Jean Kutner, MD, MSPH

At the turn of the 20th century, most deaths in the United States occurred at home. By the 1960s, over 70% of deaths occurred in an institutional setting, reflecting an evolution of medical technology.[1, 2, 3] With the birth of the hospice movement in the 1970s, dying patients had the opportunity to have both death at home and aggressive symptom control at the end of life. Although there has been a slow decline in the proportion of deaths that occur in the hospital over the past 2 decades,[3] the overwhelming majority of persons state that they would prefer to die at home. However, recent findings suggest that most people will die in an institutional setting.[3, 4, 5, 6]

Although good data exist describing population preferences for location of death, and we know, based on death records, where deaths occur in the United States, there are few studies that examine concordance between preferred and actual site of death at the individual patient level. Furthermore, although factors have been identified that predict death at home, factors predicting concordance between preferred and actual site of death are not well described.[3, 6, 7, 8, 9, 10, 11, 12, 13]

Regardless of where death ultimately occurs, most adults will experience multiple hospitalizations within the last years of their life. Understanding the preferences and subsequent experiences of this population is of particular relevance to hospitalist physicians who are in a unique position to elicit goals from seriously ill patients and help match patient preferences with their medical care. In this observational study, we sought to determine preferences for site of death in a cohort of adult patients admitted to the hospital for medical illness, and then follow those patients to determine where death occurred for those who died. We also sought to explore factors that may predict concordance between preferred and actual site of death. We hypothesized that ethnic diversity and lower socioeconomic status would be associated with a lower likelihood of concordance between preferred and actual site of death. We also hypothesized that advanced care planning would be associated with a higher likelihood of concordance. The Colorado Multi‐Institutional Review Board approved this study.

METHODS

Participants were recruited from 3 hospitals affiliated with the University of Colorado School of Medicine Internal Medicine Residency program, including the Denver Veterans' Administration Center (DVAMC), Denver Health Medical Center (DHMC), and University of Colorado Hospital (UCH). The DVAMC is a large urban Veterans Administration hospital, serving veterans from the Denver metro area, and is a tertiary referral center for veterans in rural Colorado, Wyoming, and parts of Montana. DHMC, the safety‐net hospital for the Denver area, serves over 25% of the residents in the city and county of Denver, including such special populations as the indigent, chronically mentally ill, and persons with polysubstance dependence. UCH had 350 licensed beds at the time of our study and serves as the Rocky Mountain region's only academic tertiary, specialty care, and referral center. At the time of this study, there was limited inpatient palliative care services at the DVAMC and UH, and no palliative care services at DHMC. Participants were screened on the first day following admission to the adult general medical service. Participants were recruited on 96 postadmission days between February 2004 and June 2006. Recruitment days varied from Monday through Friday, to include admissions from the weekend and throughout the year to reduce potential bias due to seasonal trends of diseases such as influenza. Patients were excluded if they died or were discharged within the first 24 hours of admission, were pregnant, jailed, or unable to give informed consent. All other patients were approached and invited to participate in a brief survey.

After informed consent was obtained, participants completed a bedside interview that included self‐identified ethnicity and the Berkman‐Syme Social Network Index,[14] a brief questionnaire quantifying social support from spouse or domestic partner, family, friends, and other religious or secular organizations. Baseline socioeconomic measures (eg, income, employment, home ownership, car ownership) and questions related to the last days of life were also included. Participants were asked the following question, If you were very sick, with an illness that could not be cured, and in bed most of the time, where would you spend the last days of your life if you could chose?

For each participant, we performed a detailed chart review to determine demographic data, presence of advance directives, and CARING criteria (Cancer, Admissions 2, Residence in a nursing home, Intensive care unit admit with multiorgan failure, 2 Noncancer hospice Guidelines), a set of prognostic criteria identifying patients at an index hospitalization who have a high burden of illness and are at risk for death in the following year.[15] We then followed patients for 5 years. If participants died within the follow‐up period, we collected the date and location of death using medical records, death certificates, or in a few cases when official death records were unavailable, direct contact with the family. Participants were considered alive if they had a clinic visit or MD/RN phone contact within 3 months prior to the final collection point date.

RESULTS

Preferred Site of Death

When asked where they preferred to spend the last days of their life, 75% of patients (n=343) stated they would like to be at home. In the hospital was the preferred location for 10% of patients, whereas 6% stated a nursing home and 4% a hospice inpatient facility. Two percent stated they had no preference, and 3% refused to answer (Figure 1)

Figure 1

We found that in the univariable analysis the following factors were associated with preference for site of death at a significance level of P<0.25: unstable housing, hospital setting, income level, ethnicity, CARING criteria, presence of an advance directive, education level, married, primary care provider, and presence of public insurance. Results of the logit models (home vs nursing home or hospice facility, and hospital vs nursing home or hospice facility and home vs hospital) are presented in Table 2.

Table 2.Logistic Regression Modeling of Preference for Death at Home or Hospital

	Adjusted Odds Ratio (95% Confidence Interval)
	Home vs Nursing Home/Hospice Facility	Hospital vs Nursing Home/Hospice Facility	Home vs Hospital
NOTE: Abbreviations: CARING, Cancer, Admissions 2, Residence in a nursing home, Intensive care unit admit with multiorgan failure, 2 Noncancer hospice Guidelines.
Low income	2.71 (1.305.67)	3.05 (1.019.24)	0.99 (0.422.37)
Married	2.44 (1.145.21)	2.40 (0.876.62)	0.82 (0.421.57)
CARING criteria	0.58 (0.301.14)	0.44 (0.181.09)	0.89 (0.471.66)

Patients with income <$30,000/year were more likely to prefer home (or hospital) over a nursing home or hospice facility. Being married was predictive of preferring home over nursing home or hospice facility. Patients meeting 1 of the CARING criteria trended toward being less likely (P=0.11 for home and P=0.08 for hospital) to prefer home (or hospital) vs nursing home or hospice facility. However, there were no significant predictors for a preference for home or hospital when directly comparing the 2 locations, as expected from observing similar effects of variables in the other 2 logit models.

DISCUSSION

We found, similarly to previous reports in the literature, the majority of patients preferred to die at home. We did not find a significant difference in preferences or location of death by ethnicity or illness severity. Lower‐income patients and married patients were more likely to prefer to be at home over a nursing home or a hospice facility in the last days of life. We found that the minority of patients died at their stated preferred site of death, and female gender was the only predictive variable we found to distinguish those patients who died in a place concordant with their wishes compared to those who did not.

In the literature, previous studies have reported concordance rates between preferred and actual site of death that range from 30% to 90%.[12, 13, 18, 19, 20, 21, 22, 23, 24] We found a concordance rate at the lowest end of this spectrum. In trying to understand our findings and place them in context, it is helpful to examine other studies. Many of these studies focused solely on cancer patients.[13, 18, 19, 20, 21, 22, 23] Cancer follows a more predictable trajectory of decline compared to other common life‐threatening illnesses, such as cardiac disease, emphysema, or liver failure, that often involve periods of acute deteriorations and plateaus throughout illness progression. The more predictable trajectory may explain the overall higher concordance rates found in the studies involving cancer patients.

The majority of studies in the literature examining concordance between preferred and actual site of death recruited the study sample from home health or home palliative care programs that were providing support and care to participants.[10, 12, 13, 18, 22, 25, 26, 27] The high concordance rates reported may be the result of the patients in the sample receiving services at home aimed at eliciting preferences and providing support at home. Our observational study is unique in that we elicited patient preferences from a diverse group of hospitalized adults. Patients had a broad range of medical illness and were at various stages in their disease trajectory. This allowed our findings to be more generalizable, a major strength of our study.

The only variable associated with concordance that we identified to predict concordance between preferred and actual site of death was female gender. Women have been shown to be more active in medical decision making, which may explain our findings.[28] Female gender and illness severity (as measured by the CARING criteria) were found to be associated with concordance when the preference is for death at home. For persons with more advanced medical illness, they may have had more opportunity to consider their preferences and talk about these preferences. It is even possible that our interview prompted some participants to have discussions with their families or providers.

Variables with high face validity, such as high social support, higher education, and completing an advance directive, did not demonstrate any effect on the outcome of concordance. Other studies have shown that low functional status, Caucasian ethnicity, home care, higher education, and social support have been associated with a greater likelihood for a home death.[3, 6, 9] However, although studies specifically examining concordance between preferred and actual site of death have looked at predictors for home death, we were unable to find predictors for concordance across all preferences in the literature. We can conclude from our findings that the factors that influence concordance of preferences for site of death are extremely complex and difficult to capture and measure. This is extremely unsatisfying in the face of the low concordance rate of 30% we identified.

Latino ethnicity showed a trend toward having a negative association with concordance between preferred and actual site of death. This trend persisted whether it was concordance overall or for concordance with those who preferred a death at home. In the literature, Latinos have been found to be less likely to complete advance directives, use hospice services at the end of life, and are more likely to experience a hospital death.[29, 30, 31, 32, 33] As care at the end of life continues to improve, careful attention should be paid to ensure that these kinds of gaps do not widen any further.

We interviewed patients at an index hospitalization. Patients had an acute medical illness or an exacerbation of a chronic medical illness and required at least 24 hours of hospitalization to be eligible for inclusion. Our bedside interview made use of an opportune time to question patients, a time when it may have been easier for patients to visualize severe illness at the end of life, rather than asking this question during a time of wellness. Although participants overwhelmingly stated they preferred to be at home, for those who died, decisions were made in their care that did not allow for this preference.

Our follow‐up after the initial bedside interview only included death records of where and when participants died. We do not have the details and narrative of the conversations that may have taken place that led to the care decisions that determined participants' actual place of death. We do not know if preferences were elicited or discussed, and care decisions then negotiated, to best meet the goals and preferences expressed at that time. We also do not know if the conversations did not occur and the default of medical intervention and cure‐focused care dictated how participants spent the last days of their life. There is evidence that when conversations about goals and preferences do occur, concordance between preferences and care received are high.[12, 21]

We were unable to identify any predictors beyond gender in this cohort of adults hospitalized with a broad spectrum of severe medical illness to predict concordance with stated preferences and actual site of death. We can conclude then, based on our findings and supported by the literature, that the default trends toward institutional end‐of‐life experiences. To shift to a more patient‐centered approach, away from the default, healthcare providers need to embrace a palliative approach and incorporate preferences and goals into the discussions about next steps of care to facilitate the peaceful death that the majority of patients imagine for themselves. Hospitalist physicians have a unique opportunity at an index hospitalization to start the conversation about preferences for care including where patients would want to spend the last days of their life.

Our study does have some limitations. We elicited preferences at a single point in time, at an index hospitalization. It is possible that participants' preferences changed over the course of their illness. However, in Agar et al.'s study of longitudinal patient preferences for site of death and place of care, most preferences remained stable over time.[18] We also did not have data that included palliative care involvement, homecare or hospice utilization, or cause of death. All of these variables may be important predictors of concordance. Issues of symptom management and lack of caregiver may also dictate place of death, even when goals and care are aligned. We do not have data to address these components of end‐of‐life decision making.

CONCLUSION

Patients continue to express a preference for death at home. However, the majority of patients experienced an institutional death. Furthermore, few participants achieved concordance with where they preferred to die and where they actually died. Female gender was the sole factor associated with concordance between preferred and actual site of death. Incorporating a palliative approach that elicits goals and helps match goals to care, may offer the best opportunity to help people die where they chose.

Disclosures: This research was supported by the Brookdale National Fellowship Award and the NIA/Beeson grant 5K23AG028957. All authors have seen and agree with the contents of the article. This submission was not under review by any other publication. The authors have no financial interest or other potential conflicts of interest.

At the turn of the 20th century, most deaths in the United States occurred at home. By the 1960s, over 70% of deaths occurred in an institutional setting, reflecting an evolution of medical technology.[1, 2, 3] With the birth of the hospice movement in the 1970s, dying patients had the opportunity to have both death at home and aggressive symptom control at the end of life. Although there has been a slow decline in the proportion of deaths that occur in the hospital over the past 2 decades,[3] the overwhelming majority of persons state that they would prefer to die at home. However, recent findings suggest that most people will die in an institutional setting.[3, 4, 5, 6]

Although good data exist describing population preferences for location of death, and we know, based on death records, where deaths occur in the United States, there are few studies that examine concordance between preferred and actual site of death at the individual patient level. Furthermore, although factors have been identified that predict death at home, factors predicting concordance between preferred and actual site of death are not well described.[3, 6, 7, 8, 9, 10, 11, 12, 13]

Regardless of where death ultimately occurs, most adults will experience multiple hospitalizations within the last years of their life. Understanding the preferences and subsequent experiences of this population is of particular relevance to hospitalist physicians who are in a unique position to elicit goals from seriously ill patients and help match patient preferences with their medical care. In this observational study, we sought to determine preferences for site of death in a cohort of adult patients admitted to the hospital for medical illness, and then follow those patients to determine where death occurred for those who died. We also sought to explore factors that may predict concordance between preferred and actual site of death. We hypothesized that ethnic diversity and lower socioeconomic status would be associated with a lower likelihood of concordance between preferred and actual site of death. We also hypothesized that advanced care planning would be associated with a higher likelihood of concordance. The Colorado Multi‐Institutional Review Board approved this study.

METHODS

Participants were recruited from 3 hospitals affiliated with the University of Colorado School of Medicine Internal Medicine Residency program, including the Denver Veterans' Administration Center (DVAMC), Denver Health Medical Center (DHMC), and University of Colorado Hospital (UCH). The DVAMC is a large urban Veterans Administration hospital, serving veterans from the Denver metro area, and is a tertiary referral center for veterans in rural Colorado, Wyoming, and parts of Montana. DHMC, the safety‐net hospital for the Denver area, serves over 25% of the residents in the city and county of Denver, including such special populations as the indigent, chronically mentally ill, and persons with polysubstance dependence. UCH had 350 licensed beds at the time of our study and serves as the Rocky Mountain region's only academic tertiary, specialty care, and referral center. At the time of this study, there was limited inpatient palliative care services at the DVAMC and UH, and no palliative care services at DHMC. Participants were screened on the first day following admission to the adult general medical service. Participants were recruited on 96 postadmission days between February 2004 and June 2006. Recruitment days varied from Monday through Friday, to include admissions from the weekend and throughout the year to reduce potential bias due to seasonal trends of diseases such as influenza. Patients were excluded if they died or were discharged within the first 24 hours of admission, were pregnant, jailed, or unable to give informed consent. All other patients were approached and invited to participate in a brief survey.

After informed consent was obtained, participants completed a bedside interview that included self‐identified ethnicity and the Berkman‐Syme Social Network Index,[14] a brief questionnaire quantifying social support from spouse or domestic partner, family, friends, and other religious or secular organizations. Baseline socioeconomic measures (eg, income, employment, home ownership, car ownership) and questions related to the last days of life were also included. Participants were asked the following question, If you were very sick, with an illness that could not be cured, and in bed most of the time, where would you spend the last days of your life if you could chose?

For each participant, we performed a detailed chart review to determine demographic data, presence of advance directives, and CARING criteria (Cancer, Admissions 2, Residence in a nursing home, Intensive care unit admit with multiorgan failure, 2 Noncancer hospice Guidelines), a set of prognostic criteria identifying patients at an index hospitalization who have a high burden of illness and are at risk for death in the following year.[15] We then followed patients for 5 years. If participants died within the follow‐up period, we collected the date and location of death using medical records, death certificates, or in a few cases when official death records were unavailable, direct contact with the family. Participants were considered alive if they had a clinic visit or MD/RN phone contact within 3 months prior to the final collection point date.

RESULTS

Preferred Site of Death

When asked where they preferred to spend the last days of their life, 75% of patients (n=343) stated they would like to be at home. In the hospital was the preferred location for 10% of patients, whereas 6% stated a nursing home and 4% a hospice inpatient facility. Two percent stated they had no preference, and 3% refused to answer (Figure 1)

Figure 1

We found that in the univariable analysis the following factors were associated with preference for site of death at a significance level of P<0.25: unstable housing, hospital setting, income level, ethnicity, CARING criteria, presence of an advance directive, education level, married, primary care provider, and presence of public insurance. Results of the logit models (home vs nursing home or hospice facility, and hospital vs nursing home or hospice facility and home vs hospital) are presented in Table 2.

Table 2.Logistic Regression Modeling of Preference for Death at Home or Hospital

	Adjusted Odds Ratio (95% Confidence Interval)
	Home vs Nursing Home/Hospice Facility	Hospital vs Nursing Home/Hospice Facility	Home vs Hospital
NOTE: Abbreviations: CARING, Cancer, Admissions 2, Residence in a nursing home, Intensive care unit admit with multiorgan failure, 2 Noncancer hospice Guidelines.
Low income	2.71 (1.305.67)	3.05 (1.019.24)	0.99 (0.422.37)
Married	2.44 (1.145.21)	2.40 (0.876.62)	0.82 (0.421.57)
CARING criteria	0.58 (0.301.14)	0.44 (0.181.09)	0.89 (0.471.66)

Patients with income <$30,000/year were more likely to prefer home (or hospital) over a nursing home or hospice facility. Being married was predictive of preferring home over nursing home or hospice facility. Patients meeting 1 of the CARING criteria trended toward being less likely (P=0.11 for home and P=0.08 for hospital) to prefer home (or hospital) vs nursing home or hospice facility. However, there were no significant predictors for a preference for home or hospital when directly comparing the 2 locations, as expected from observing similar effects of variables in the other 2 logit models.

DISCUSSION

We found, similarly to previous reports in the literature, the majority of patients preferred to die at home. We did not find a significant difference in preferences or location of death by ethnicity or illness severity. Lower‐income patients and married patients were more likely to prefer to be at home over a nursing home or a hospice facility in the last days of life. We found that the minority of patients died at their stated preferred site of death, and female gender was the only predictive variable we found to distinguish those patients who died in a place concordant with their wishes compared to those who did not.

In the literature, previous studies have reported concordance rates between preferred and actual site of death that range from 30% to 90%.[12, 13, 18, 19, 20, 21, 22, 23, 24] We found a concordance rate at the lowest end of this spectrum. In trying to understand our findings and place them in context, it is helpful to examine other studies. Many of these studies focused solely on cancer patients.[13, 18, 19, 20, 21, 22, 23] Cancer follows a more predictable trajectory of decline compared to other common life‐threatening illnesses, such as cardiac disease, emphysema, or liver failure, that often involve periods of acute deteriorations and plateaus throughout illness progression. The more predictable trajectory may explain the overall higher concordance rates found in the studies involving cancer patients.

The majority of studies in the literature examining concordance between preferred and actual site of death recruited the study sample from home health or home palliative care programs that were providing support and care to participants.[10, 12, 13, 18, 22, 25, 26, 27] The high concordance rates reported may be the result of the patients in the sample receiving services at home aimed at eliciting preferences and providing support at home. Our observational study is unique in that we elicited patient preferences from a diverse group of hospitalized adults. Patients had a broad range of medical illness and were at various stages in their disease trajectory. This allowed our findings to be more generalizable, a major strength of our study.

The only variable associated with concordance that we identified to predict concordance between preferred and actual site of death was female gender. Women have been shown to be more active in medical decision making, which may explain our findings.[28] Female gender and illness severity (as measured by the CARING criteria) were found to be associated with concordance when the preference is for death at home. For persons with more advanced medical illness, they may have had more opportunity to consider their preferences and talk about these preferences. It is even possible that our interview prompted some participants to have discussions with their families or providers.

Variables with high face validity, such as high social support, higher education, and completing an advance directive, did not demonstrate any effect on the outcome of concordance. Other studies have shown that low functional status, Caucasian ethnicity, home care, higher education, and social support have been associated with a greater likelihood for a home death.[3, 6, 9] However, although studies specifically examining concordance between preferred and actual site of death have looked at predictors for home death, we were unable to find predictors for concordance across all preferences in the literature. We can conclude from our findings that the factors that influence concordance of preferences for site of death are extremely complex and difficult to capture and measure. This is extremely unsatisfying in the face of the low concordance rate of 30% we identified.

Latino ethnicity showed a trend toward having a negative association with concordance between preferred and actual site of death. This trend persisted whether it was concordance overall or for concordance with those who preferred a death at home. In the literature, Latinos have been found to be less likely to complete advance directives, use hospice services at the end of life, and are more likely to experience a hospital death.[29, 30, 31, 32, 33] As care at the end of life continues to improve, careful attention should be paid to ensure that these kinds of gaps do not widen any further.

We interviewed patients at an index hospitalization. Patients had an acute medical illness or an exacerbation of a chronic medical illness and required at least 24 hours of hospitalization to be eligible for inclusion. Our bedside interview made use of an opportune time to question patients, a time when it may have been easier for patients to visualize severe illness at the end of life, rather than asking this question during a time of wellness. Although participants overwhelmingly stated they preferred to be at home, for those who died, decisions were made in their care that did not allow for this preference.

Our follow‐up after the initial bedside interview only included death records of where and when participants died. We do not have the details and narrative of the conversations that may have taken place that led to the care decisions that determined participants' actual place of death. We do not know if preferences were elicited or discussed, and care decisions then negotiated, to best meet the goals and preferences expressed at that time. We also do not know if the conversations did not occur and the default of medical intervention and cure‐focused care dictated how participants spent the last days of their life. There is evidence that when conversations about goals and preferences do occur, concordance between preferences and care received are high.[12, 21]

We were unable to identify any predictors beyond gender in this cohort of adults hospitalized with a broad spectrum of severe medical illness to predict concordance with stated preferences and actual site of death. We can conclude then, based on our findings and supported by the literature, that the default trends toward institutional end‐of‐life experiences. To shift to a more patient‐centered approach, away from the default, healthcare providers need to embrace a palliative approach and incorporate preferences and goals into the discussions about next steps of care to facilitate the peaceful death that the majority of patients imagine for themselves. Hospitalist physicians have a unique opportunity at an index hospitalization to start the conversation about preferences for care including where patients would want to spend the last days of their life.

Our study does have some limitations. We elicited preferences at a single point in time, at an index hospitalization. It is possible that participants' preferences changed over the course of their illness. However, in Agar et al.'s study of longitudinal patient preferences for site of death and place of care, most preferences remained stable over time.[18] We also did not have data that included palliative care involvement, homecare or hospice utilization, or cause of death. All of these variables may be important predictors of concordance. Issues of symptom management and lack of caregiver may also dictate place of death, even when goals and care are aligned. We do not have data to address these components of end‐of‐life decision making.

CONCLUSION

Patients continue to express a preference for death at home. However, the majority of patients experienced an institutional death. Furthermore, few participants achieved concordance with where they preferred to die and where they actually died. Female gender was the sole factor associated with concordance between preferred and actual site of death. Incorporating a palliative approach that elicits goals and helps match goals to care, may offer the best opportunity to help people die where they chose.

Disclosures: This research was supported by the Brookdale National Fellowship Award and the NIA/Beeson grant 5K23AG028957. All authors have seen and agree with the contents of the article. This submission was not under review by any other publication. The authors have no financial interest or other potential conflicts of interest.

At the turn of the 20th century, most deaths in the United States occurred at home. By the 1960s, over 70% of deaths occurred in an institutional setting, reflecting an evolution of medical technology.[1, 2, 3] With the birth of the hospice movement in the 1970s, dying patients had the opportunity to have both death at home and aggressive symptom control at the end of life. Although there has been a slow decline in the proportion of deaths that occur in the hospital over the past 2 decades,[3] the overwhelming majority of persons state that they would prefer to die at home. However, recent findings suggest that most people will die in an institutional setting.[3, 4, 5, 6]

Although good data exist describing population preferences for location of death, and we know, based on death records, where deaths occur in the United States, there are few studies that examine concordance between preferred and actual site of death at the individual patient level. Furthermore, although factors have been identified that predict death at home, factors predicting concordance between preferred and actual site of death are not well described.[3, 6, 7, 8, 9, 10, 11, 12, 13]

Regardless of where death ultimately occurs, most adults will experience multiple hospitalizations within the last years of their life. Understanding the preferences and subsequent experiences of this population is of particular relevance to hospitalist physicians who are in a unique position to elicit goals from seriously ill patients and help match patient preferences with their medical care. In this observational study, we sought to determine preferences for site of death in a cohort of adult patients admitted to the hospital for medical illness, and then follow those patients to determine where death occurred for those who died. We also sought to explore factors that may predict concordance between preferred and actual site of death. We hypothesized that ethnic diversity and lower socioeconomic status would be associated with a lower likelihood of concordance between preferred and actual site of death. We also hypothesized that advanced care planning would be associated with a higher likelihood of concordance. The Colorado Multi‐Institutional Review Board approved this study.

METHODS

Participants were recruited from 3 hospitals affiliated with the University of Colorado School of Medicine Internal Medicine Residency program, including the Denver Veterans' Administration Center (DVAMC), Denver Health Medical Center (DHMC), and University of Colorado Hospital (UCH). The DVAMC is a large urban Veterans Administration hospital, serving veterans from the Denver metro area, and is a tertiary referral center for veterans in rural Colorado, Wyoming, and parts of Montana. DHMC, the safety‐net hospital for the Denver area, serves over 25% of the residents in the city and county of Denver, including such special populations as the indigent, chronically mentally ill, and persons with polysubstance dependence. UCH had 350 licensed beds at the time of our study and serves as the Rocky Mountain region's only academic tertiary, specialty care, and referral center. At the time of this study, there was limited inpatient palliative care services at the DVAMC and UH, and no palliative care services at DHMC. Participants were screened on the first day following admission to the adult general medical service. Participants were recruited on 96 postadmission days between February 2004 and June 2006. Recruitment days varied from Monday through Friday, to include admissions from the weekend and throughout the year to reduce potential bias due to seasonal trends of diseases such as influenza. Patients were excluded if they died or were discharged within the first 24 hours of admission, were pregnant, jailed, or unable to give informed consent. All other patients were approached and invited to participate in a brief survey.

After informed consent was obtained, participants completed a bedside interview that included self‐identified ethnicity and the Berkman‐Syme Social Network Index,[14] a brief questionnaire quantifying social support from spouse or domestic partner, family, friends, and other religious or secular organizations. Baseline socioeconomic measures (eg, income, employment, home ownership, car ownership) and questions related to the last days of life were also included. Participants were asked the following question, If you were very sick, with an illness that could not be cured, and in bed most of the time, where would you spend the last days of your life if you could chose?

For each participant, we performed a detailed chart review to determine demographic data, presence of advance directives, and CARING criteria (Cancer, Admissions 2, Residence in a nursing home, Intensive care unit admit with multiorgan failure, 2 Noncancer hospice Guidelines), a set of prognostic criteria identifying patients at an index hospitalization who have a high burden of illness and are at risk for death in the following year.[15] We then followed patients for 5 years. If participants died within the follow‐up period, we collected the date and location of death using medical records, death certificates, or in a few cases when official death records were unavailable, direct contact with the family. Participants were considered alive if they had a clinic visit or MD/RN phone contact within 3 months prior to the final collection point date.

RESULTS

Preferred Site of Death

When asked where they preferred to spend the last days of their life, 75% of patients (n=343) stated they would like to be at home. In the hospital was the preferred location for 10% of patients, whereas 6% stated a nursing home and 4% a hospice inpatient facility. Two percent stated they had no preference, and 3% refused to answer (Figure 1)

Figure 1

We found that in the univariable analysis the following factors were associated with preference for site of death at a significance level of P<0.25: unstable housing, hospital setting, income level, ethnicity, CARING criteria, presence of an advance directive, education level, married, primary care provider, and presence of public insurance. Results of the logit models (home vs nursing home or hospice facility, and hospital vs nursing home or hospice facility and home vs hospital) are presented in Table 2.

Table 2.Logistic Regression Modeling of Preference for Death at Home or Hospital

	Adjusted Odds Ratio (95% Confidence Interval)
	Home vs Nursing Home/Hospice Facility	Hospital vs Nursing Home/Hospice Facility	Home vs Hospital
NOTE: Abbreviations: CARING, Cancer, Admissions 2, Residence in a nursing home, Intensive care unit admit with multiorgan failure, 2 Noncancer hospice Guidelines.
Low income	2.71 (1.305.67)	3.05 (1.019.24)	0.99 (0.422.37)
Married	2.44 (1.145.21)	2.40 (0.876.62)	0.82 (0.421.57)
CARING criteria	0.58 (0.301.14)	0.44 (0.181.09)	0.89 (0.471.66)

Patients with income <$30,000/year were more likely to prefer home (or hospital) over a nursing home or hospice facility. Being married was predictive of preferring home over nursing home or hospice facility. Patients meeting 1 of the CARING criteria trended toward being less likely (P=0.11 for home and P=0.08 for hospital) to prefer home (or hospital) vs nursing home or hospice facility. However, there were no significant predictors for a preference for home or hospital when directly comparing the 2 locations, as expected from observing similar effects of variables in the other 2 logit models.

DISCUSSION

We found, similarly to previous reports in the literature, the majority of patients preferred to die at home. We did not find a significant difference in preferences or location of death by ethnicity or illness severity. Lower‐income patients and married patients were more likely to prefer to be at home over a nursing home or a hospice facility in the last days of life. We found that the minority of patients died at their stated preferred site of death, and female gender was the only predictive variable we found to distinguish those patients who died in a place concordant with their wishes compared to those who did not.

In the literature, previous studies have reported concordance rates between preferred and actual site of death that range from 30% to 90%.[12, 13, 18, 19, 20, 21, 22, 23, 24] We found a concordance rate at the lowest end of this spectrum. In trying to understand our findings and place them in context, it is helpful to examine other studies. Many of these studies focused solely on cancer patients.[13, 18, 19, 20, 21, 22, 23] Cancer follows a more predictable trajectory of decline compared to other common life‐threatening illnesses, such as cardiac disease, emphysema, or liver failure, that often involve periods of acute deteriorations and plateaus throughout illness progression. The more predictable trajectory may explain the overall higher concordance rates found in the studies involving cancer patients.

The majority of studies in the literature examining concordance between preferred and actual site of death recruited the study sample from home health or home palliative care programs that were providing support and care to participants.[10, 12, 13, 18, 22, 25, 26, 27] The high concordance rates reported may be the result of the patients in the sample receiving services at home aimed at eliciting preferences and providing support at home. Our observational study is unique in that we elicited patient preferences from a diverse group of hospitalized adults. Patients had a broad range of medical illness and were at various stages in their disease trajectory. This allowed our findings to be more generalizable, a major strength of our study.

The only variable associated with concordance that we identified to predict concordance between preferred and actual site of death was female gender. Women have been shown to be more active in medical decision making, which may explain our findings.[28] Female gender and illness severity (as measured by the CARING criteria) were found to be associated with concordance when the preference is for death at home. For persons with more advanced medical illness, they may have had more opportunity to consider their preferences and talk about these preferences. It is even possible that our interview prompted some participants to have discussions with their families or providers.

Variables with high face validity, such as high social support, higher education, and completing an advance directive, did not demonstrate any effect on the outcome of concordance. Other studies have shown that low functional status, Caucasian ethnicity, home care, higher education, and social support have been associated with a greater likelihood for a home death.[3, 6, 9] However, although studies specifically examining concordance between preferred and actual site of death have looked at predictors for home death, we were unable to find predictors for concordance across all preferences in the literature. We can conclude from our findings that the factors that influence concordance of preferences for site of death are extremely complex and difficult to capture and measure. This is extremely unsatisfying in the face of the low concordance rate of 30% we identified.

Latino ethnicity showed a trend toward having a negative association with concordance between preferred and actual site of death. This trend persisted whether it was concordance overall or for concordance with those who preferred a death at home. In the literature, Latinos have been found to be less likely to complete advance directives, use hospice services at the end of life, and are more likely to experience a hospital death.[29, 30, 31, 32, 33] As care at the end of life continues to improve, careful attention should be paid to ensure that these kinds of gaps do not widen any further.

We interviewed patients at an index hospitalization. Patients had an acute medical illness or an exacerbation of a chronic medical illness and required at least 24 hours of hospitalization to be eligible for inclusion. Our bedside interview made use of an opportune time to question patients, a time when it may have been easier for patients to visualize severe illness at the end of life, rather than asking this question during a time of wellness. Although participants overwhelmingly stated they preferred to be at home, for those who died, decisions were made in their care that did not allow for this preference.

Our follow‐up after the initial bedside interview only included death records of where and when participants died. We do not have the details and narrative of the conversations that may have taken place that led to the care decisions that determined participants' actual place of death. We do not know if preferences were elicited or discussed, and care decisions then negotiated, to best meet the goals and preferences expressed at that time. We also do not know if the conversations did not occur and the default of medical intervention and cure‐focused care dictated how participants spent the last days of their life. There is evidence that when conversations about goals and preferences do occur, concordance between preferences and care received are high.[12, 21]

We were unable to identify any predictors beyond gender in this cohort of adults hospitalized with a broad spectrum of severe medical illness to predict concordance with stated preferences and actual site of death. We can conclude then, based on our findings and supported by the literature, that the default trends toward institutional end‐of‐life experiences. To shift to a more patient‐centered approach, away from the default, healthcare providers need to embrace a palliative approach and incorporate preferences and goals into the discussions about next steps of care to facilitate the peaceful death that the majority of patients imagine for themselves. Hospitalist physicians have a unique opportunity at an index hospitalization to start the conversation about preferences for care including where patients would want to spend the last days of their life.

Our study does have some limitations. We elicited preferences at a single point in time, at an index hospitalization. It is possible that participants' preferences changed over the course of their illness. However, in Agar et al.'s study of longitudinal patient preferences for site of death and place of care, most preferences remained stable over time.[18] We also did not have data that included palliative care involvement, homecare or hospice utilization, or cause of death. All of these variables may be important predictors of concordance. Issues of symptom management and lack of caregiver may also dictate place of death, even when goals and care are aligned. We do not have data to address these components of end‐of‐life decision making.

CONCLUSION

Patients continue to express a preference for death at home. However, the majority of patients experienced an institutional death. Furthermore, few participants achieved concordance with where they preferred to die and where they actually died. Female gender was the sole factor associated with concordance between preferred and actual site of death. Incorporating a palliative approach that elicits goals and helps match goals to care, may offer the best opportunity to help people die where they chose.

Disclosures: This research was supported by the Brookdale National Fellowship Award and the NIA/Beeson grant 5K23AG028957. All authors have seen and agree with the contents of the article. This submission was not under review by any other publication. The authors have no financial interest or other potential conflicts of interest.

Inpatient medication errors represent an important patient safety issue. The magnitude of the problem is staggering, with 1 review finding almost 1 in every 5 medication doses in error, with 7% having potential for adverse drug events.1 While mistakes made at the ordering stage are frequently intercepted by pharmacist or nursing review, administration errors are particularly difficult to prevent.2 The patient, as the last link in the medication administration chain, represents the final individual capable of preventing an incorrect medication administration. It is perhaps surprising then that patients generally lack a formal role in detecting and preventing adverse medication administration events.3

There have been some ambitious attempts to improve patient education regarding hospital medications and involve selected patients in the medication administration process. Such initiatives may result in increased patient participation and satisfaction.47 There is also potential that increased patient knowledge of their hospital medications could promote the goal of medication safety, as the actively involved patient may be able to catch medication errors in the hospital.

Knowledge of prescribed medications is a prerequisite to patient involvement in prevention of inpatient medication errors and yet there is little research on patient knowledge of their hospital medications. Furthermore, as the experience of hospitalization may be disorienting and disempowering for patients, it remains to be seen if patient attitudes toward participation in inpatient medication safety are favorable. To that end, we conducted a pilot study in which we assessed current patient awareness of their in‐hospital medications and surveyed attitudes toward increased patient knowledge of hospital medications.

PATIENTS AND METHODS

We conducted a cross‐sectional study of 50 cognitively intact adult internal medicine inpatients at the University of Colorado Hospital, a tertiary‐care academic teaching hospital. This study was part of a larger project designed to examine potential for patient involvement in the medication reconciliation process. A professional research assistant approached eligible patients within 24 hours of admission. To be eligible, patients had to self‐identify as knowing their outpatient medications, speak English, and have been admitted from the community. Nursing home residents and patients with a past medical history of dementia were excluded. Enrollment was tracked during the first half of the study to estimate effect of inclusion/exclusion criteria. Thirty‐eight percent of hospital admissions to medicine services were excluded based on the specified criteria. Thirty‐four percent of eligible patients were approached and 50% of approached patients agreed to participate in the study. Patient knowledge of their outpatient medication regimen was compared to admitting physician medication reconciliation to assess accuracy of patient self‐report of outpatient medication knowledge.

After consenting to participate, study patients completed a structured list of their outpatient medications and a survey of attitudes about being shown their in‐hospital medications, hospital medication errors, and patient involvement in hospital safety. They then completed a list of the medications they believed to be prescribed to them in the hospital.

The primary outcomes were the proportions of as needed (PRN), scheduled, and total hospital medications omitted by the patient, compared to the inpatient medication administration record (MAR) (patient errors of omission). Secondary outcomes included the number of in‐hospital medications listed by the patient that did not appear on the inpatient MAR (patient errors of commission), as well as patient attitudes measured on a 5‐point Likert scale (1 indicated strongly disagree and 5 indicated strongly agree.) Descriptive data included age, race, gender, and number of inpatient medications prescribed. Separate analysis of variance (ANOVA) models provided mean estimates of the primary outcomes and tested differences according to each of the patient characteristics: age in years (<65 or 65), self‐reported knowledge of hospital medications, and self‐reported desire to be involved in medication safety. Similar ANOVA models adjusted for number of medications were also examined to determine whether the relationship between the primary outcomes according to patient characteristics were altered by the number of medications. The protocol was approved by the Colorado Multiple Institutional Review Board.

RESULTS

Participants averaged 54 years of age (standard deviation [SD] = 17, range = 21‐89). Forty‐six percent (23/50) were male, and 74% (37/50) were non‐Hispanic white. Using a structured, patient‐completed, outpatient medication list, patients in the study were on an average of 5.3 outpatient prescription medications (range = 0‐17), 2.2 over‐the‐counter medications (range = 0‐8), and 0.2 herbal medications (range = 0‐7). The admitting physician's medication reconciliation list demonstrated similar number of outpatient prescription medications (average = 5.7) to the patient‐generated list. Fifty‐four percent of patient‐completed home medication lists included all of the prescription medications on the physician's medication reconciliation at admission. According to the inpatient MAR, study patients were prescribed an average of 11.3 scheduled and PRN hospital medications (range = 2‐26) at time of study enrollment.

Patient Knowledge of Their Hospital Medication List

Ninety‐six percent (48/50) of study patients omitted 1 or more of their hospital medications. On average, patients omitted 6.8 medications (range = 0‐22) (Table 1). Among scheduled medications, patients most commonly omitted antibiotics (17%), cardiovascular medications (16%), and antithrombotics (15%) (Figure 1). Among PRN medications, patients most commonly omitted analgesics (33%) and gastrointestinal medications (29%) (Figure 2).

Table 1.Patient Knowledge of Their Hospital Medications List

	Total Medications	Scheduled Medications	PRN Medications
NOTE: n = 50 patients. Abbreviations: CI, confidence interval; PRN, as needed.
Percent of patients with at least 1 hospital medication they could not name (95% CI)	96% (90‐100%)	94% (87‐100%)	80% (69‐92%)
Average number of hospital medications omitted by patient (range)	6.8 (0‐22)	5.2 (0‐15)	1.6 (0‐7)
Percentage of hospital medications omitted by patient (95% CI)	60% (52‐67%)	60% (52‐67%)	68% (57‐78%)

Figure 1

Figure 2

Patients less than 65 years omitted 60% of their PRN medications whereas patients greater than 65 years omitted 88% (P = 0.01). This difference remained even after adjustment for number of medications. There were no significant differences, based on age, in ability to name scheduled or total medications. Forty‐four percent of patients (22/50) believed they were receiving a medication in the hospital that was not actually prescribed.

DISCUSSION

Overall, patients in the study were able to name fewer than one‐half of their hospital medications. Our study suggests that adult medicine inpatients believe learning about their hospital medications would increase their satisfaction and has potential to promote medication safety. At the same time, patients did not know many of their hospital medications and this would limit their ability to fully participate in the medication safety process. Study patients frequently committed both errors of omission (ie, they did not know which medications were prescribed), and errors of commission (ie, they believed they were prescribed medications that were not prescribed). Younger patients were aware of more of their PRN medications than older patients, potentially reflecting greater patient care involvement in younger generations. However, study patients, regardless of age, were able to name fewer than one‐half of their PRN hospital medications. The most common scheduled hospital medications that patients were unable to name come from medication classes which can be associated with significant adverse events, including antibiotics, cardiovascular medications, and antithrombotics.

We posit that without systematically educating patients about their hospital medications, significant deficits in patient knowledge are inevitable. Some might argue that patients should not be asked to know their hospital medications or identify medication errors while sick and vulnerable. Certainly with multiple medication changes, formulary substitutions, and frequent modifications based on changes in clinical status, inpatient medication education could be time consuming and potentially introduce patient confusion or anxiety. Incorrect patient feedback could have potential to introduce new errors. An educational program might use graded participation based on patient interest and ability. Models for this exist in the literature, even extending to patient medication self‐administration.57 In our sample of inpatients, the majority desired a more active role in learning about their hospital medications and believed that their involvement might prevent hospital medication errors from occurring.

Medication literacy, education, and active patient involvement in medication monitoring as a means to improve patient outcomes has received significant attention in the outpatient setting, with lessons applicable to the hospital.8, 9 More broadly, the Joint Commission has established a Hospital National Patient Safety Goal to encourage patients' active involvement in their own care as a patient safety strategy.10 Examples set forth by the Joint Commission include involving patients in infection control measures, marking of procedural sites, and reporting of safety concerns relating to treatment.

While this study identifies patient knowledge deficit as a barrier to utilizing patients as part of the hospital medication safety process, it does not test whether reducing this knowledge deficit would actually reduce medication error. Our study population was limited to cognitively intact adult medicine patients at a single institution, limiting the generalizability of our conclusions. Our enrollment process may have resulted in a study population with less serious illness, greater knowledge of their hospital medications, and greater interest in participating in medication safety potentially overestimating patient knowledge of hospital medications. Finally, our small sample size limits the power to find differences in study comparisons.

Our findings are striking in that we found significant deficits in patient understanding of their hospital medications even among patients who believed they knew, or desired to know, what is being prescribed to them in the hospital. Without a system to incorporate the patient into hospital medication management, these patients will be disenfranchised from participating in inpatient medication safety. These results are a call to reexamine how we educate and involve patients regarding hospital medications. Mechanisms to allow patients to provide feedback to the medical team on their hospital medications might identify errors or improve patient satisfaction with their care. However, the systems and cultural changes needed to provide education on inpatient medications are considerable. Future research is needed to determine if increasing patient knowledge regarding their hospital medications would reduce medication errors in the inpatient setting and how this could be effectively implemented.

Inpatient medication errors represent an important patient safety issue. The magnitude of the problem is staggering, with 1 review finding almost 1 in every 5 medication doses in error, with 7% having potential for adverse drug events.1 While mistakes made at the ordering stage are frequently intercepted by pharmacist or nursing review, administration errors are particularly difficult to prevent.2 The patient, as the last link in the medication administration chain, represents the final individual capable of preventing an incorrect medication administration. It is perhaps surprising then that patients generally lack a formal role in detecting and preventing adverse medication administration events.3

There have been some ambitious attempts to improve patient education regarding hospital medications and involve selected patients in the medication administration process. Such initiatives may result in increased patient participation and satisfaction.47 There is also potential that increased patient knowledge of their hospital medications could promote the goal of medication safety, as the actively involved patient may be able to catch medication errors in the hospital.

Knowledge of prescribed medications is a prerequisite to patient involvement in prevention of inpatient medication errors and yet there is little research on patient knowledge of their hospital medications. Furthermore, as the experience of hospitalization may be disorienting and disempowering for patients, it remains to be seen if patient attitudes toward participation in inpatient medication safety are favorable. To that end, we conducted a pilot study in which we assessed current patient awareness of their in‐hospital medications and surveyed attitudes toward increased patient knowledge of hospital medications.

PATIENTS AND METHODS

We conducted a cross‐sectional study of 50 cognitively intact adult internal medicine inpatients at the University of Colorado Hospital, a tertiary‐care academic teaching hospital. This study was part of a larger project designed to examine potential for patient involvement in the medication reconciliation process. A professional research assistant approached eligible patients within 24 hours of admission. To be eligible, patients had to self‐identify as knowing their outpatient medications, speak English, and have been admitted from the community. Nursing home residents and patients with a past medical history of dementia were excluded. Enrollment was tracked during the first half of the study to estimate effect of inclusion/exclusion criteria. Thirty‐eight percent of hospital admissions to medicine services were excluded based on the specified criteria. Thirty‐four percent of eligible patients were approached and 50% of approached patients agreed to participate in the study. Patient knowledge of their outpatient medication regimen was compared to admitting physician medication reconciliation to assess accuracy of patient self‐report of outpatient medication knowledge.

After consenting to participate, study patients completed a structured list of their outpatient medications and a survey of attitudes about being shown their in‐hospital medications, hospital medication errors, and patient involvement in hospital safety. They then completed a list of the medications they believed to be prescribed to them in the hospital.

The primary outcomes were the proportions of as needed (PRN), scheduled, and total hospital medications omitted by the patient, compared to the inpatient medication administration record (MAR) (patient errors of omission). Secondary outcomes included the number of in‐hospital medications listed by the patient that did not appear on the inpatient MAR (patient errors of commission), as well as patient attitudes measured on a 5‐point Likert scale (1 indicated strongly disagree and 5 indicated strongly agree.) Descriptive data included age, race, gender, and number of inpatient medications prescribed. Separate analysis of variance (ANOVA) models provided mean estimates of the primary outcomes and tested differences according to each of the patient characteristics: age in years (<65 or 65), self‐reported knowledge of hospital medications, and self‐reported desire to be involved in medication safety. Similar ANOVA models adjusted for number of medications were also examined to determine whether the relationship between the primary outcomes according to patient characteristics were altered by the number of medications. The protocol was approved by the Colorado Multiple Institutional Review Board.

RESULTS

Participants averaged 54 years of age (standard deviation [SD] = 17, range = 21‐89). Forty‐six percent (23/50) were male, and 74% (37/50) were non‐Hispanic white. Using a structured, patient‐completed, outpatient medication list, patients in the study were on an average of 5.3 outpatient prescription medications (range = 0‐17), 2.2 over‐the‐counter medications (range = 0‐8), and 0.2 herbal medications (range = 0‐7). The admitting physician's medication reconciliation list demonstrated similar number of outpatient prescription medications (average = 5.7) to the patient‐generated list. Fifty‐four percent of patient‐completed home medication lists included all of the prescription medications on the physician's medication reconciliation at admission. According to the inpatient MAR, study patients were prescribed an average of 11.3 scheduled and PRN hospital medications (range = 2‐26) at time of study enrollment.

Patient Knowledge of Their Hospital Medication List

Ninety‐six percent (48/50) of study patients omitted 1 or more of their hospital medications. On average, patients omitted 6.8 medications (range = 0‐22) (Table 1). Among scheduled medications, patients most commonly omitted antibiotics (17%), cardiovascular medications (16%), and antithrombotics (15%) (Figure 1). Among PRN medications, patients most commonly omitted analgesics (33%) and gastrointestinal medications (29%) (Figure 2).

Table 1.Patient Knowledge of Their Hospital Medications List

	Total Medications	Scheduled Medications	PRN Medications
NOTE: n = 50 patients. Abbreviations: CI, confidence interval; PRN, as needed.
Percent of patients with at least 1 hospital medication they could not name (95% CI)	96% (90‐100%)	94% (87‐100%)	80% (69‐92%)
Average number of hospital medications omitted by patient (range)	6.8 (0‐22)	5.2 (0‐15)	1.6 (0‐7)
Percentage of hospital medications omitted by patient (95% CI)	60% (52‐67%)	60% (52‐67%)	68% (57‐78%)

Figure 1

Figure 2

Patients less than 65 years omitted 60% of their PRN medications whereas patients greater than 65 years omitted 88% (P = 0.01). This difference remained even after adjustment for number of medications. There were no significant differences, based on age, in ability to name scheduled or total medications. Forty‐four percent of patients (22/50) believed they were receiving a medication in the hospital that was not actually prescribed.

DISCUSSION

Overall, patients in the study were able to name fewer than one‐half of their hospital medications. Our study suggests that adult medicine inpatients believe learning about their hospital medications would increase their satisfaction and has potential to promote medication safety. At the same time, patients did not know many of their hospital medications and this would limit their ability to fully participate in the medication safety process. Study patients frequently committed both errors of omission (ie, they did not know which medications were prescribed), and errors of commission (ie, they believed they were prescribed medications that were not prescribed). Younger patients were aware of more of their PRN medications than older patients, potentially reflecting greater patient care involvement in younger generations. However, study patients, regardless of age, were able to name fewer than one‐half of their PRN hospital medications. The most common scheduled hospital medications that patients were unable to name come from medication classes which can be associated with significant adverse events, including antibiotics, cardiovascular medications, and antithrombotics.

We posit that without systematically educating patients about their hospital medications, significant deficits in patient knowledge are inevitable. Some might argue that patients should not be asked to know their hospital medications or identify medication errors while sick and vulnerable. Certainly with multiple medication changes, formulary substitutions, and frequent modifications based on changes in clinical status, inpatient medication education could be time consuming and potentially introduce patient confusion or anxiety. Incorrect patient feedback could have potential to introduce new errors. An educational program might use graded participation based on patient interest and ability. Models for this exist in the literature, even extending to patient medication self‐administration.57 In our sample of inpatients, the majority desired a more active role in learning about their hospital medications and believed that their involvement might prevent hospital medication errors from occurring.

Medication literacy, education, and active patient involvement in medication monitoring as a means to improve patient outcomes has received significant attention in the outpatient setting, with lessons applicable to the hospital.8, 9 More broadly, the Joint Commission has established a Hospital National Patient Safety Goal to encourage patients' active involvement in their own care as a patient safety strategy.10 Examples set forth by the Joint Commission include involving patients in infection control measures, marking of procedural sites, and reporting of safety concerns relating to treatment.

While this study identifies patient knowledge deficit as a barrier to utilizing patients as part of the hospital medication safety process, it does not test whether reducing this knowledge deficit would actually reduce medication error. Our study population was limited to cognitively intact adult medicine patients at a single institution, limiting the generalizability of our conclusions. Our enrollment process may have resulted in a study population with less serious illness, greater knowledge of their hospital medications, and greater interest in participating in medication safety potentially overestimating patient knowledge of hospital medications. Finally, our small sample size limits the power to find differences in study comparisons.

Our findings are striking in that we found significant deficits in patient understanding of their hospital medications even among patients who believed they knew, or desired to know, what is being prescribed to them in the hospital. Without a system to incorporate the patient into hospital medication management, these patients will be disenfranchised from participating in inpatient medication safety. These results are a call to reexamine how we educate and involve patients regarding hospital medications. Mechanisms to allow patients to provide feedback to the medical team on their hospital medications might identify errors or improve patient satisfaction with their care. However, the systems and cultural changes needed to provide education on inpatient medications are considerable. Future research is needed to determine if increasing patient knowledge regarding their hospital medications would reduce medication errors in the inpatient setting and how this could be effectively implemented.

Inpatient medication errors represent an important patient safety issue. The magnitude of the problem is staggering, with 1 review finding almost 1 in every 5 medication doses in error, with 7% having potential for adverse drug events.1 While mistakes made at the ordering stage are frequently intercepted by pharmacist or nursing review, administration errors are particularly difficult to prevent.2 The patient, as the last link in the medication administration chain, represents the final individual capable of preventing an incorrect medication administration. It is perhaps surprising then that patients generally lack a formal role in detecting and preventing adverse medication administration events.3

There have been some ambitious attempts to improve patient education regarding hospital medications and involve selected patients in the medication administration process. Such initiatives may result in increased patient participation and satisfaction.47 There is also potential that increased patient knowledge of their hospital medications could promote the goal of medication safety, as the actively involved patient may be able to catch medication errors in the hospital.

Knowledge of prescribed medications is a prerequisite to patient involvement in prevention of inpatient medication errors and yet there is little research on patient knowledge of their hospital medications. Furthermore, as the experience of hospitalization may be disorienting and disempowering for patients, it remains to be seen if patient attitudes toward participation in inpatient medication safety are favorable. To that end, we conducted a pilot study in which we assessed current patient awareness of their in‐hospital medications and surveyed attitudes toward increased patient knowledge of hospital medications.

PATIENTS AND METHODS

We conducted a cross‐sectional study of 50 cognitively intact adult internal medicine inpatients at the University of Colorado Hospital, a tertiary‐care academic teaching hospital. This study was part of a larger project designed to examine potential for patient involvement in the medication reconciliation process. A professional research assistant approached eligible patients within 24 hours of admission. To be eligible, patients had to self‐identify as knowing their outpatient medications, speak English, and have been admitted from the community. Nursing home residents and patients with a past medical history of dementia were excluded. Enrollment was tracked during the first half of the study to estimate effect of inclusion/exclusion criteria. Thirty‐eight percent of hospital admissions to medicine services were excluded based on the specified criteria. Thirty‐four percent of eligible patients were approached and 50% of approached patients agreed to participate in the study. Patient knowledge of their outpatient medication regimen was compared to admitting physician medication reconciliation to assess accuracy of patient self‐report of outpatient medication knowledge.

After consenting to participate, study patients completed a structured list of their outpatient medications and a survey of attitudes about being shown their in‐hospital medications, hospital medication errors, and patient involvement in hospital safety. They then completed a list of the medications they believed to be prescribed to them in the hospital.

The primary outcomes were the proportions of as needed (PRN), scheduled, and total hospital medications omitted by the patient, compared to the inpatient medication administration record (MAR) (patient errors of omission). Secondary outcomes included the number of in‐hospital medications listed by the patient that did not appear on the inpatient MAR (patient errors of commission), as well as patient attitudes measured on a 5‐point Likert scale (1 indicated strongly disagree and 5 indicated strongly agree.) Descriptive data included age, race, gender, and number of inpatient medications prescribed. Separate analysis of variance (ANOVA) models provided mean estimates of the primary outcomes and tested differences according to each of the patient characteristics: age in years (<65 or 65), self‐reported knowledge of hospital medications, and self‐reported desire to be involved in medication safety. Similar ANOVA models adjusted for number of medications were also examined to determine whether the relationship between the primary outcomes according to patient characteristics were altered by the number of medications. The protocol was approved by the Colorado Multiple Institutional Review Board.

RESULTS

Participants averaged 54 years of age (standard deviation [SD] = 17, range = 21‐89). Forty‐six percent (23/50) were male, and 74% (37/50) were non‐Hispanic white. Using a structured, patient‐completed, outpatient medication list, patients in the study were on an average of 5.3 outpatient prescription medications (range = 0‐17), 2.2 over‐the‐counter medications (range = 0‐8), and 0.2 herbal medications (range = 0‐7). The admitting physician's medication reconciliation list demonstrated similar number of outpatient prescription medications (average = 5.7) to the patient‐generated list. Fifty‐four percent of patient‐completed home medication lists included all of the prescription medications on the physician's medication reconciliation at admission. According to the inpatient MAR, study patients were prescribed an average of 11.3 scheduled and PRN hospital medications (range = 2‐26) at time of study enrollment.

Patient Knowledge of Their Hospital Medication List

Ninety‐six percent (48/50) of study patients omitted 1 or more of their hospital medications. On average, patients omitted 6.8 medications (range = 0‐22) (Table 1). Among scheduled medications, patients most commonly omitted antibiotics (17%), cardiovascular medications (16%), and antithrombotics (15%) (Figure 1). Among PRN medications, patients most commonly omitted analgesics (33%) and gastrointestinal medications (29%) (Figure 2).

Table 1.Patient Knowledge of Their Hospital Medications List

	Total Medications	Scheduled Medications	PRN Medications
NOTE: n = 50 patients. Abbreviations: CI, confidence interval; PRN, as needed.
Percent of patients with at least 1 hospital medication they could not name (95% CI)	96% (90‐100%)	94% (87‐100%)	80% (69‐92%)
Average number of hospital medications omitted by patient (range)	6.8 (0‐22)	5.2 (0‐15)	1.6 (0‐7)
Percentage of hospital medications omitted by patient (95% CI)	60% (52‐67%)	60% (52‐67%)	68% (57‐78%)

Figure 1

Figure 2

Patients less than 65 years omitted 60% of their PRN medications whereas patients greater than 65 years omitted 88% (P = 0.01). This difference remained even after adjustment for number of medications. There were no significant differences, based on age, in ability to name scheduled or total medications. Forty‐four percent of patients (22/50) believed they were receiving a medication in the hospital that was not actually prescribed.

DISCUSSION

Overall, patients in the study were able to name fewer than one‐half of their hospital medications. Our study suggests that adult medicine inpatients believe learning about their hospital medications would increase their satisfaction and has potential to promote medication safety. At the same time, patients did not know many of their hospital medications and this would limit their ability to fully participate in the medication safety process. Study patients frequently committed both errors of omission (ie, they did not know which medications were prescribed), and errors of commission (ie, they believed they were prescribed medications that were not prescribed). Younger patients were aware of more of their PRN medications than older patients, potentially reflecting greater patient care involvement in younger generations. However, study patients, regardless of age, were able to name fewer than one‐half of their PRN hospital medications. The most common scheduled hospital medications that patients were unable to name come from medication classes which can be associated with significant adverse events, including antibiotics, cardiovascular medications, and antithrombotics.

We posit that without systematically educating patients about their hospital medications, significant deficits in patient knowledge are inevitable. Some might argue that patients should not be asked to know their hospital medications or identify medication errors while sick and vulnerable. Certainly with multiple medication changes, formulary substitutions, and frequent modifications based on changes in clinical status, inpatient medication education could be time consuming and potentially introduce patient confusion or anxiety. Incorrect patient feedback could have potential to introduce new errors. An educational program might use graded participation based on patient interest and ability. Models for this exist in the literature, even extending to patient medication self‐administration.57 In our sample of inpatients, the majority desired a more active role in learning about their hospital medications and believed that their involvement might prevent hospital medication errors from occurring.

Medication literacy, education, and active patient involvement in medication monitoring as a means to improve patient outcomes has received significant attention in the outpatient setting, with lessons applicable to the hospital.8, 9 More broadly, the Joint Commission has established a Hospital National Patient Safety Goal to encourage patients' active involvement in their own care as a patient safety strategy.10 Examples set forth by the Joint Commission include involving patients in infection control measures, marking of procedural sites, and reporting of safety concerns relating to treatment.

While this study identifies patient knowledge deficit as a barrier to utilizing patients as part of the hospital medication safety process, it does not test whether reducing this knowledge deficit would actually reduce medication error. Our study population was limited to cognitively intact adult medicine patients at a single institution, limiting the generalizability of our conclusions. Our enrollment process may have resulted in a study population with less serious illness, greater knowledge of their hospital medications, and greater interest in participating in medication safety potentially overestimating patient knowledge of hospital medications. Finally, our small sample size limits the power to find differences in study comparisons.

Our findings are striking in that we found significant deficits in patient understanding of their hospital medications even among patients who believed they knew, or desired to know, what is being prescribed to them in the hospital. Without a system to incorporate the patient into hospital medication management, these patients will be disenfranchised from participating in inpatient medication safety. These results are a call to reexamine how we educate and involve patients regarding hospital medications. Mechanisms to allow patients to provide feedback to the medical team on their hospital medications might identify errors or improve patient satisfaction with their care. However, the systems and cultural changes needed to provide education on inpatient medications are considerable. Future research is needed to determine if increasing patient knowledge regarding their hospital medications would reduce medication errors in the inpatient setting and how this could be effectively implemented.