprised by the length of time (approximately 8-10 months) it took for the practice change to be adopted by the physicians. In part, some of this delay in adoption resulted from medical staff turnover, primarily in the medical resident training rotations. Collaborative communication was key. The CT surgeons spoke with ED leadership and hospitalist services to explain the readmission reduction project and the use of an electronic alert tool. The CT surgeons also communicated to the ED physicians, hospitalists, and cardiologists that the Cardiac Surgical Services coordinator would be involved in the process and discussions regarding patientss care. Additionally, the CT surgeons authored the furosemide protocol and then committed to its use in the home health setting, further highlighting the role of collaborative communication in avoiding readmissions.
Another key step in this quality improvement project was determining who should receive the alert notifications. At the onset of the project, all notifications were sent to 1 person, the Cardiac Surgical Services coordinator. While this seemed logical in the initial stage of the project, it was unsustainable, as the receipt of the alert and the subsequent notification of the CT surgeon depended on 1 person and their availability. Approximately 10 months into the project, the notification process was further refined, with the cardiovascular intensive care unit charge nurse becoming the point of contact for the alerts. The Cardiac Surgical Services coordinator, in collaboration with nursing leaders and CT surgeons, completed a Lean Standard Work template outlining the major steps and the associated responsibilities (for the cardiovascular intensive care unit charge nurse, CT surgeon and on-call surgeon, Cardiac Surgical Services coordinator) in the process of receiving notifications, collecting patient assessment data, and reporting notifications to the CT surgeons.
Establishing adequate support mechanisms during a practice change is also important. For instance, we had to dedicate personnel time for data collection and analysis and involve additional nursing or other qualified personnel in the new process to avoid depending on a single person for the project’s success. Additional considerations were establishing criteria for surgeon notification and defining an appropriate time frame for notification (eg, urgent versus next-day notifications). We accomplished these activities approximately 10 months into the project, after it became apparent at CV team meeting discussions that further clarification of criteria and timelines was needed.
Some aspects of the project unfolded as planned, while others presented opportunities for improvement. For example, the alert notification process worked as envisioned; however, as previously mentioned, the process needed to be more inclusive to ensure there is always a charge nurse on duty to receive the alert notification, rather than just the Cardiac Surgical Services coordinator, who may not always be at the hospital. The outpatient thoracentesis program was well planned and effectively implemented. This program provided an avenue for patients who had symptoms of pleural effusion to be treated in an outpatient setting, rather than requiring an inpatient stay. Opportunities for improvement included addressing the inconsistent use of the home health furosemide protocol (developed in 2016), and the need for continued interprofessional and interdepartmental communication and coordination. For example, we had to inform the ED physicians and staff who rotate or are new to the ED about established processes and protocols in place for managing post-CABG patients who present to the ED.
The primary limitation of this project was the inability to measure the enhanced patient experience, which was 1 of the stated project goals. This goal became secondary because of more pressing issues, specifically, interorganizational collaboration (eg, hospital EHR, HIE, and CT surgical team) and tailoring the functionality of the electronic alert tool to the project. Developing and implementing measures of enhanced patient experience were not feasible during this implementation. Additionally, because this was not a research study, it was not possible to determine cause and effect or to control for confounders, such as a sicker, older cohort with more comorbid conditions, during the comparison period. Finally, although this process improvement project was conducted at a regional medical center that is the only facility performing CABG within the region, patients may have presented to another facility for an event that led to a readmission. Because readmissions to other facilities could not be captured, it is possible that the actual readmission rate was higher than the rate reported here.
Conclusions and Implications
Utilizing a real-time alert from the HIE to the CT surgical team resulted in CT surgeons being immediately made aware when their patients presented to the ED, allowing the CT surgical team the opportunity to intervene, as appropriate, in the care of their patients. Furthermore, this real-time notification and intervention resulted in timely patient engagement and, in some cases, avoidance of readmissions. Currently, patients are monitored for readmission within 30 days of discharge. In the future, the time will expand to 91 days, in preparation for participation in the CMS bundle payment program for CABG surgery.
This practice change can be used in organizations that do not have or participate in a HIE. In fact, these real-time alert applications may be available through an EHR already in use within the organization. The use of the alert requires collaborative communication and having supporting protocols in place to guide decision-making and care of post-CABG patients presenting to the ED.
There appears to be a gap in the literature discussing the use of an electronic alert tool as a real-time patient engagement strategy for post-CABG patients presenting to the ED. As such, this project contributes important results and lessons learned for other hospital service lines/departments that might consider implementing a similar process. Next steps include designing and conducting methodologically rigorous research studies based on this process improvement project to examine mortality rates as an outcome, and designing a more specific measure of patient experience, as the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey only provides hospital-level data.
Corresponding author: Stephanie D. Smith, PhD, RN, UNCW School of Nursing, 601 South College Road, Wilmington, NC 28403; smithsd@uncw.edu.
Funding disclosures: None.
1. Hannan EL, Zhong Y, Lahey SJ, et al. 30-day readmissions after coronary artery bypass graft surgery in New York State. JACC Cardiovasc Interv. 2011;4:569-576.
2. Feng TR, White R, Gaber-Baylis L, et al. Coronary artery bypass graft readmission rates and risk factors- A retrospective cohort study. Int J Surg. 2018;54 (Part A):7-17.
3. Donndorf P, Kaminski A. “Return to sender” or “consider it done”?! The importance of reducing hospital readmission after coronary artery bypass grafting. J Thorac Cardiovasc Surg. 2017;154:1298-1299.
4. Sequist TD, Morong SM, Marston A, et al. Electronic risk alerts to improve primary care management of chest pain: A randomized, controlled trial. J Gen Intern Med. 2012;27:438-444.
5. Engelman D, Benjamin EM. Physician engagement: The “secret sauce” to success in bundled health care. Am J Med Qual. 2018;33:100-102.
1. Hannan EL, Zhong Y, Lahey SJ, et al. 30-day readmissions after coronary artery bypass graft surgery in New York State. JACC Cardiovasc Interv. 2011;4:569-576.
2. Feng TR, White R, Gaber-Baylis L, et al. Coronary artery bypass graft readmission rates and risk factors- A retrospective cohort study. Int J Surg. 2018;54 (Part A):7-17.
3. Donndorf P, Kaminski A. “Return to sender” or “consider it done”?! The importance of reducing hospital readmission after coronary artery bypass grafting. J Thorac Cardiovasc Surg. 2017;154:1298-1299.
4. Sequist TD, Morong SM, Marston A, et al. Electronic risk alerts to improve primary care management of chest pain: A randomized, controlled trial. J Gen Intern Med. 2012;27:438-444.
5. Engelman D, Benjamin EM. Physician engagement: The “secret sauce” to success in bundled health care. Am J Med Qual. 2018;33:100-102.