The Hospital Readmission Reduction Program (HRRP)[1] contained within the Affordable Care Act focused national and local attention on hospital resources and efforts to reduce hospital readmissions. Driven by the Centers for Medicare and Medicaid Services' (CMS) desire to pay for value instead of volume, the response of hospitals and health systems appears to be yielding change across the United States.[2] A number of recent publications in the Journal of Hospital Medicine (JHM) exemplify the keen interest in reducing readmissions, while providing guidance regarding interventions and where we might target future research. Evidence from an exemplary systematic review of the pediatric literature confirms some experience in adults regarding effective interventionsall studies were multifacetedand highlights the importance of identifying a single healthcare provider or centrally coordinated hub to assume responsibility for extended care transition and follow‐up.[3] Notably, studies of pediatric patients and their families document the effectiveness of enhanced inpatient education and engagement while in the hospital.[3] Unfortunately, a study among adults at a top‐ranked academic institution indicates poor communication among nurses and physicians regarding patient discharge education.[4] Efforts to improve nursephysician communication by redesigning the hospitalist model of care delivery at a Veterans Affairs (VA) institution appeared to enhance perceptions of communication among the care team members and reduced length of stay, but disappointingly there was no reduction in readmission rates.[5] Studies such as this are essential in identifying which specific interventions may actually change outcomes such as readmission rates.

In 1984, a diminutive elderly woman provocatively squawked Where's the beef?, launching a highly successful advertising campaign for Wendy's hamburger chain.[6] This catchphrase may aptly describe Bradley and colleague's survey study of the State Action on Avoidable Rehospitalization (STAAR) and Hospital‐to‐Home (H2H) campaigns.[7] Auerbach and colleagues eloquently stated in a 2007 New England Journal of Medicine perspective[8] how they had witnessed recent initiatives that emphasize dissemination of innovative but unproven strategies, an approach that runs counter to the principle of following the evidence[9] in selecting interventions that meet quality and safety goals.[10] I firmly agree with this assessment, and 6 years later believe we should be more thoughtful about potentially repeating implementation of unproven strategies.

Do we know if the interventions recommended by H2H and STAAR are what hospital care teams should be attempting? Even the authors mention that definitive evidence on their effectiveness is lacking. The H2H and STAAR programs certainly encourage some theoretically laudable activitiesmedication reconciliation by nurses, alerting outpatient physicians within 48 hours of patient discharge, and providing skilled nursing facilities the direct contact number of the inpatient treating physician for patients transferred. However, do these efforts actually improve patient outcomes? Before embarking on state or national campaigns to improve care, we should consider carefully what are the best evidence‐based interventions. Remarkably, some prior evidence indicates that direct communication between the hospital‐based physician and primary care provider (PCP) may not actually impact patient outcomes.[11] Newer research published in JHM confirms my belief that the PCP needs to be engaged by hospitalists during a hospitalization. Lindquist's research group at Northwestern nicely demonstrated how communication between a patient's PCP and the admitting hospitalist, complemented by contact between the PCP and patient within 24 hours postdischarge, reduced the probability of a medication discrepancy by 70%.[12] Although no evaluation of the effect on readmissions was reported, this study may provide information on causality related to the importance of PCP involvement in the care of hospitalized patients.

Numerous publications now document research on successfully implemented programs that lowered hospital readmissions, and are cited by CMS as evidence‐based interventions.[13] Projects Re‐Engineered Discharge (RED)[14] and Better Outcomes by Optimizing Safe Transitions[15] target the hospital discharge process, and both appear to lower hospital readmission rates. The Care Transitions Intervention (CTI),[16] Transitional Care Model (TCM),[17] and the Guided Care model[18] all leverage nurse practitioners or nurses to protect elderly patients during what can be a perilous care transition from hospital to home. CTI and TCM have been further validated in effectiveness studies.[19, 20] Two recent systematic reviews provide further insight into the complexity of efforts to reduce 30‐day rehospitalizations, but unfortunately do not reveal a desired silver bullet. The first focused exclusively on interventions to reduce 30‐day rehospitalization, and concluded that no single intervention was successful alone, but identified interventions bridging the hospital‐to‐home transition (eg, CTI), and a bundle of interventions such as Project RED as showing efficacy.[21] The second review more broadly sought to evaluate the effectiveness of hospital‐initiated strategies to prevent postdischarge adverse events (AEs) such as readmissions and emergency department visits,[22] stating Because of scant evidence, no conclusions could be reached on methods to prevent postdischarge AEs. The researchers' sobering conclusion stated that strategies to improve patient safety at hospital discharge remain unclear.

With rising federal penalties for higher‐than‐expected readmission rates, many hospital leaders eagerly join collaboratives aiming to reduce hospital readmissions. H2H appears to be among the largest, reporting >600 hospital participants, and STAAR has been active since 2009, with a recently published qualitative study identifying gaps in evidence for effective interventions, and deficits in quality improvement capabilities among some organizations as implementation challenges.[23] Notably, the survey by Bradley and colleagues documented that just half of the hospitals had a quality improvement (QI) team focused on reducing readmissions. Although laudable in their goals, H2H and STAAR may represent expensive commitments of staff and time to efforts that may not improve outcomes. Importantly, recently published research evaluating QI studies showed concerning results among patients with chronic obstructive pulmonary disease (COPD). A randomized controlled trial (RCT) conducted at 6 Glasgow hospitals evaluated supported self‐management (home visits by nurses and thorough education) by patients with moderate to severe COPD, but documented no changes in hospitalization or mortality.[24]Another RCT at 20 sites evaluated a comprehensive care management program to prevent hospitalizations among 960 VA patients with COPD.[25] It had to be stopped early due to elevated all‐cause mortality in the intervention group, and there was no difference in hospitalization rates.

Moving forward, QI efforts to reduce hospital readmissions should utilize proven interventions unless they are part of a rigorous trial. The emerging field of implementation science (the scientific study of methods to promote the systematic uptake of research findings and other evidence‐based practices into routine practice, and hence, to improve the quality and effectiveness of health services[26]) needs to be applied to additional research in this area.[27] Another consideration would be for CMS and funders such as the Commonwealth Foundation or The Robert Wood Johnson Foundation to encourage and fund merging of current initiatives to move away from competition and provide clarity to community hospitals. Regardless, such collaboration should still undertake formal evaluation to discern best approaches to implementation. I applaud the authors for recognizing that Input from hospitalists who are often critical links among inpatient and outpatient care and between patients and their families is strongly needed to ensure hospitals focus on what strategies are most effective for successful transitions from hospital to home. Yet, I wonder why neither of the large STAAR and H2H initiatives actively partnered with hospitalists and their specialty society (Society of Hospital Medicine) directly in the leadership of these initiatives? On the other hand, why not ask medical societies engaged in delivery of primary care (eg, American Academy for Family Practice, American College of Physicians, or Society of General Internal Medicine), especially to elderly patients (American Geriatric Society), to contribute directly? Involvement on an advisory board is likely not sufficient. Prior efforts document the willingness of these organizations to collaborate and achieve consensus on principles for transitions of care.[28] As powerfully articulated 6 years ago, [W]e must pursue the solutions to quality and safety problems in a way that does not blind us to harms, squander scarce resources, or delude us about the effectiveness of our efforts.[8]

The Hospital Readmission Reduction Program (HRRP)[1] contained within the Affordable Care Act focused national and local attention on hospital resources and efforts to reduce hospital readmissions. Driven by the Centers for Medicare and Medicaid Services' (CMS) desire to pay for value instead of volume, the response of hospitals and health systems appears to be yielding change across the United States.[2] A number of recent publications in the Journal of Hospital Medicine (JHM) exemplify the keen interest in reducing readmissions, while providing guidance regarding interventions and where we might target future research. Evidence from an exemplary systematic review of the pediatric literature confirms some experience in adults regarding effective interventionsall studies were multifacetedand highlights the importance of identifying a single healthcare provider or centrally coordinated hub to assume responsibility for extended care transition and follow‐up.[3] Notably, studies of pediatric patients and their families document the effectiveness of enhanced inpatient education and engagement while in the hospital.[3] Unfortunately, a study among adults at a top‐ranked academic institution indicates poor communication among nurses and physicians regarding patient discharge education.[4] Efforts to improve nursephysician communication by redesigning the hospitalist model of care delivery at a Veterans Affairs (VA) institution appeared to enhance perceptions of communication among the care team members and reduced length of stay, but disappointingly there was no reduction in readmission rates.[5] Studies such as this are essential in identifying which specific interventions may actually change outcomes such as readmission rates.

In 1984, a diminutive elderly woman provocatively squawked Where's the beef?, launching a highly successful advertising campaign for Wendy's hamburger chain.[6] This catchphrase may aptly describe Bradley and colleague's survey study of the State Action on Avoidable Rehospitalization (STAAR) and Hospital‐to‐Home (H2H) campaigns.[7] Auerbach and colleagues eloquently stated in a 2007 New England Journal of Medicine perspective[8] how they had witnessed recent initiatives that emphasize dissemination of innovative but unproven strategies, an approach that runs counter to the principle of following the evidence[9] in selecting interventions that meet quality and safety goals.[10] I firmly agree with this assessment, and 6 years later believe we should be more thoughtful about potentially repeating implementation of unproven strategies.

Do we know if the interventions recommended by H2H and STAAR are what hospital care teams should be attempting? Even the authors mention that definitive evidence on their effectiveness is lacking. The H2H and STAAR programs certainly encourage some theoretically laudable activitiesmedication reconciliation by nurses, alerting outpatient physicians within 48 hours of patient discharge, and providing skilled nursing facilities the direct contact number of the inpatient treating physician for patients transferred. However, do these efforts actually improve patient outcomes? Before embarking on state or national campaigns to improve care, we should consider carefully what are the best evidence‐based interventions. Remarkably, some prior evidence indicates that direct communication between the hospital‐based physician and primary care provider (PCP) may not actually impact patient outcomes.[11] Newer research published in JHM confirms my belief that the PCP needs to be engaged by hospitalists during a hospitalization. Lindquist's research group at Northwestern nicely demonstrated how communication between a patient's PCP and the admitting hospitalist, complemented by contact between the PCP and patient within 24 hours postdischarge, reduced the probability of a medication discrepancy by 70%.[12] Although no evaluation of the effect on readmissions was reported, this study may provide information on causality related to the importance of PCP involvement in the care of hospitalized patients.

Numerous publications now document research on successfully implemented programs that lowered hospital readmissions, and are cited by CMS as evidence‐based interventions.[13] Projects Re‐Engineered Discharge (RED)[14] and Better Outcomes by Optimizing Safe Transitions[15] target the hospital discharge process, and both appear to lower hospital readmission rates. The Care Transitions Intervention (CTI),[16] Transitional Care Model (TCM),[17] and the Guided Care model[18] all leverage nurse practitioners or nurses to protect elderly patients during what can be a perilous care transition from hospital to home. CTI and TCM have been further validated in effectiveness studies.[19, 20] Two recent systematic reviews provide further insight into the complexity of efforts to reduce 30‐day rehospitalizations, but unfortunately do not reveal a desired silver bullet. The first focused exclusively on interventions to reduce 30‐day rehospitalization, and concluded that no single intervention was successful alone, but identified interventions bridging the hospital‐to‐home transition (eg, CTI), and a bundle of interventions such as Project RED as showing efficacy.[21] The second review more broadly sought to evaluate the effectiveness of hospital‐initiated strategies to prevent postdischarge adverse events (AEs) such as readmissions and emergency department visits,[22] stating Because of scant evidence, no conclusions could be reached on methods to prevent postdischarge AEs. The researchers' sobering conclusion stated that strategies to improve patient safety at hospital discharge remain unclear.

With rising federal penalties for higher‐than‐expected readmission rates, many hospital leaders eagerly join collaboratives aiming to reduce hospital readmissions. H2H appears to be among the largest, reporting >600 hospital participants, and STAAR has been active since 2009, with a recently published qualitative study identifying gaps in evidence for effective interventions, and deficits in quality improvement capabilities among some organizations as implementation challenges.[23] Notably, the survey by Bradley and colleagues documented that just half of the hospitals had a quality improvement (QI) team focused on reducing readmissions. Although laudable in their goals, H2H and STAAR may represent expensive commitments of staff and time to efforts that may not improve outcomes. Importantly, recently published research evaluating QI studies showed concerning results among patients with chronic obstructive pulmonary disease (COPD). A randomized controlled trial (RCT) conducted at 6 Glasgow hospitals evaluated supported self‐management (home visits by nurses and thorough education) by patients with moderate to severe COPD, but documented no changes in hospitalization or mortality.[24]Another RCT at 20 sites evaluated a comprehensive care management program to prevent hospitalizations among 960 VA patients with COPD.[25] It had to be stopped early due to elevated all‐cause mortality in the intervention group, and there was no difference in hospitalization rates.

Moving forward, QI efforts to reduce hospital readmissions should utilize proven interventions unless they are part of a rigorous trial. The emerging field of implementation science (the scientific study of methods to promote the systematic uptake of research findings and other evidence‐based practices into routine practice, and hence, to improve the quality and effectiveness of health services[26]) needs to be applied to additional research in this area.[27] Another consideration would be for CMS and funders such as the Commonwealth Foundation or The Robert Wood Johnson Foundation to encourage and fund merging of current initiatives to move away from competition and provide clarity to community hospitals. Regardless, such collaboration should still undertake formal evaluation to discern best approaches to implementation. I applaud the authors for recognizing that Input from hospitalists who are often critical links among inpatient and outpatient care and between patients and their families is strongly needed to ensure hospitals focus on what strategies are most effective for successful transitions from hospital to home. Yet, I wonder why neither of the large STAAR and H2H initiatives actively partnered with hospitalists and their specialty society (Society of Hospital Medicine) directly in the leadership of these initiatives? On the other hand, why not ask medical societies engaged in delivery of primary care (eg, American Academy for Family Practice, American College of Physicians, or Society of General Internal Medicine), especially to elderly patients (American Geriatric Society), to contribute directly? Involvement on an advisory board is likely not sufficient. Prior efforts document the willingness of these organizations to collaborate and achieve consensus on principles for transitions of care.[28] As powerfully articulated 6 years ago, [W]e must pursue the solutions to quality and safety problems in a way that does not blind us to harms, squander scarce resources, or delude us about the effectiveness of our efforts.[8]

The Hospital Readmission Reduction Program (HRRP)[1] contained within the Affordable Care Act focused national and local attention on hospital resources and efforts to reduce hospital readmissions. Driven by the Centers for Medicare and Medicaid Services' (CMS) desire to pay for value instead of volume, the response of hospitals and health systems appears to be yielding change across the United States.[2] A number of recent publications in the Journal of Hospital Medicine (JHM) exemplify the keen interest in reducing readmissions, while providing guidance regarding interventions and where we might target future research. Evidence from an exemplary systematic review of the pediatric literature confirms some experience in adults regarding effective interventionsall studies were multifacetedand highlights the importance of identifying a single healthcare provider or centrally coordinated hub to assume responsibility for extended care transition and follow‐up.[3] Notably, studies of pediatric patients and their families document the effectiveness of enhanced inpatient education and engagement while in the hospital.[3] Unfortunately, a study among adults at a top‐ranked academic institution indicates poor communication among nurses and physicians regarding patient discharge education.[4] Efforts to improve nursephysician communication by redesigning the hospitalist model of care delivery at a Veterans Affairs (VA) institution appeared to enhance perceptions of communication among the care team members and reduced length of stay, but disappointingly there was no reduction in readmission rates.[5] Studies such as this are essential in identifying which specific interventions may actually change outcomes such as readmission rates.

In 1984, a diminutive elderly woman provocatively squawked Where's the beef?, launching a highly successful advertising campaign for Wendy's hamburger chain.[6] This catchphrase may aptly describe Bradley and colleague's survey study of the State Action on Avoidable Rehospitalization (STAAR) and Hospital‐to‐Home (H2H) campaigns.[7] Auerbach and colleagues eloquently stated in a 2007 New England Journal of Medicine perspective[8] how they had witnessed recent initiatives that emphasize dissemination of innovative but unproven strategies, an approach that runs counter to the principle of following the evidence[9] in selecting interventions that meet quality and safety goals.[10] I firmly agree with this assessment, and 6 years later believe we should be more thoughtful about potentially repeating implementation of unproven strategies.

Do we know if the interventions recommended by H2H and STAAR are what hospital care teams should be attempting? Even the authors mention that definitive evidence on their effectiveness is lacking. The H2H and STAAR programs certainly encourage some theoretically laudable activitiesmedication reconciliation by nurses, alerting outpatient physicians within 48 hours of patient discharge, and providing skilled nursing facilities the direct contact number of the inpatient treating physician for patients transferred. However, do these efforts actually improve patient outcomes? Before embarking on state or national campaigns to improve care, we should consider carefully what are the best evidence‐based interventions. Remarkably, some prior evidence indicates that direct communication between the hospital‐based physician and primary care provider (PCP) may not actually impact patient outcomes.[11] Newer research published in JHM confirms my belief that the PCP needs to be engaged by hospitalists during a hospitalization. Lindquist's research group at Northwestern nicely demonstrated how communication between a patient's PCP and the admitting hospitalist, complemented by contact between the PCP and patient within 24 hours postdischarge, reduced the probability of a medication discrepancy by 70%.[12] Although no evaluation of the effect on readmissions was reported, this study may provide information on causality related to the importance of PCP involvement in the care of hospitalized patients.

Numerous publications now document research on successfully implemented programs that lowered hospital readmissions, and are cited by CMS as evidence‐based interventions.[13] Projects Re‐Engineered Discharge (RED)[14] and Better Outcomes by Optimizing Safe Transitions[15] target the hospital discharge process, and both appear to lower hospital readmission rates. The Care Transitions Intervention (CTI),[16] Transitional Care Model (TCM),[17] and the Guided Care model[18] all leverage nurse practitioners or nurses to protect elderly patients during what can be a perilous care transition from hospital to home. CTI and TCM have been further validated in effectiveness studies.[19, 20] Two recent systematic reviews provide further insight into the complexity of efforts to reduce 30‐day rehospitalizations, but unfortunately do not reveal a desired silver bullet. The first focused exclusively on interventions to reduce 30‐day rehospitalization, and concluded that no single intervention was successful alone, but identified interventions bridging the hospital‐to‐home transition (eg, CTI), and a bundle of interventions such as Project RED as showing efficacy.[21] The second review more broadly sought to evaluate the effectiveness of hospital‐initiated strategies to prevent postdischarge adverse events (AEs) such as readmissions and emergency department visits,[22] stating Because of scant evidence, no conclusions could be reached on methods to prevent postdischarge AEs. The researchers' sobering conclusion stated that strategies to improve patient safety at hospital discharge remain unclear.

With rising federal penalties for higher‐than‐expected readmission rates, many hospital leaders eagerly join collaboratives aiming to reduce hospital readmissions. H2H appears to be among the largest, reporting >600 hospital participants, and STAAR has been active since 2009, with a recently published qualitative study identifying gaps in evidence for effective interventions, and deficits in quality improvement capabilities among some organizations as implementation challenges.[23] Notably, the survey by Bradley and colleagues documented that just half of the hospitals had a quality improvement (QI) team focused on reducing readmissions. Although laudable in their goals, H2H and STAAR may represent expensive commitments of staff and time to efforts that may not improve outcomes. Importantly, recently published research evaluating QI studies showed concerning results among patients with chronic obstructive pulmonary disease (COPD). A randomized controlled trial (RCT) conducted at 6 Glasgow hospitals evaluated supported self‐management (home visits by nurses and thorough education) by patients with moderate to severe COPD, but documented no changes in hospitalization or mortality.[24]Another RCT at 20 sites evaluated a comprehensive care management program to prevent hospitalizations among 960 VA patients with COPD.[25] It had to be stopped early due to elevated all‐cause mortality in the intervention group, and there was no difference in hospitalization rates.

Moving forward, QI efforts to reduce hospital readmissions should utilize proven interventions unless they are part of a rigorous trial. The emerging field of implementation science (the scientific study of methods to promote the systematic uptake of research findings and other evidence‐based practices into routine practice, and hence, to improve the quality and effectiveness of health services[26]) needs to be applied to additional research in this area.[27] Another consideration would be for CMS and funders such as the Commonwealth Foundation or The Robert Wood Johnson Foundation to encourage and fund merging of current initiatives to move away from competition and provide clarity to community hospitals. Regardless, such collaboration should still undertake formal evaluation to discern best approaches to implementation. I applaud the authors for recognizing that Input from hospitalists who are often critical links among inpatient and outpatient care and between patients and their families is strongly needed to ensure hospitals focus on what strategies are most effective for successful transitions from hospital to home. Yet, I wonder why neither of the large STAAR and H2H initiatives actively partnered with hospitalists and their specialty society (Society of Hospital Medicine) directly in the leadership of these initiatives? On the other hand, why not ask medical societies engaged in delivery of primary care (eg, American Academy for Family Practice, American College of Physicians, or Society of General Internal Medicine), especially to elderly patients (American Geriatric Society), to contribute directly? Involvement on an advisory board is likely not sufficient. Prior efforts document the willingness of these organizations to collaborate and achieve consensus on principles for transitions of care.[28] As powerfully articulated 6 years ago, [W]e must pursue the solutions to quality and safety problems in a way that does not blind us to harms, squander scarce resources, or delude us about the effectiveness of our efforts.[8]

BACKGROUND

Many hospitals have initiated intense efforts to improve transitions of care[1] such as discharge coordinators or transition coaches,[2, 3] but use of mobile devices as approaches to add or extend the value of human interventions have been understudied.[4] Additionally, many hospitalized patients experience substantial inactive time between provider visits, tests, and treatments. This time could be used to engage patients in their care through interactive health education modules and by learning to use their PHR to manage medications and postdischarge appointments.

Greater understanding of the advantages and limitations of mobile devices may be important for improving transitions of care and may help leverage existing hospital personnel resources. However, prior studies have focused on healthcare provider uses of tablet computers for medical education,[5] to collect clinical registration data,[6] or to do clinical work (eg, check labs, write notes)[7, 8, 9] primarily in outpatient settings; few studies have focused on patient uses for this technology in hospital settings.[10, 11] To address these knowledge gaps, we conducted a pilot project to explore inpatient satisfaction with bedside tablets and barriers to usability. Additionally, we evaluated use of these devices to deliver 2 specific Web‐based programs: (1) an interactive video to improve inpatient education about hospital safety, and (2) PHR access to promote inpatient engagement in discharge planning.

METHODS

RESULTS

As shown in Table 1, we enrolled 30 patients. Most participants (60%) were aged 40 years or older, and most (87%) owned a mobile device; 70% owned a laptop and 60% owned a smartphone, but few (22%) owned a computer tablet. Most participants accessed the Internet daily, but fewer reported Internet use for health tasks; about half (52%) communicated with a provider, but few refilled a prescription (27%) or scheduled an appointment (21%) online over the last year.

Nearly all participants (90%) were satisfied or very satisfied with their experience using the tablet in the hospital (Figure 1). Most (87%) required 30 minutes or less for basic orientation, and 70% required only 15 minutes or less. Most participants (83%) were able to independently complete an interactive health education module on hospital safety and were highly satisfied with the module. Despite the fact that 73% of participants were first‐time users of our PHR, the majority were able to login and independently access their medication list, verify scheduled appointments, or send a secure message to their primary care provider.

Figure 1

Participants aged 50 years or older were less likely to complete orientation in 15 minutes or less compared to those under 50 years old (25% vs 79%, P=0.025); however, age was not a significant factor in ability to complete the online health educational module or perform at least 1 essential PHR function. Other demographic features, such as device ownership and daily Internet use, did not correlate with shorter orientation time, educational module completion, or PHR use (data available on request).

Participants also made suggestions for improvement during the debrief interviews. Several suggested applications for entertainment (gaming, magazines, or music) and 2 suggested that all patients should be introduced to their PHR during hospitalization (data available on request). No device software malfunction (eg, device freezes, Internet connection failures), hardware issues (eg, damage from falls, wetness, or repeated disinfectant exposure), or theft or misappropriation were reported by patients or observed by the RAs to date.

DISCUSSION

Our pilot study suggests that tablet‐based access to educational modules and PHRs can increase inpatient engagement in care with high satisfaction and minimal time for orientation. Surprisingly, even older patients and those who might be considered less tech savvy in terms of Internet use and device ownership were equally able to utilize our tablet interventions. Furthermore, we did not experience any hardware issues in the harsh physical environment of inpatient wards. These preliminary findings suggest the potential utility of tablets for clinically meaningful tasks by inpatients with a low rate of technical issues.

From a technical standpoint, our experience suggests several next steps. First, although orientation time was minimal, it might be even less if patients used their own mobile devices because most patients already owned one. This bring your own device (BYOD) approach could also promote postdischarge patient engagement. Second, the flexibility of a BYOD approach raises the question of whether to also allow patients a choice of application‐based versus browser‐based platforms for specific programs such as the PHR and educational video we used. Indeed, although we used a browser‐based approach, several other teams have developed patient‐facing engagement applications (or apps) for mobile devices,[4, 12] and hospitalists could prescribe apps at discharge as a more providers are now doing in outpatient settings.[13] Of course, maximizing flexibility for BYOD and Web‐based versus app‐based approaches would likely increase patient engagement but would come at the cost of more time and effort for hospital providers to vet apps/websites and educate patients about their use. Third, regardless of the devices and programs used, broader engagement of patients, nurses, hospitalists, and other providers will be needed in the future to identify key areas for development to avoid overburdening patients and providers.

From a quality‐improvement perspective, recent literature has considered broad clinical uses for tablets by hospital providers,[14, 15] but our experience suggests more specific opportunities to improve transitions of care though direct patient engagement. Tablets and other mobile devices may help improve discharge education for patients taking high‐risk medications such as warfarin or insulin using interactive educational modules similar to the hospital safety modules we used. Additionally, clinical staff, such as nurses and pharmacists, can be trained to deliver mobile device interventions such as education on high‐risk medications.[16] Ultimately, scale up for our intervention will require that mobile devices and content eventually improve and replace current practices by hospital staff (especially nurses) in a way that streamlines, rather than compounds, current workflow. This could increase efficiency in these discharge tasks and extend contributions of these providers to high‐quality transitions.

Our study has several limitations. First, although this is a pilot study with only 30 patients, it adds needed scale to much smaller (N=58) published feasibility studies of tablet computer use by inpatients.[11, 12] Beyond more robust feasibility testing, our study adds new data about mobile device use for specific clinical tasks in the hospital such as patient education and PHR use. Second, we did not track postdischarge outcomes to test the effects of our intervention on transition care quality; this will be a focus of our future research. Third, we used existing platforms for interactive educational modules and PHR access at our site; participant satisfaction in our study may not generalize to other platforms. Furthermore, most PHR platforms (including ours) are not optimally configured to engage patients during transitions of care, but we plan to integrate existing functions (such as ability to refill medications or change appointments) into discharge education and planning. Finally, we have not engaged caregivers as surrogates for cognitively impaired patients or adapted our platform for non‐English speakers; these are areas for development in our ongoing work. Overall, our pilot results help set the stage to deploy mobile devices for better patient monitoring, engagement, and quality of care in the inpatient setting.[17]

In conclusion, our pilot project demonstrates that tablet computers can be used to improve inpatient education and patient engagement in discharge planning. Inpatients are highly satisfied with the use of tablets to complete health education modules and access their PHR, with minimal time required for patient training and device management by hospital staff. Tablets and other mobile devices have significant potential to improve patients' education and engagement in their hospital care.

BACKGROUND

Many hospitals have initiated intense efforts to improve transitions of care[1] such as discharge coordinators or transition coaches,[2, 3] but use of mobile devices as approaches to add or extend the value of human interventions have been understudied.[4] Additionally, many hospitalized patients experience substantial inactive time between provider visits, tests, and treatments. This time could be used to engage patients in their care through interactive health education modules and by learning to use their PHR to manage medications and postdischarge appointments.

Greater understanding of the advantages and limitations of mobile devices may be important for improving transitions of care and may help leverage existing hospital personnel resources. However, prior studies have focused on healthcare provider uses of tablet computers for medical education,[5] to collect clinical registration data,[6] or to do clinical work (eg, check labs, write notes)[7, 8, 9] primarily in outpatient settings; few studies have focused on patient uses for this technology in hospital settings.[10, 11] To address these knowledge gaps, we conducted a pilot project to explore inpatient satisfaction with bedside tablets and barriers to usability. Additionally, we evaluated use of these devices to deliver 2 specific Web‐based programs: (1) an interactive video to improve inpatient education about hospital safety, and (2) PHR access to promote inpatient engagement in discharge planning.

METHODS

RESULTS

As shown in Table 1, we enrolled 30 patients. Most participants (60%) were aged 40 years or older, and most (87%) owned a mobile device; 70% owned a laptop and 60% owned a smartphone, but few (22%) owned a computer tablet. Most participants accessed the Internet daily, but fewer reported Internet use for health tasks; about half (52%) communicated with a provider, but few refilled a prescription (27%) or scheduled an appointment (21%) online over the last year.

Nearly all participants (90%) were satisfied or very satisfied with their experience using the tablet in the hospital (Figure 1). Most (87%) required 30 minutes or less for basic orientation, and 70% required only 15 minutes or less. Most participants (83%) were able to independently complete an interactive health education module on hospital safety and were highly satisfied with the module. Despite the fact that 73% of participants were first‐time users of our PHR, the majority were able to login and independently access their medication list, verify scheduled appointments, or send a secure message to their primary care provider.

Figure 1

Participants aged 50 years or older were less likely to complete orientation in 15 minutes or less compared to those under 50 years old (25% vs 79%, P=0.025); however, age was not a significant factor in ability to complete the online health educational module or perform at least 1 essential PHR function. Other demographic features, such as device ownership and daily Internet use, did not correlate with shorter orientation time, educational module completion, or PHR use (data available on request).

Participants also made suggestions for improvement during the debrief interviews. Several suggested applications for entertainment (gaming, magazines, or music) and 2 suggested that all patients should be introduced to their PHR during hospitalization (data available on request). No device software malfunction (eg, device freezes, Internet connection failures), hardware issues (eg, damage from falls, wetness, or repeated disinfectant exposure), or theft or misappropriation were reported by patients or observed by the RAs to date.

DISCUSSION

Our pilot study suggests that tablet‐based access to educational modules and PHRs can increase inpatient engagement in care with high satisfaction and minimal time for orientation. Surprisingly, even older patients and those who might be considered less tech savvy in terms of Internet use and device ownership were equally able to utilize our tablet interventions. Furthermore, we did not experience any hardware issues in the harsh physical environment of inpatient wards. These preliminary findings suggest the potential utility of tablets for clinically meaningful tasks by inpatients with a low rate of technical issues.

From a technical standpoint, our experience suggests several next steps. First, although orientation time was minimal, it might be even less if patients used their own mobile devices because most patients already owned one. This bring your own device (BYOD) approach could also promote postdischarge patient engagement. Second, the flexibility of a BYOD approach raises the question of whether to also allow patients a choice of application‐based versus browser‐based platforms for specific programs such as the PHR and educational video we used. Indeed, although we used a browser‐based approach, several other teams have developed patient‐facing engagement applications (or apps) for mobile devices,[4, 12] and hospitalists could prescribe apps at discharge as a more providers are now doing in outpatient settings.[13] Of course, maximizing flexibility for BYOD and Web‐based versus app‐based approaches would likely increase patient engagement but would come at the cost of more time and effort for hospital providers to vet apps/websites and educate patients about their use. Third, regardless of the devices and programs used, broader engagement of patients, nurses, hospitalists, and other providers will be needed in the future to identify key areas for development to avoid overburdening patients and providers.

From a quality‐improvement perspective, recent literature has considered broad clinical uses for tablets by hospital providers,[14, 15] but our experience suggests more specific opportunities to improve transitions of care though direct patient engagement. Tablets and other mobile devices may help improve discharge education for patients taking high‐risk medications such as warfarin or insulin using interactive educational modules similar to the hospital safety modules we used. Additionally, clinical staff, such as nurses and pharmacists, can be trained to deliver mobile device interventions such as education on high‐risk medications.[16] Ultimately, scale up for our intervention will require that mobile devices and content eventually improve and replace current practices by hospital staff (especially nurses) in a way that streamlines, rather than compounds, current workflow. This could increase efficiency in these discharge tasks and extend contributions of these providers to high‐quality transitions.

Our study has several limitations. First, although this is a pilot study with only 30 patients, it adds needed scale to much smaller (N=58) published feasibility studies of tablet computer use by inpatients.[11, 12] Beyond more robust feasibility testing, our study adds new data about mobile device use for specific clinical tasks in the hospital such as patient education and PHR use. Second, we did not track postdischarge outcomes to test the effects of our intervention on transition care quality; this will be a focus of our future research. Third, we used existing platforms for interactive educational modules and PHR access at our site; participant satisfaction in our study may not generalize to other platforms. Furthermore, most PHR platforms (including ours) are not optimally configured to engage patients during transitions of care, but we plan to integrate existing functions (such as ability to refill medications or change appointments) into discharge education and planning. Finally, we have not engaged caregivers as surrogates for cognitively impaired patients or adapted our platform for non‐English speakers; these are areas for development in our ongoing work. Overall, our pilot results help set the stage to deploy mobile devices for better patient monitoring, engagement, and quality of care in the inpatient setting.[17]

In conclusion, our pilot project demonstrates that tablet computers can be used to improve inpatient education and patient engagement in discharge planning. Inpatients are highly satisfied with the use of tablets to complete health education modules and access their PHR, with minimal time required for patient training and device management by hospital staff. Tablets and other mobile devices have significant potential to improve patients' education and engagement in their hospital care.

BACKGROUND

Many hospitals have initiated intense efforts to improve transitions of care[1] such as discharge coordinators or transition coaches,[2, 3] but use of mobile devices as approaches to add or extend the value of human interventions have been understudied.[4] Additionally, many hospitalized patients experience substantial inactive time between provider visits, tests, and treatments. This time could be used to engage patients in their care through interactive health education modules and by learning to use their PHR to manage medications and postdischarge appointments.

Greater understanding of the advantages and limitations of mobile devices may be important for improving transitions of care and may help leverage existing hospital personnel resources. However, prior studies have focused on healthcare provider uses of tablet computers for medical education,[5] to collect clinical registration data,[6] or to do clinical work (eg, check labs, write notes)[7, 8, 9] primarily in outpatient settings; few studies have focused on patient uses for this technology in hospital settings.[10, 11] To address these knowledge gaps, we conducted a pilot project to explore inpatient satisfaction with bedside tablets and barriers to usability. Additionally, we evaluated use of these devices to deliver 2 specific Web‐based programs: (1) an interactive video to improve inpatient education about hospital safety, and (2) PHR access to promote inpatient engagement in discharge planning.

METHODS

RESULTS

As shown in Table 1, we enrolled 30 patients. Most participants (60%) were aged 40 years or older, and most (87%) owned a mobile device; 70% owned a laptop and 60% owned a smartphone, but few (22%) owned a computer tablet. Most participants accessed the Internet daily, but fewer reported Internet use for health tasks; about half (52%) communicated with a provider, but few refilled a prescription (27%) or scheduled an appointment (21%) online over the last year.

Nearly all participants (90%) were satisfied or very satisfied with their experience using the tablet in the hospital (Figure 1). Most (87%) required 30 minutes or less for basic orientation, and 70% required only 15 minutes or less. Most participants (83%) were able to independently complete an interactive health education module on hospital safety and were highly satisfied with the module. Despite the fact that 73% of participants were first‐time users of our PHR, the majority were able to login and independently access their medication list, verify scheduled appointments, or send a secure message to their primary care provider.

Figure 1

Participants aged 50 years or older were less likely to complete orientation in 15 minutes or less compared to those under 50 years old (25% vs 79%, P=0.025); however, age was not a significant factor in ability to complete the online health educational module or perform at least 1 essential PHR function. Other demographic features, such as device ownership and daily Internet use, did not correlate with shorter orientation time, educational module completion, or PHR use (data available on request).

Participants also made suggestions for improvement during the debrief interviews. Several suggested applications for entertainment (gaming, magazines, or music) and 2 suggested that all patients should be introduced to their PHR during hospitalization (data available on request). No device software malfunction (eg, device freezes, Internet connection failures), hardware issues (eg, damage from falls, wetness, or repeated disinfectant exposure), or theft or misappropriation were reported by patients or observed by the RAs to date.

DISCUSSION

Our pilot study suggests that tablet‐based access to educational modules and PHRs can increase inpatient engagement in care with high satisfaction and minimal time for orientation. Surprisingly, even older patients and those who might be considered less tech savvy in terms of Internet use and device ownership were equally able to utilize our tablet interventions. Furthermore, we did not experience any hardware issues in the harsh physical environment of inpatient wards. These preliminary findings suggest the potential utility of tablets for clinically meaningful tasks by inpatients with a low rate of technical issues.

From a technical standpoint, our experience suggests several next steps. First, although orientation time was minimal, it might be even less if patients used their own mobile devices because most patients already owned one. This bring your own device (BYOD) approach could also promote postdischarge patient engagement. Second, the flexibility of a BYOD approach raises the question of whether to also allow patients a choice of application‐based versus browser‐based platforms for specific programs such as the PHR and educational video we used. Indeed, although we used a browser‐based approach, several other teams have developed patient‐facing engagement applications (or apps) for mobile devices,[4, 12] and hospitalists could prescribe apps at discharge as a more providers are now doing in outpatient settings.[13] Of course, maximizing flexibility for BYOD and Web‐based versus app‐based approaches would likely increase patient engagement but would come at the cost of more time and effort for hospital providers to vet apps/websites and educate patients about their use. Third, regardless of the devices and programs used, broader engagement of patients, nurses, hospitalists, and other providers will be needed in the future to identify key areas for development to avoid overburdening patients and providers.

From a quality‐improvement perspective, recent literature has considered broad clinical uses for tablets by hospital providers,[14, 15] but our experience suggests more specific opportunities to improve transitions of care though direct patient engagement. Tablets and other mobile devices may help improve discharge education for patients taking high‐risk medications such as warfarin or insulin using interactive educational modules similar to the hospital safety modules we used. Additionally, clinical staff, such as nurses and pharmacists, can be trained to deliver mobile device interventions such as education on high‐risk medications.[16] Ultimately, scale up for our intervention will require that mobile devices and content eventually improve and replace current practices by hospital staff (especially nurses) in a way that streamlines, rather than compounds, current workflow. This could increase efficiency in these discharge tasks and extend contributions of these providers to high‐quality transitions.

Our study has several limitations. First, although this is a pilot study with only 30 patients, it adds needed scale to much smaller (N=58) published feasibility studies of tablet computer use by inpatients.[11, 12] Beyond more robust feasibility testing, our study adds new data about mobile device use for specific clinical tasks in the hospital such as patient education and PHR use. Second, we did not track postdischarge outcomes to test the effects of our intervention on transition care quality; this will be a focus of our future research. Third, we used existing platforms for interactive educational modules and PHR access at our site; participant satisfaction in our study may not generalize to other platforms. Furthermore, most PHR platforms (including ours) are not optimally configured to engage patients during transitions of care, but we plan to integrate existing functions (such as ability to refill medications or change appointments) into discharge education and planning. Finally, we have not engaged caregivers as surrogates for cognitively impaired patients or adapted our platform for non‐English speakers; these are areas for development in our ongoing work. Overall, our pilot results help set the stage to deploy mobile devices for better patient monitoring, engagement, and quality of care in the inpatient setting.[17]

In conclusion, our pilot project demonstrates that tablet computers can be used to improve inpatient education and patient engagement in discharge planning. Inpatients are highly satisfied with the use of tablets to complete health education modules and access their PHR, with minimal time required for patient training and device management by hospital staff. Tablets and other mobile devices have significant potential to improve patients' education and engagement in their hospital care.

Sodium is the predominant extracellular cation and a major determinant of serum osmolality. As such, the serum sodium (SNa) concentration in humans is closely maintained by sensitive homeostatic mechanisms. However, disorders of sodium homeostasis are relatively common in selected patient populations, resulting in hyponatremia (<135 mmol/L) or hypernatremia (>144 mmol/L).[1, 2]

The presence of hyponatremia is independently associated with greater mortality in hospitalized individuals,[3] including patients with congestive heart failure[4] and cancer.[5] In prior subgroup analyses of patients with musculoskeletal disorders undergoing surgery, hyponatremia (<135 mmol/L) at the time of hospital admission was associated with a 2.31‐fold greater risk of death, compared with normonatremic individuals (135144 mmol/L).[3] Hyponatremia is also associated with increased fracture risk[6, 7] and disturbances of gait⁸; however, controversy remains as to whether this association is causal or simply a marker of comorbid disease. On the other hand, hypernatremia has been associated with greater risk of mortality in critically ill patients⁹; however, there is a relative paucity of data regarding clinical associations in the orthopedic population.

We aimed to examine the relationship of the perioperative SNa (corrected for glucose) with length of stay and 30‐day mortality in patients undergoing major orthopedic surgery. We hypothesized that both hypo‐ and hypernatremia would be associated with greater length of stay and greater 30‐day mortality.

METHODS

RESULTS

30‐Day Mortality

Overall, patients contributed 1325 years of at‐risk time, during which 208 deaths were recorded within 30 days of orthopedic surgery. In both unadjusted and case‐mix adjusted models, there was evidence for the presence of a J‐shaped association for categories of SNa with greater 30‐day mortality (Table 3). Restricted cubic spline analyses provided additional evidence for the presence of a nonlinear relationship, with hypo‐ and hypernatremia being associated with greater 30‐day mortality (Figure 1). In adjusted subgroup analyses, mild hyponatremia and hypernatremia remained associated with greater mortality in those with fracture, whereas only moderate/severe hyponatremia remained associated with greater mortality in those without a diagnosis of fracture.

Table 3.Association of Categories of Perioperative Corrected SNa With 30‐Day Mortality

	Hazard Ratio (95% CI) for 30‐Day Mortality According to Category of Perioperative SNa
	<130 mmol/L, n= 198	131134 mmol/L, n=1,036	135143 mmol/L, n=14,563	144 mmol/L, n=409
NOTE: Model 1 adjusted for age, race, and sex; model 2 adjusted for same variables as model 1 plus categories of the Deyo Charlson comorbidity index and diagnosis of fracture; model 3 adjusted for same as model 2 plus individual diagnostic codes for congestive heart failure, diabetes, cancer, and liver disease. All models were stratified by clinical center. Abbreviations: CI, confidence interval; SNa, serum sodium. a Corrected for simultaneous measurement of glucose. b Effect estimates were obtained using model 3, without the inclusion of fracture as a covariate.
Unadjusted	5.73 (3.11‐10.6)	3.48 (2.40‐5.04)	REF	4.90 (3.037.91)
Model 1	3.49 (1.88‐6.49)	2.36 (1.60‐3.50)	REF	3.83 (2.31‐6.35)
Model 2	2.89 (1.56‐5.35)	1.96 (1.33‐2.90)	REF	3.14 (1.88‐5.21)
Model 3	2.47 (1.33‐4.59)	1.80 (1.21‐2.66)	REF	2.99 (1.79‐4.98)
Fractureb
Present, n=5,296	1.94 (0.84‐4.47)	1.83 (1.13‐2.97)	REF	3.12 (1.72‐5.66)
Absent, n=10,910	3.85 (1.53‐9.68)	1.58 (0.80‐3.14)	REF	2.73 (0.98‐7.62)

Figure 1

In sensitivity analyses, when restricted to individuals with SNa available within 60 days prior to admission, the effect estimates for the relationships between categories of hyponatremia and length of stay were qualitatively unchanged (see Supporting Information, Table B, in the online version of this article).

DISCUSSION

In this study of hospitalized patients undergoing major orthopedic procedures, we report that abnormal preadmission and perioperative SNa during hospitalization are: (1) present in approximately 10% of patients, (2) associated with greater hospital length of stay, and (3) associated with greater 30‐day mortality.

The incidence of perioperative hyponatremia (<135 mmol/L) in prior studies ranges from 9.1% to 26.5% in studies of patients over 65 years of age admitted to the hospital with large bone fractures.[13, 14] In our study, the overall incidence of hyponatremia (SNa <135 mmol/L) was 7.6%. Of note, our sample included individuals aged 18 years and was not limited to individuals with fractures, which may partly explain why the incidence was lower than that previously reported.

Few studies have examined the association of perioperative hyponatremia with length of stay in the hospitalized orthopedic surgery population. We found that both hyponatremia and hypernatremia (corrected for glucose) were independently associated with greater adjusted hospital length of stay, compared with normonatremic individuals. This has important implications for healthcare costs and resource utilization. However, it is unclear if dysnatremia is associated with other metrics of postoperative recovery that could delay discharge, or whether dysnatremia alone is responsible for the decision to delay discharge (despite other measures of recovery being deemed adequate).

Leung et al. recently examined the association of preoperative hyponatremia (<135 mmol/L, uncorrected and measured within 90 days of surgery) with 30‐day mortality in 964,263 patients from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) dataset.[15] They found that preoperative hyponatremia was associated with 44% greater adjusted odds (odds ratio [OR]: 1.44, 95% CI: 1.38‐1.50) of 30‐day mortality in the whole cohort and with 56% greater adjusted odds (OR: 1.56, 95% CI: 1.22‐1.99) in the subgroup of orthopedic patients. Waikar et al. also reported that hyponatremia is associated with greater in‐hospital and long‐term mortality in the subgroup of hospitalized patients who were admitted for musculoskeletal problems requiring surgery.[3] Our analyses support these findings and provide greater confidence by specifically focusing on patients admitted for major orthopedic surgery. We also expand the current knowledge base by correcting for serum glucose concentrations and by reporting associations of moderate/severe hyponatremia with adverse clinical outcomes.

The incidence of perioperative hypernatremia in our study was 2.5%, which compares to 1.0% to 2.6% in other studies of orthopedic patients.[14, 16] Hypernatremia has previously been associated with greater mortality in hospitalized patients in the intensive care unit (ICU) setting at the time of admission,[17] during the ICU stay,[9] in older patients (>60 years),[18] and in those with decompensated liver disease.[19] More recently, Leung et al. performed further analyses using data from the ACS NSQIP, reporting that preoperative hypernatremia (>144 mmol/L, uncorrected and measured within 90 days of surgery) is associated with 44% greater adjusted odds (OR: 1.44, 95% CI: 1.33‐1.56) of 30‐day mortality, but was not significantly associated with greater mortality in the orthopedic subgroup.[20] We extend the literature by examining glucose‐corrected SNa and again by focusing specifically on those undergoing major orthopedic surgery, reporting an association of perioperative hypernatremia with greater length of stay and 30‐day mortality. In our study, when we specifically examined the association of preoperative SNa values, we noted attenuation of the effect estimates and loss of statistical significance, confirming the subgroup findings of Leung et al.[20] The reasons for this are not clear, but may relate to the possibility that perioperative hypernatremia (as opposed to preoperative) is a stronger marker of concurrent illness severity and therefore more closely associates with adverse clinical outcomes.

As with most observational studies in this area, the question of whether dysnatremia is causative or merely a marker of comorbidity remains. In this regard, there are some unique points that deserve mention in this cohort of patients. Hyponatremia has previously been associated with several musculoskeletal abnormalities, including a greater risk of fracture,[7, 16, 21] which may contribute to the observed associations with greater morbidity and mortality. For example, Verbalis et al. reported that the induction and maintenance of hyponatremia by administration of 1‐deamino8‐_d‐arginine vasopressin in rodent models is associated with reduced bone mineral density in excised rat femurs, which may predispose to greater fracture risk.[22] In humans, the same authors reported that hyponatremia (<135 mmol/L) was independently associated with greater odds of having osteoporosis at the femoral neck in individuals aged 50 years or older (OR: 2.87, 95% CI: 1.41‐5.81), compared with normonatremic individuals (135145 mmol/L).[22] On the other hand, Kinsella et al. found that hyponatremia (<135 mmol/L) associated with greater odds of having a fracture (OR: 2.25, 95% CI: 1.24‐4.09), independent of the presence of osteoporosis as measured by hip and vertebral T‐scores, suggesting an association between hyponatremia and fracture, independent of osteoporosis.[6] Other potential confounders of these associations may include gait disturbance and unsteadiness, which could contribute to greater fall and fracture risk.[7, 8, 21] Additional proposed mechanisms for the association of hyponatremia with adverse outcomes include the development of cerebral edema,[23] abnormal nerve conduction,[24] and predisposition to infection,[25] perhaps via altered immune functioning in the presence of hypo‐osmolality. Unfortunately, due to data limitations, we were unable to investigate these hypotheses further in our present study. In relation to hypernatremia, associations with impairment in neurologic,[26] myocardial,[27] and immune functioning have been reported previously, which may contribute to some of the excess risk associated with this condition.

There are several limitations of this study that deserve further mention. We used ICD‐9 and diagnosis‐related group codes to ascertain data on primary diagnoses and comorbid conditions, raising the possibility of some degree of misclassification of covariates in this study. We were unable to differentiate between elective versus urgent/emergent procedures. Given the large sample size and intrinsic data limitations, we were unable to ascertain the underlying causes of dysnatremia, or examine practice differences between the 2 institutions from which the sample was sourced. The majority of our sample had perioperative SNa measurements performed on the same day as their major orthopedic procedure. Although we were unable to confirm the timing of SNa measurements relative to the operation, it is not uncommon for elective cases to have initial hospitalization labs drawn in the recovery room, as opposed to preoperatively. In sensitivity analyses, we found similar patterns of association for hyponatremia with outcomes, but not for hypernatremia, when we examined the SNa measurement within 60 days prior to admission as the exposure of interest. Although these analyses were underpowered, they provide some modicum of reassurance that the observed associations of perioperative hyponatremia with adverse outcomes are robust. Whether perioperative dysnatremia, measured in the recovery room, has associations with clinical outcomes that are distinct from immediate preoperative dysnatremia requires further research. The possibility of residual confounding (eg, administration of fluids, medications, severity of illness) that was not captured by the D‐CI index, functional status and infection remain important considerations. Finally, caution must be applied before generalizing our results from 2 large academic centers to the general hospitalized orthopedic population.

In conclusion, we report that dysnatremia on admission for patients requiring major orthopedic surgery is present in approximately 10% of patients and is associated with greater length of stay and all‐cause mortality. Further research is required to assess whether dysnatremia is a mediator or marker for increased morbidity and mortality, and whether perioperative correction of hypo‐ or hypernatremia will improve clinical outcomes in these patients.

Sodium is the predominant extracellular cation and a major determinant of serum osmolality. As such, the serum sodium (SNa) concentration in humans is closely maintained by sensitive homeostatic mechanisms. However, disorders of sodium homeostasis are relatively common in selected patient populations, resulting in hyponatremia (<135 mmol/L) or hypernatremia (>144 mmol/L).[1, 2]

The presence of hyponatremia is independently associated with greater mortality in hospitalized individuals,[3] including patients with congestive heart failure[4] and cancer.[5] In prior subgroup analyses of patients with musculoskeletal disorders undergoing surgery, hyponatremia (<135 mmol/L) at the time of hospital admission was associated with a 2.31‐fold greater risk of death, compared with normonatremic individuals (135144 mmol/L).[3] Hyponatremia is also associated with increased fracture risk[6, 7] and disturbances of gait⁸; however, controversy remains as to whether this association is causal or simply a marker of comorbid disease. On the other hand, hypernatremia has been associated with greater risk of mortality in critically ill patients⁹; however, there is a relative paucity of data regarding clinical associations in the orthopedic population.

We aimed to examine the relationship of the perioperative SNa (corrected for glucose) with length of stay and 30‐day mortality in patients undergoing major orthopedic surgery. We hypothesized that both hypo‐ and hypernatremia would be associated with greater length of stay and greater 30‐day mortality.

METHODS

RESULTS

30‐Day Mortality

Overall, patients contributed 1325 years of at‐risk time, during which 208 deaths were recorded within 30 days of orthopedic surgery. In both unadjusted and case‐mix adjusted models, there was evidence for the presence of a J‐shaped association for categories of SNa with greater 30‐day mortality (Table 3). Restricted cubic spline analyses provided additional evidence for the presence of a nonlinear relationship, with hypo‐ and hypernatremia being associated with greater 30‐day mortality (Figure 1). In adjusted subgroup analyses, mild hyponatremia and hypernatremia remained associated with greater mortality in those with fracture, whereas only moderate/severe hyponatremia remained associated with greater mortality in those without a diagnosis of fracture.

Table 3.Association of Categories of Perioperative Corrected SNa With 30‐Day Mortality

	Hazard Ratio (95% CI) for 30‐Day Mortality According to Category of Perioperative SNa
	<130 mmol/L, n= 198	131134 mmol/L, n=1,036	135143 mmol/L, n=14,563	144 mmol/L, n=409
NOTE: Model 1 adjusted for age, race, and sex; model 2 adjusted for same variables as model 1 plus categories of the Deyo Charlson comorbidity index and diagnosis of fracture; model 3 adjusted for same as model 2 plus individual diagnostic codes for congestive heart failure, diabetes, cancer, and liver disease. All models were stratified by clinical center. Abbreviations: CI, confidence interval; SNa, serum sodium. a Corrected for simultaneous measurement of glucose. b Effect estimates were obtained using model 3, without the inclusion of fracture as a covariate.
Unadjusted	5.73 (3.11‐10.6)	3.48 (2.40‐5.04)	REF	4.90 (3.037.91)
Model 1	3.49 (1.88‐6.49)	2.36 (1.60‐3.50)	REF	3.83 (2.31‐6.35)
Model 2	2.89 (1.56‐5.35)	1.96 (1.33‐2.90)	REF	3.14 (1.88‐5.21)
Model 3	2.47 (1.33‐4.59)	1.80 (1.21‐2.66)	REF	2.99 (1.79‐4.98)
Fractureb
Present, n=5,296	1.94 (0.84‐4.47)	1.83 (1.13‐2.97)	REF	3.12 (1.72‐5.66)
Absent, n=10,910	3.85 (1.53‐9.68)	1.58 (0.80‐3.14)	REF	2.73 (0.98‐7.62)

Figure 1

In sensitivity analyses, when restricted to individuals with SNa available within 60 days prior to admission, the effect estimates for the relationships between categories of hyponatremia and length of stay were qualitatively unchanged (see Supporting Information, Table B, in the online version of this article).

DISCUSSION

In this study of hospitalized patients undergoing major orthopedic procedures, we report that abnormal preadmission and perioperative SNa during hospitalization are: (1) present in approximately 10% of patients, (2) associated with greater hospital length of stay, and (3) associated with greater 30‐day mortality.

The incidence of perioperative hyponatremia (<135 mmol/L) in prior studies ranges from 9.1% to 26.5% in studies of patients over 65 years of age admitted to the hospital with large bone fractures.[13, 14] In our study, the overall incidence of hyponatremia (SNa <135 mmol/L) was 7.6%. Of note, our sample included individuals aged 18 years and was not limited to individuals with fractures, which may partly explain why the incidence was lower than that previously reported.

Few studies have examined the association of perioperative hyponatremia with length of stay in the hospitalized orthopedic surgery population. We found that both hyponatremia and hypernatremia (corrected for glucose) were independently associated with greater adjusted hospital length of stay, compared with normonatremic individuals. This has important implications for healthcare costs and resource utilization. However, it is unclear if dysnatremia is associated with other metrics of postoperative recovery that could delay discharge, or whether dysnatremia alone is responsible for the decision to delay discharge (despite other measures of recovery being deemed adequate).

Leung et al. recently examined the association of preoperative hyponatremia (<135 mmol/L, uncorrected and measured within 90 days of surgery) with 30‐day mortality in 964,263 patients from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) dataset.[15] They found that preoperative hyponatremia was associated with 44% greater adjusted odds (odds ratio [OR]: 1.44, 95% CI: 1.38‐1.50) of 30‐day mortality in the whole cohort and with 56% greater adjusted odds (OR: 1.56, 95% CI: 1.22‐1.99) in the subgroup of orthopedic patients. Waikar et al. also reported that hyponatremia is associated with greater in‐hospital and long‐term mortality in the subgroup of hospitalized patients who were admitted for musculoskeletal problems requiring surgery.[3] Our analyses support these findings and provide greater confidence by specifically focusing on patients admitted for major orthopedic surgery. We also expand the current knowledge base by correcting for serum glucose concentrations and by reporting associations of moderate/severe hyponatremia with adverse clinical outcomes.

The incidence of perioperative hypernatremia in our study was 2.5%, which compares to 1.0% to 2.6% in other studies of orthopedic patients.[14, 16] Hypernatremia has previously been associated with greater mortality in hospitalized patients in the intensive care unit (ICU) setting at the time of admission,[17] during the ICU stay,[9] in older patients (>60 years),[18] and in those with decompensated liver disease.[19] More recently, Leung et al. performed further analyses using data from the ACS NSQIP, reporting that preoperative hypernatremia (>144 mmol/L, uncorrected and measured within 90 days of surgery) is associated with 44% greater adjusted odds (OR: 1.44, 95% CI: 1.33‐1.56) of 30‐day mortality, but was not significantly associated with greater mortality in the orthopedic subgroup.[20] We extend the literature by examining glucose‐corrected SNa and again by focusing specifically on those undergoing major orthopedic surgery, reporting an association of perioperative hypernatremia with greater length of stay and 30‐day mortality. In our study, when we specifically examined the association of preoperative SNa values, we noted attenuation of the effect estimates and loss of statistical significance, confirming the subgroup findings of Leung et al.[20] The reasons for this are not clear, but may relate to the possibility that perioperative hypernatremia (as opposed to preoperative) is a stronger marker of concurrent illness severity and therefore more closely associates with adverse clinical outcomes.

As with most observational studies in this area, the question of whether dysnatremia is causative or merely a marker of comorbidity remains. In this regard, there are some unique points that deserve mention in this cohort of patients. Hyponatremia has previously been associated with several musculoskeletal abnormalities, including a greater risk of fracture,[7, 16, 21] which may contribute to the observed associations with greater morbidity and mortality. For example, Verbalis et al. reported that the induction and maintenance of hyponatremia by administration of 1‐deamino8‐_d‐arginine vasopressin in rodent models is associated with reduced bone mineral density in excised rat femurs, which may predispose to greater fracture risk.[22] In humans, the same authors reported that hyponatremia (<135 mmol/L) was independently associated with greater odds of having osteoporosis at the femoral neck in individuals aged 50 years or older (OR: 2.87, 95% CI: 1.41‐5.81), compared with normonatremic individuals (135145 mmol/L).[22] On the other hand, Kinsella et al. found that hyponatremia (<135 mmol/L) associated with greater odds of having a fracture (OR: 2.25, 95% CI: 1.24‐4.09), independent of the presence of osteoporosis as measured by hip and vertebral T‐scores, suggesting an association between hyponatremia and fracture, independent of osteoporosis.[6] Other potential confounders of these associations may include gait disturbance and unsteadiness, which could contribute to greater fall and fracture risk.[7, 8, 21] Additional proposed mechanisms for the association of hyponatremia with adverse outcomes include the development of cerebral edema,[23] abnormal nerve conduction,[24] and predisposition to infection,[25] perhaps via altered immune functioning in the presence of hypo‐osmolality. Unfortunately, due to data limitations, we were unable to investigate these hypotheses further in our present study. In relation to hypernatremia, associations with impairment in neurologic,[26] myocardial,[27] and immune functioning have been reported previously, which may contribute to some of the excess risk associated with this condition.

There are several limitations of this study that deserve further mention. We used ICD‐9 and diagnosis‐related group codes to ascertain data on primary diagnoses and comorbid conditions, raising the possibility of some degree of misclassification of covariates in this study. We were unable to differentiate between elective versus urgent/emergent procedures. Given the large sample size and intrinsic data limitations, we were unable to ascertain the underlying causes of dysnatremia, or examine practice differences between the 2 institutions from which the sample was sourced. The majority of our sample had perioperative SNa measurements performed on the same day as their major orthopedic procedure. Although we were unable to confirm the timing of SNa measurements relative to the operation, it is not uncommon for elective cases to have initial hospitalization labs drawn in the recovery room, as opposed to preoperatively. In sensitivity analyses, we found similar patterns of association for hyponatremia with outcomes, but not for hypernatremia, when we examined the SNa measurement within 60 days prior to admission as the exposure of interest. Although these analyses were underpowered, they provide some modicum of reassurance that the observed associations of perioperative hyponatremia with adverse outcomes are robust. Whether perioperative dysnatremia, measured in the recovery room, has associations with clinical outcomes that are distinct from immediate preoperative dysnatremia requires further research. The possibility of residual confounding (eg, administration of fluids, medications, severity of illness) that was not captured by the D‐CI index, functional status and infection remain important considerations. Finally, caution must be applied before generalizing our results from 2 large academic centers to the general hospitalized orthopedic population.

In conclusion, we report that dysnatremia on admission for patients requiring major orthopedic surgery is present in approximately 10% of patients and is associated with greater length of stay and all‐cause mortality. Further research is required to assess whether dysnatremia is a mediator or marker for increased morbidity and mortality, and whether perioperative correction of hypo‐ or hypernatremia will improve clinical outcomes in these patients.

Sodium is the predominant extracellular cation and a major determinant of serum osmolality. As such, the serum sodium (SNa) concentration in humans is closely maintained by sensitive homeostatic mechanisms. However, disorders of sodium homeostasis are relatively common in selected patient populations, resulting in hyponatremia (<135 mmol/L) or hypernatremia (>144 mmol/L).[1, 2]

The presence of hyponatremia is independently associated with greater mortality in hospitalized individuals,[3] including patients with congestive heart failure[4] and cancer.[5] In prior subgroup analyses of patients with musculoskeletal disorders undergoing surgery, hyponatremia (<135 mmol/L) at the time of hospital admission was associated with a 2.31‐fold greater risk of death, compared with normonatremic individuals (135144 mmol/L).[3] Hyponatremia is also associated with increased fracture risk[6, 7] and disturbances of gait⁸; however, controversy remains as to whether this association is causal or simply a marker of comorbid disease. On the other hand, hypernatremia has been associated with greater risk of mortality in critically ill patients⁹; however, there is a relative paucity of data regarding clinical associations in the orthopedic population.

We aimed to examine the relationship of the perioperative SNa (corrected for glucose) with length of stay and 30‐day mortality in patients undergoing major orthopedic surgery. We hypothesized that both hypo‐ and hypernatremia would be associated with greater length of stay and greater 30‐day mortality.

METHODS

RESULTS

30‐Day Mortality

Overall, patients contributed 1325 years of at‐risk time, during which 208 deaths were recorded within 30 days of orthopedic surgery. In both unadjusted and case‐mix adjusted models, there was evidence for the presence of a J‐shaped association for categories of SNa with greater 30‐day mortality (Table 3). Restricted cubic spline analyses provided additional evidence for the presence of a nonlinear relationship, with hypo‐ and hypernatremia being associated with greater 30‐day mortality (Figure 1). In adjusted subgroup analyses, mild hyponatremia and hypernatremia remained associated with greater mortality in those with fracture, whereas only moderate/severe hyponatremia remained associated with greater mortality in those without a diagnosis of fracture.

Table 3.Association of Categories of Perioperative Corrected SNa With 30‐Day Mortality

	Hazard Ratio (95% CI) for 30‐Day Mortality According to Category of Perioperative SNa
	<130 mmol/L, n= 198	131134 mmol/L, n=1,036	135143 mmol/L, n=14,563	144 mmol/L, n=409
NOTE: Model 1 adjusted for age, race, and sex; model 2 adjusted for same variables as model 1 plus categories of the Deyo Charlson comorbidity index and diagnosis of fracture; model 3 adjusted for same as model 2 plus individual diagnostic codes for congestive heart failure, diabetes, cancer, and liver disease. All models were stratified by clinical center. Abbreviations: CI, confidence interval; SNa, serum sodium. a Corrected for simultaneous measurement of glucose. b Effect estimates were obtained using model 3, without the inclusion of fracture as a covariate.
Unadjusted	5.73 (3.11‐10.6)	3.48 (2.40‐5.04)	REF	4.90 (3.037.91)
Model 1	3.49 (1.88‐6.49)	2.36 (1.60‐3.50)	REF	3.83 (2.31‐6.35)
Model 2	2.89 (1.56‐5.35)	1.96 (1.33‐2.90)	REF	3.14 (1.88‐5.21)
Model 3	2.47 (1.33‐4.59)	1.80 (1.21‐2.66)	REF	2.99 (1.79‐4.98)
Fractureb
Present, n=5,296	1.94 (0.84‐4.47)	1.83 (1.13‐2.97)	REF	3.12 (1.72‐5.66)
Absent, n=10,910	3.85 (1.53‐9.68)	1.58 (0.80‐3.14)	REF	2.73 (0.98‐7.62)

Figure 1

In sensitivity analyses, when restricted to individuals with SNa available within 60 days prior to admission, the effect estimates for the relationships between categories of hyponatremia and length of stay were qualitatively unchanged (see Supporting Information, Table B, in the online version of this article).

DISCUSSION

In this study of hospitalized patients undergoing major orthopedic procedures, we report that abnormal preadmission and perioperative SNa during hospitalization are: (1) present in approximately 10% of patients, (2) associated with greater hospital length of stay, and (3) associated with greater 30‐day mortality.

The incidence of perioperative hyponatremia (<135 mmol/L) in prior studies ranges from 9.1% to 26.5% in studies of patients over 65 years of age admitted to the hospital with large bone fractures.[13, 14] In our study, the overall incidence of hyponatremia (SNa <135 mmol/L) was 7.6%. Of note, our sample included individuals aged 18 years and was not limited to individuals with fractures, which may partly explain why the incidence was lower than that previously reported.

Few studies have examined the association of perioperative hyponatremia with length of stay in the hospitalized orthopedic surgery population. We found that both hyponatremia and hypernatremia (corrected for glucose) were independently associated with greater adjusted hospital length of stay, compared with normonatremic individuals. This has important implications for healthcare costs and resource utilization. However, it is unclear if dysnatremia is associated with other metrics of postoperative recovery that could delay discharge, or whether dysnatremia alone is responsible for the decision to delay discharge (despite other measures of recovery being deemed adequate).

Leung et al. recently examined the association of preoperative hyponatremia (<135 mmol/L, uncorrected and measured within 90 days of surgery) with 30‐day mortality in 964,263 patients from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) dataset.[15] They found that preoperative hyponatremia was associated with 44% greater adjusted odds (odds ratio [OR]: 1.44, 95% CI: 1.38‐1.50) of 30‐day mortality in the whole cohort and with 56% greater adjusted odds (OR: 1.56, 95% CI: 1.22‐1.99) in the subgroup of orthopedic patients. Waikar et al. also reported that hyponatremia is associated with greater in‐hospital and long‐term mortality in the subgroup of hospitalized patients who were admitted for musculoskeletal problems requiring surgery.[3] Our analyses support these findings and provide greater confidence by specifically focusing on patients admitted for major orthopedic surgery. We also expand the current knowledge base by correcting for serum glucose concentrations and by reporting associations of moderate/severe hyponatremia with adverse clinical outcomes.

The incidence of perioperative hypernatremia in our study was 2.5%, which compares to 1.0% to 2.6% in other studies of orthopedic patients.[14, 16] Hypernatremia has previously been associated with greater mortality in hospitalized patients in the intensive care unit (ICU) setting at the time of admission,[17] during the ICU stay,[9] in older patients (>60 years),[18] and in those with decompensated liver disease.[19] More recently, Leung et al. performed further analyses using data from the ACS NSQIP, reporting that preoperative hypernatremia (>144 mmol/L, uncorrected and measured within 90 days of surgery) is associated with 44% greater adjusted odds (OR: 1.44, 95% CI: 1.33‐1.56) of 30‐day mortality, but was not significantly associated with greater mortality in the orthopedic subgroup.[20] We extend the literature by examining glucose‐corrected SNa and again by focusing specifically on those undergoing major orthopedic surgery, reporting an association of perioperative hypernatremia with greater length of stay and 30‐day mortality. In our study, when we specifically examined the association of preoperative SNa values, we noted attenuation of the effect estimates and loss of statistical significance, confirming the subgroup findings of Leung et al.[20] The reasons for this are not clear, but may relate to the possibility that perioperative hypernatremia (as opposed to preoperative) is a stronger marker of concurrent illness severity and therefore more closely associates with adverse clinical outcomes.

As with most observational studies in this area, the question of whether dysnatremia is causative or merely a marker of comorbidity remains. In this regard, there are some unique points that deserve mention in this cohort of patients. Hyponatremia has previously been associated with several musculoskeletal abnormalities, including a greater risk of fracture,[7, 16, 21] which may contribute to the observed associations with greater morbidity and mortality. For example, Verbalis et al. reported that the induction and maintenance of hyponatremia by administration of 1‐deamino8‐_d‐arginine vasopressin in rodent models is associated with reduced bone mineral density in excised rat femurs, which may predispose to greater fracture risk.[22] In humans, the same authors reported that hyponatremia (<135 mmol/L) was independently associated with greater odds of having osteoporosis at the femoral neck in individuals aged 50 years or older (OR: 2.87, 95% CI: 1.41‐5.81), compared with normonatremic individuals (135145 mmol/L).[22] On the other hand, Kinsella et al. found that hyponatremia (<135 mmol/L) associated with greater odds of having a fracture (OR: 2.25, 95% CI: 1.24‐4.09), independent of the presence of osteoporosis as measured by hip and vertebral T‐scores, suggesting an association between hyponatremia and fracture, independent of osteoporosis.[6] Other potential confounders of these associations may include gait disturbance and unsteadiness, which could contribute to greater fall and fracture risk.[7, 8, 21] Additional proposed mechanisms for the association of hyponatremia with adverse outcomes include the development of cerebral edema,[23] abnormal nerve conduction,[24] and predisposition to infection,[25] perhaps via altered immune functioning in the presence of hypo‐osmolality. Unfortunately, due to data limitations, we were unable to investigate these hypotheses further in our present study. In relation to hypernatremia, associations with impairment in neurologic,[26] myocardial,[27] and immune functioning have been reported previously, which may contribute to some of the excess risk associated with this condition.

There are several limitations of this study that deserve further mention. We used ICD‐9 and diagnosis‐related group codes to ascertain data on primary diagnoses and comorbid conditions, raising the possibility of some degree of misclassification of covariates in this study. We were unable to differentiate between elective versus urgent/emergent procedures. Given the large sample size and intrinsic data limitations, we were unable to ascertain the underlying causes of dysnatremia, or examine practice differences between the 2 institutions from which the sample was sourced. The majority of our sample had perioperative SNa measurements performed on the same day as their major orthopedic procedure. Although we were unable to confirm the timing of SNa measurements relative to the operation, it is not uncommon for elective cases to have initial hospitalization labs drawn in the recovery room, as opposed to preoperatively. In sensitivity analyses, we found similar patterns of association for hyponatremia with outcomes, but not for hypernatremia, when we examined the SNa measurement within 60 days prior to admission as the exposure of interest. Although these analyses were underpowered, they provide some modicum of reassurance that the observed associations of perioperative hyponatremia with adverse outcomes are robust. Whether perioperative dysnatremia, measured in the recovery room, has associations with clinical outcomes that are distinct from immediate preoperative dysnatremia requires further research. The possibility of residual confounding (eg, administration of fluids, medications, severity of illness) that was not captured by the D‐CI index, functional status and infection remain important considerations. Finally, caution must be applied before generalizing our results from 2 large academic centers to the general hospitalized orthopedic population.

In conclusion, we report that dysnatremia on admission for patients requiring major orthopedic surgery is present in approximately 10% of patients and is associated with greater length of stay and all‐cause mortality. Further research is required to assess whether dysnatremia is a mediator or marker for increased morbidity and mortality, and whether perioperative correction of hypo‐ or hypernatremia will improve clinical outcomes in these patients.