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Journal of Hospital Medicine – Jan. 2018
BACKGROUND: Hospital charges and lengths of stay may be greater when adults with chronic conditions are admitted to children’s hospitals. Despite multiple efforts to improve pediatric-adult health care transitions, little guidance exists for transitioning inpatient care.
OBJECTIVE: This study sought to characterize pediatric-adult inpatient care transitions across general pediatric services at U.S. children’s hospitals.
DESIGN and SETTING: National survey of inpatient general pediatric service leaders at U.S. children’s hospitals from January 2016 to July 2016.
MEASUREMENT: Questionnaires assessed institutional characteristics, presence of inpatient transition initiatives (having a specific process and/or leader), and 22 inpatient transition activities. Scales of highly correlated activities were created using exploratory factor analysis. Logistic regression identified associations among institutional characteristics, transition activities, and presence of an inpatient transition initiative.
RESULTS: Of 195 children’s hospitals, 96 responded (49.2% response rate). Transition initiatives were present at 38% of children’s hospitals, more often where there were providers who were trained in both internal medicine and pediatrics or where there were outpatient transition processes. Specific activities were infrequent and varied widely from 2.1% (systems to track youth in transition) to 40.5% (addressing potential insurance problems). Institutions with initiatives more often consistently performed the majority of activities, including using checklists and creating patient-centered transition care plans. Of remaining activities, half involved transition planning, the essential step between readiness and transfer.
CONCLUSION: Relatively few inpatient general pediatric services at U.S. children’s hospitals have leaders or dedicated processes to shepherd transitions to adult-oriented inpatient care. Across institutions, there is wide variability in performance of activities to facilitate this transition. Feasible process and outcome measures are needed.
Also in JHM this month
Characterizing hospitalist practice and perceptions of critical care delivery
AUTHORS: Joseph R. Sweigart, MD, FACP, FHM; David Aymond, MD; Alfred Burger, MD, FACP, SFHM; Andy Kelly, MAS, MS; Nick Marzano, Med; Thomas McIlraith, MD, SFHM; Peter Morris, MD; Mark V. Williams, MD, FACP, MHM; and Eric M. Siegal, MD, SFHM, FCCM
Clinical decision making: Observing the smartphone user an observational study in predicting acute surgical patients’ suitability for discharge
AUTHORS: Richard Hoffmann, MBBS; Simon Harley, MBBS; Samuel Ellison, MBBS; and Peter G. Devitt, MBBS, FRACS
BACKGROUND: Hospital charges and lengths of stay may be greater when adults with chronic conditions are admitted to children’s hospitals. Despite multiple efforts to improve pediatric-adult health care transitions, little guidance exists for transitioning inpatient care.
OBJECTIVE: This study sought to characterize pediatric-adult inpatient care transitions across general pediatric services at U.S. children’s hospitals.
DESIGN and SETTING: National survey of inpatient general pediatric service leaders at U.S. children’s hospitals from January 2016 to July 2016.
MEASUREMENT: Questionnaires assessed institutional characteristics, presence of inpatient transition initiatives (having a specific process and/or leader), and 22 inpatient transition activities. Scales of highly correlated activities were created using exploratory factor analysis. Logistic regression identified associations among institutional characteristics, transition activities, and presence of an inpatient transition initiative.
RESULTS: Of 195 children’s hospitals, 96 responded (49.2% response rate). Transition initiatives were present at 38% of children’s hospitals, more often where there were providers who were trained in both internal medicine and pediatrics or where there were outpatient transition processes. Specific activities were infrequent and varied widely from 2.1% (systems to track youth in transition) to 40.5% (addressing potential insurance problems). Institutions with initiatives more often consistently performed the majority of activities, including using checklists and creating patient-centered transition care plans. Of remaining activities, half involved transition planning, the essential step between readiness and transfer.
CONCLUSION: Relatively few inpatient general pediatric services at U.S. children’s hospitals have leaders or dedicated processes to shepherd transitions to adult-oriented inpatient care. Across institutions, there is wide variability in performance of activities to facilitate this transition. Feasible process and outcome measures are needed.
Also in JHM this month
Characterizing hospitalist practice and perceptions of critical care delivery
AUTHORS: Joseph R. Sweigart, MD, FACP, FHM; David Aymond, MD; Alfred Burger, MD, FACP, SFHM; Andy Kelly, MAS, MS; Nick Marzano, Med; Thomas McIlraith, MD, SFHM; Peter Morris, MD; Mark V. Williams, MD, FACP, MHM; and Eric M. Siegal, MD, SFHM, FCCM
Clinical decision making: Observing the smartphone user an observational study in predicting acute surgical patients’ suitability for discharge
AUTHORS: Richard Hoffmann, MBBS; Simon Harley, MBBS; Samuel Ellison, MBBS; and Peter G. Devitt, MBBS, FRACS
BACKGROUND: Hospital charges and lengths of stay may be greater when adults with chronic conditions are admitted to children’s hospitals. Despite multiple efforts to improve pediatric-adult health care transitions, little guidance exists for transitioning inpatient care.
OBJECTIVE: This study sought to characterize pediatric-adult inpatient care transitions across general pediatric services at U.S. children’s hospitals.
DESIGN and SETTING: National survey of inpatient general pediatric service leaders at U.S. children’s hospitals from January 2016 to July 2016.
MEASUREMENT: Questionnaires assessed institutional characteristics, presence of inpatient transition initiatives (having a specific process and/or leader), and 22 inpatient transition activities. Scales of highly correlated activities were created using exploratory factor analysis. Logistic regression identified associations among institutional characteristics, transition activities, and presence of an inpatient transition initiative.
RESULTS: Of 195 children’s hospitals, 96 responded (49.2% response rate). Transition initiatives were present at 38% of children’s hospitals, more often where there were providers who were trained in both internal medicine and pediatrics or where there were outpatient transition processes. Specific activities were infrequent and varied widely from 2.1% (systems to track youth in transition) to 40.5% (addressing potential insurance problems). Institutions with initiatives more often consistently performed the majority of activities, including using checklists and creating patient-centered transition care plans. Of remaining activities, half involved transition planning, the essential step between readiness and transfer.
CONCLUSION: Relatively few inpatient general pediatric services at U.S. children’s hospitals have leaders or dedicated processes to shepherd transitions to adult-oriented inpatient care. Across institutions, there is wide variability in performance of activities to facilitate this transition. Feasible process and outcome measures are needed.
Also in JHM this month
Characterizing hospitalist practice and perceptions of critical care delivery
AUTHORS: Joseph R. Sweigart, MD, FACP, FHM; David Aymond, MD; Alfred Burger, MD, FACP, SFHM; Andy Kelly, MAS, MS; Nick Marzano, Med; Thomas McIlraith, MD, SFHM; Peter Morris, MD; Mark V. Williams, MD, FACP, MHM; and Eric M. Siegal, MD, SFHM, FCCM
Clinical decision making: Observing the smartphone user an observational study in predicting acute surgical patients’ suitability for discharge
AUTHORS: Richard Hoffmann, MBBS; Simon Harley, MBBS; Samuel Ellison, MBBS; and Peter G. Devitt, MBBS, FRACS
Homelessness: Whose job is it?
Despite programs to end homelessness, it remains a substantial and growing problem in many cities in the United States.1,2 In 2016, there were an estimated 10,550 homeless people living in my home state of Colorado, a 6% increase from the prior year.2 A recent point-estimate study found that there were more than 5,000 homeless individuals in the Denver metropolitan area on a single night in January 2017.3 Because of the relative scarcity of housing, a growing number of cities like Denver now utilize a practice known as vulnerability indexing to prioritize homeless persons at high risk of mortality from medical conditions for placement in permanent supportive housing.4
Although hospitalists like myself frequently care for vulnerable homeless patients in the hospital, most have little formal training in how best to care for and advocate for these individuals beyond treating their acute medical need, and little direct contact with community organizations with expertise in doing so. Instead, we have learned informally through experience. Hospital providers are often frustrated by the perceived lack of services and support available to these patients, and there is substantial variability in the extent to which providers engage patients and community partners during and after hospitalization. Despite the growing practice of vulnerability indexing in the community, hospital-based providers do not routinely assess vulnerability with respect to housing. Previous research indicates that housing status is assessed in only a minority of homeless patients during their hospital stay.12 Thus, hospitalization often represents a missed opportunity to identify vulnerability and utilize it to connect patients with housing and other resources.
Addressing the significant known health disparities faced by homeless persons is one of the greatest health equity challenges of our time.13 We need better ways of understanding, identifying, and addressing vulnerability among homeless patients who are hospitalized, paired with improved integration with local community organizations. This will require moving beyond the idea that homelessness is the social worker’s job to one of shared responsibility and advocacy.
Collaborative research and other partnerships that engage both community organizations and individuals affected by homelessness are crucial to further understand the specific needs, barriers, challenges, and opportunities for improving hospital care and care transitions in this population. As well-respected community members and systems thinkers who witness these inequities on a daily basis, hospitalists are well positioned to help lead this work.
Dr. Stella is a hospitalist at Denver Health and Hospital Authority, and an associate professor of medicine at the University of Colorado. She is a member of The Hospitalist editorial advisory board.
References
1. Ending Chronic Homelessness. (Aug 2017). U.S. Interagency Council on Homelessness. Available at: https://www.usich.gov/goals/chronicsness. Accessed: Oct 21, 2017.
2. 2016 Annual Homeless Assessment Report (AHAR) to Congress. (Nov 2016). U.S. Department of Housing and Urban Development Office of Community Planning and Development, Part 1. Available at: https://www.hudexchange.info/resources/documents/2016-AHAR-Part-1.pdf. Accessed: Oct 21, 2017.
3. 2017 Point-In-Time Report, Seven-County Metro Denver Region. Metro Denver Homeless Initiative. Available at: http://www.mdhi.org/2017_pit. Accessed Oct 22, 2017.
4. Henwood BF et al. Examining mortality among formerly homeless adults enrolled in Housing First: An observational study. BMC Public Health. 2015;15:1209.
5. Weinstein LC et al. Moving from street to home: Health status of entrants to a Housing First program. J Prim Care Community Health. 2011;2:11–5.
6. Kushel MB et al. Factors associated with the health care utilization of homeless persons. JAMA. 2001;285(2):200-6.
7. Kushel MB et al. Emergency department use among the homeless and marginally housed: Results from a community-based study. Am J Public Health. 2002;92(5):778-84.
8. Baggett TP et al. Mortality among homeless adults in Boston: Shifts in causes of death over a 15-year period. JAMA Intern Med. 2013 Feb 11;173(3):189–95.
9. Johnson et al. For many patients who use large amounts of health care services, the need is intense yet temporary. Health Aff (Millwood). 2015 Aug;34(8):1312-9.
10. Durfee J et al. The impact of tailored intervention services on charges and mortality for adult super-utilizers. Healthc (Amst). 2017 Aug 25. pii: S2213-0764(17)30057-X. doi: 10.1016/j.hjdsi.2017.08.004. [Epub ahead of print]
11. Rinehart DJ et al. Identifying subgroups of adult super utilizers in an urban safety-net system using latent class analysis: Implications for clinical practice. Med Care. 2016 Sep 14. doi: 10.1097/MLR.0000000000000628. [Epub ahead of print]
12. Greysen RS et al. Understanding transitions of care from hospital to homeless shelter: A mixed-methods, community-based participatory approach. J Gen Intern Med. 2012;27(11):1484-91.
13. National Health Care for the Homeless Council. (Oct 2012). Improving Care Transitions for People Experiencing Homelessness. (Lead author: Sabrina Edgington, policy and program specialist.) Available at: www.nhchc.org/wp-content/uploads/2012/12/Policy_Brief_Care_Transitions.pdf. Accessed Oct 21, 2017.
14. Koh HK et al. Improving healthcare for homeless people. JAMA. 2016;316(24):2586-7.
Despite programs to end homelessness, it remains a substantial and growing problem in many cities in the United States.1,2 In 2016, there were an estimated 10,550 homeless people living in my home state of Colorado, a 6% increase from the prior year.2 A recent point-estimate study found that there were more than 5,000 homeless individuals in the Denver metropolitan area on a single night in January 2017.3 Because of the relative scarcity of housing, a growing number of cities like Denver now utilize a practice known as vulnerability indexing to prioritize homeless persons at high risk of mortality from medical conditions for placement in permanent supportive housing.4
Although hospitalists like myself frequently care for vulnerable homeless patients in the hospital, most have little formal training in how best to care for and advocate for these individuals beyond treating their acute medical need, and little direct contact with community organizations with expertise in doing so. Instead, we have learned informally through experience. Hospital providers are often frustrated by the perceived lack of services and support available to these patients, and there is substantial variability in the extent to which providers engage patients and community partners during and after hospitalization. Despite the growing practice of vulnerability indexing in the community, hospital-based providers do not routinely assess vulnerability with respect to housing. Previous research indicates that housing status is assessed in only a minority of homeless patients during their hospital stay.12 Thus, hospitalization often represents a missed opportunity to identify vulnerability and utilize it to connect patients with housing and other resources.
Addressing the significant known health disparities faced by homeless persons is one of the greatest health equity challenges of our time.13 We need better ways of understanding, identifying, and addressing vulnerability among homeless patients who are hospitalized, paired with improved integration with local community organizations. This will require moving beyond the idea that homelessness is the social worker’s job to one of shared responsibility and advocacy.
Collaborative research and other partnerships that engage both community organizations and individuals affected by homelessness are crucial to further understand the specific needs, barriers, challenges, and opportunities for improving hospital care and care transitions in this population. As well-respected community members and systems thinkers who witness these inequities on a daily basis, hospitalists are well positioned to help lead this work.
Dr. Stella is a hospitalist at Denver Health and Hospital Authority, and an associate professor of medicine at the University of Colorado. She is a member of The Hospitalist editorial advisory board.
References
1. Ending Chronic Homelessness. (Aug 2017). U.S. Interagency Council on Homelessness. Available at: https://www.usich.gov/goals/chronicsness. Accessed: Oct 21, 2017.
2. 2016 Annual Homeless Assessment Report (AHAR) to Congress. (Nov 2016). U.S. Department of Housing and Urban Development Office of Community Planning and Development, Part 1. Available at: https://www.hudexchange.info/resources/documents/2016-AHAR-Part-1.pdf. Accessed: Oct 21, 2017.
3. 2017 Point-In-Time Report, Seven-County Metro Denver Region. Metro Denver Homeless Initiative. Available at: http://www.mdhi.org/2017_pit. Accessed Oct 22, 2017.
4. Henwood BF et al. Examining mortality among formerly homeless adults enrolled in Housing First: An observational study. BMC Public Health. 2015;15:1209.
5. Weinstein LC et al. Moving from street to home: Health status of entrants to a Housing First program. J Prim Care Community Health. 2011;2:11–5.
6. Kushel MB et al. Factors associated with the health care utilization of homeless persons. JAMA. 2001;285(2):200-6.
7. Kushel MB et al. Emergency department use among the homeless and marginally housed: Results from a community-based study. Am J Public Health. 2002;92(5):778-84.
8. Baggett TP et al. Mortality among homeless adults in Boston: Shifts in causes of death over a 15-year period. JAMA Intern Med. 2013 Feb 11;173(3):189–95.
9. Johnson et al. For many patients who use large amounts of health care services, the need is intense yet temporary. Health Aff (Millwood). 2015 Aug;34(8):1312-9.
10. Durfee J et al. The impact of tailored intervention services on charges and mortality for adult super-utilizers. Healthc (Amst). 2017 Aug 25. pii: S2213-0764(17)30057-X. doi: 10.1016/j.hjdsi.2017.08.004. [Epub ahead of print]
11. Rinehart DJ et al. Identifying subgroups of adult super utilizers in an urban safety-net system using latent class analysis: Implications for clinical practice. Med Care. 2016 Sep 14. doi: 10.1097/MLR.0000000000000628. [Epub ahead of print]
12. Greysen RS et al. Understanding transitions of care from hospital to homeless shelter: A mixed-methods, community-based participatory approach. J Gen Intern Med. 2012;27(11):1484-91.
13. National Health Care for the Homeless Council. (Oct 2012). Improving Care Transitions for People Experiencing Homelessness. (Lead author: Sabrina Edgington, policy and program specialist.) Available at: www.nhchc.org/wp-content/uploads/2012/12/Policy_Brief_Care_Transitions.pdf. Accessed Oct 21, 2017.
14. Koh HK et al. Improving healthcare for homeless people. JAMA. 2016;316(24):2586-7.
Despite programs to end homelessness, it remains a substantial and growing problem in many cities in the United States.1,2 In 2016, there were an estimated 10,550 homeless people living in my home state of Colorado, a 6% increase from the prior year.2 A recent point-estimate study found that there were more than 5,000 homeless individuals in the Denver metropolitan area on a single night in January 2017.3 Because of the relative scarcity of housing, a growing number of cities like Denver now utilize a practice known as vulnerability indexing to prioritize homeless persons at high risk of mortality from medical conditions for placement in permanent supportive housing.4
Although hospitalists like myself frequently care for vulnerable homeless patients in the hospital, most have little formal training in how best to care for and advocate for these individuals beyond treating their acute medical need, and little direct contact with community organizations with expertise in doing so. Instead, we have learned informally through experience. Hospital providers are often frustrated by the perceived lack of services and support available to these patients, and there is substantial variability in the extent to which providers engage patients and community partners during and after hospitalization. Despite the growing practice of vulnerability indexing in the community, hospital-based providers do not routinely assess vulnerability with respect to housing. Previous research indicates that housing status is assessed in only a minority of homeless patients during their hospital stay.12 Thus, hospitalization often represents a missed opportunity to identify vulnerability and utilize it to connect patients with housing and other resources.
Addressing the significant known health disparities faced by homeless persons is one of the greatest health equity challenges of our time.13 We need better ways of understanding, identifying, and addressing vulnerability among homeless patients who are hospitalized, paired with improved integration with local community organizations. This will require moving beyond the idea that homelessness is the social worker’s job to one of shared responsibility and advocacy.
Collaborative research and other partnerships that engage both community organizations and individuals affected by homelessness are crucial to further understand the specific needs, barriers, challenges, and opportunities for improving hospital care and care transitions in this population. As well-respected community members and systems thinkers who witness these inequities on a daily basis, hospitalists are well positioned to help lead this work.
Dr. Stella is a hospitalist at Denver Health and Hospital Authority, and an associate professor of medicine at the University of Colorado. She is a member of The Hospitalist editorial advisory board.
References
1. Ending Chronic Homelessness. (Aug 2017). U.S. Interagency Council on Homelessness. Available at: https://www.usich.gov/goals/chronicsness. Accessed: Oct 21, 2017.
2. 2016 Annual Homeless Assessment Report (AHAR) to Congress. (Nov 2016). U.S. Department of Housing and Urban Development Office of Community Planning and Development, Part 1. Available at: https://www.hudexchange.info/resources/documents/2016-AHAR-Part-1.pdf. Accessed: Oct 21, 2017.
3. 2017 Point-In-Time Report, Seven-County Metro Denver Region. Metro Denver Homeless Initiative. Available at: http://www.mdhi.org/2017_pit. Accessed Oct 22, 2017.
4. Henwood BF et al. Examining mortality among formerly homeless adults enrolled in Housing First: An observational study. BMC Public Health. 2015;15:1209.
5. Weinstein LC et al. Moving from street to home: Health status of entrants to a Housing First program. J Prim Care Community Health. 2011;2:11–5.
6. Kushel MB et al. Factors associated with the health care utilization of homeless persons. JAMA. 2001;285(2):200-6.
7. Kushel MB et al. Emergency department use among the homeless and marginally housed: Results from a community-based study. Am J Public Health. 2002;92(5):778-84.
8. Baggett TP et al. Mortality among homeless adults in Boston: Shifts in causes of death over a 15-year period. JAMA Intern Med. 2013 Feb 11;173(3):189–95.
9. Johnson et al. For many patients who use large amounts of health care services, the need is intense yet temporary. Health Aff (Millwood). 2015 Aug;34(8):1312-9.
10. Durfee J et al. The impact of tailored intervention services on charges and mortality for adult super-utilizers. Healthc (Amst). 2017 Aug 25. pii: S2213-0764(17)30057-X. doi: 10.1016/j.hjdsi.2017.08.004. [Epub ahead of print]
11. Rinehart DJ et al. Identifying subgroups of adult super utilizers in an urban safety-net system using latent class analysis: Implications for clinical practice. Med Care. 2016 Sep 14. doi: 10.1097/MLR.0000000000000628. [Epub ahead of print]
12. Greysen RS et al. Understanding transitions of care from hospital to homeless shelter: A mixed-methods, community-based participatory approach. J Gen Intern Med. 2012;27(11):1484-91.
13. National Health Care for the Homeless Council. (Oct 2012). Improving Care Transitions for People Experiencing Homelessness. (Lead author: Sabrina Edgington, policy and program specialist.) Available at: www.nhchc.org/wp-content/uploads/2012/12/Policy_Brief_Care_Transitions.pdf. Accessed Oct 21, 2017.
14. Koh HK et al. Improving healthcare for homeless people. JAMA. 2016;316(24):2586-7.
Choosing location after discharge wisely
Of all the care decisions we make during a hospital stay, perhaps the one with the biggest implications for cost and quality is the one determining the location to which we send the patient after discharge.
Yet ironically, we haven’t typically participated in this decision, but instead have left it up to case managers and others to work with patients to determine discharge location. This is a missed opportunity, as patients first look to their doctor for guidance on this decision. Absent such guidance, they turn to other care team members for the conversation. With a principal focus on hospital length of stay, we have prioritized when patients are ready to leave over where they go after they leave.
In terms of cost during hospitalization and for the 30 days after discharge, for common conditions such as pneumonia, heart failure, COPD, or major joint replacement, Medicare spends nearly as much on postacute care – home health, skilled nursing facilities, inpatient rehabilitation, long-term acute care hospitals – as for hospital care.1 Further, an Institute of Medicine analysis showed that geographic variation in postacute care spending is responsible for three-quarters of all variation in Medicare spending.2 Such variation raises questions about the rigor with which postacute care decisions are made by hospital teams.
Perhaps most striking of all, hospitalist care (versus that of traditional primary care providers) has been associated with excess discharge rates to skilled nursing facilities, and savings that accrue under hospitalists during hospitalization are more than outweighed by spending on care during the postacute period.3
All of this leads me to my point: Hospitalists and inpatient teams need a defined process for selecting the most appropriate discharge location. Such a location should ideally be the least restrictive location suitable for a patient’s needs. In the box below, I propose a framework for the process. The domains listed in the box should be evaluated and discussed by the team, with early input and final approval by the patient and caregiver(s). The domains listed are not intended to be an exhaustive list, but rather to serve as the basis for discussion during discharge team rounds.
Identifying patient factors informing an optimal discharge location may represent a new skill set for many hospitalists and underscores the value of collaboration with team members who can provide needed information. In April, the Society of Hospital Medicine published the Revised Core Competencies in Hospital Medicine. In the Care of the Older Patient section, the authors state that hospitalists should be able to “describe postacute care options that can enable older patients to regain functional capacity.”4 Inherent in this competency is an understanding of not only patient factors in postacute care location decisions, but also the differing capabilities of home health agencies, skilled nursing facilities, inpatient rehabilitation facilities, and long-term acute care hospitals.
Dr. Whitcomb is chief medical officer at Remedy Partners in Darien, Conn., and cofounder and past president of the Society of Hospital Medicine. Contact him at [email protected].
References
1. Mechanic R. Post-acute care – the next frontier for controlling Medicare spending. N Engl J Med. 2014;370:692-4.
2. Newhouse JP, et al. Geographic variation in Medicare services. N Engl J Med. 2013;368:1465-8.
3. Kuo YF, et al. Association of hospitalist care with medical utilization after discharge: evidence of cost shift from a cohort study. Ann Intern Med. 2011;155(3):152-9.
4. Nichani S, et al. Core Competencies in Hospital Medicine 2017 Revision. Section 3: Healthcare Systems. J Hosp Med. 2017 April;12(1):S55-S82.
Framework for Selecting Appropriate Discharge Location
Patient Independence
- Can the patient perform activities of daily living?
- Can the patient ambulate?
- Is there cognitive impairment?
Caregiver Availability
- If the patient needs it, is a caregiver who is capable and reliable available? If so, to what extent is s/he available?
Therapy Needs
- Does the patient require PT, OT, and/or ST?
- How much and for how long?
Skilled Nursing Needs
- What, if anything, does the patient require in this area? For example, a new PEG tube, wound care, IV therapies, etc.
Social Factors
- Is there access to transportation, food, and safe housing?
Home Factors
- Are there stairs to enter the house or to get to the bedroom or bathroom?
- Has the home been modified to accommodate special needs? Is the home inhabitable?
Of all the care decisions we make during a hospital stay, perhaps the one with the biggest implications for cost and quality is the one determining the location to which we send the patient after discharge.
Yet ironically, we haven’t typically participated in this decision, but instead have left it up to case managers and others to work with patients to determine discharge location. This is a missed opportunity, as patients first look to their doctor for guidance on this decision. Absent such guidance, they turn to other care team members for the conversation. With a principal focus on hospital length of stay, we have prioritized when patients are ready to leave over where they go after they leave.
In terms of cost during hospitalization and for the 30 days after discharge, for common conditions such as pneumonia, heart failure, COPD, or major joint replacement, Medicare spends nearly as much on postacute care – home health, skilled nursing facilities, inpatient rehabilitation, long-term acute care hospitals – as for hospital care.1 Further, an Institute of Medicine analysis showed that geographic variation in postacute care spending is responsible for three-quarters of all variation in Medicare spending.2 Such variation raises questions about the rigor with which postacute care decisions are made by hospital teams.
Perhaps most striking of all, hospitalist care (versus that of traditional primary care providers) has been associated with excess discharge rates to skilled nursing facilities, and savings that accrue under hospitalists during hospitalization are more than outweighed by spending on care during the postacute period.3
All of this leads me to my point: Hospitalists and inpatient teams need a defined process for selecting the most appropriate discharge location. Such a location should ideally be the least restrictive location suitable for a patient’s needs. In the box below, I propose a framework for the process. The domains listed in the box should be evaluated and discussed by the team, with early input and final approval by the patient and caregiver(s). The domains listed are not intended to be an exhaustive list, but rather to serve as the basis for discussion during discharge team rounds.
Identifying patient factors informing an optimal discharge location may represent a new skill set for many hospitalists and underscores the value of collaboration with team members who can provide needed information. In April, the Society of Hospital Medicine published the Revised Core Competencies in Hospital Medicine. In the Care of the Older Patient section, the authors state that hospitalists should be able to “describe postacute care options that can enable older patients to regain functional capacity.”4 Inherent in this competency is an understanding of not only patient factors in postacute care location decisions, but also the differing capabilities of home health agencies, skilled nursing facilities, inpatient rehabilitation facilities, and long-term acute care hospitals.
Dr. Whitcomb is chief medical officer at Remedy Partners in Darien, Conn., and cofounder and past president of the Society of Hospital Medicine. Contact him at [email protected].
References
1. Mechanic R. Post-acute care – the next frontier for controlling Medicare spending. N Engl J Med. 2014;370:692-4.
2. Newhouse JP, et al. Geographic variation in Medicare services. N Engl J Med. 2013;368:1465-8.
3. Kuo YF, et al. Association of hospitalist care with medical utilization after discharge: evidence of cost shift from a cohort study. Ann Intern Med. 2011;155(3):152-9.
4. Nichani S, et al. Core Competencies in Hospital Medicine 2017 Revision. Section 3: Healthcare Systems. J Hosp Med. 2017 April;12(1):S55-S82.
Framework for Selecting Appropriate Discharge Location
Patient Independence
- Can the patient perform activities of daily living?
- Can the patient ambulate?
- Is there cognitive impairment?
Caregiver Availability
- If the patient needs it, is a caregiver who is capable and reliable available? If so, to what extent is s/he available?
Therapy Needs
- Does the patient require PT, OT, and/or ST?
- How much and for how long?
Skilled Nursing Needs
- What, if anything, does the patient require in this area? For example, a new PEG tube, wound care, IV therapies, etc.
Social Factors
- Is there access to transportation, food, and safe housing?
Home Factors
- Are there stairs to enter the house or to get to the bedroom or bathroom?
- Has the home been modified to accommodate special needs? Is the home inhabitable?
Of all the care decisions we make during a hospital stay, perhaps the one with the biggest implications for cost and quality is the one determining the location to which we send the patient after discharge.
Yet ironically, we haven’t typically participated in this decision, but instead have left it up to case managers and others to work with patients to determine discharge location. This is a missed opportunity, as patients first look to their doctor for guidance on this decision. Absent such guidance, they turn to other care team members for the conversation. With a principal focus on hospital length of stay, we have prioritized when patients are ready to leave over where they go after they leave.
In terms of cost during hospitalization and for the 30 days after discharge, for common conditions such as pneumonia, heart failure, COPD, or major joint replacement, Medicare spends nearly as much on postacute care – home health, skilled nursing facilities, inpatient rehabilitation, long-term acute care hospitals – as for hospital care.1 Further, an Institute of Medicine analysis showed that geographic variation in postacute care spending is responsible for three-quarters of all variation in Medicare spending.2 Such variation raises questions about the rigor with which postacute care decisions are made by hospital teams.
Perhaps most striking of all, hospitalist care (versus that of traditional primary care providers) has been associated with excess discharge rates to skilled nursing facilities, and savings that accrue under hospitalists during hospitalization are more than outweighed by spending on care during the postacute period.3
All of this leads me to my point: Hospitalists and inpatient teams need a defined process for selecting the most appropriate discharge location. Such a location should ideally be the least restrictive location suitable for a patient’s needs. In the box below, I propose a framework for the process. The domains listed in the box should be evaluated and discussed by the team, with early input and final approval by the patient and caregiver(s). The domains listed are not intended to be an exhaustive list, but rather to serve as the basis for discussion during discharge team rounds.
Identifying patient factors informing an optimal discharge location may represent a new skill set for many hospitalists and underscores the value of collaboration with team members who can provide needed information. In April, the Society of Hospital Medicine published the Revised Core Competencies in Hospital Medicine. In the Care of the Older Patient section, the authors state that hospitalists should be able to “describe postacute care options that can enable older patients to regain functional capacity.”4 Inherent in this competency is an understanding of not only patient factors in postacute care location decisions, but also the differing capabilities of home health agencies, skilled nursing facilities, inpatient rehabilitation facilities, and long-term acute care hospitals.
Dr. Whitcomb is chief medical officer at Remedy Partners in Darien, Conn., and cofounder and past president of the Society of Hospital Medicine. Contact him at [email protected].
References
1. Mechanic R. Post-acute care – the next frontier for controlling Medicare spending. N Engl J Med. 2014;370:692-4.
2. Newhouse JP, et al. Geographic variation in Medicare services. N Engl J Med. 2013;368:1465-8.
3. Kuo YF, et al. Association of hospitalist care with medical utilization after discharge: evidence of cost shift from a cohort study. Ann Intern Med. 2011;155(3):152-9.
4. Nichani S, et al. Core Competencies in Hospital Medicine 2017 Revision. Section 3: Healthcare Systems. J Hosp Med. 2017 April;12(1):S55-S82.
Framework for Selecting Appropriate Discharge Location
Patient Independence
- Can the patient perform activities of daily living?
- Can the patient ambulate?
- Is there cognitive impairment?
Caregiver Availability
- If the patient needs it, is a caregiver who is capable and reliable available? If so, to what extent is s/he available?
Therapy Needs
- Does the patient require PT, OT, and/or ST?
- How much and for how long?
Skilled Nursing Needs
- What, if anything, does the patient require in this area? For example, a new PEG tube, wound care, IV therapies, etc.
Social Factors
- Is there access to transportation, food, and safe housing?
Home Factors
- Are there stairs to enter the house or to get to the bedroom or bathroom?
- Has the home been modified to accommodate special needs? Is the home inhabitable?
How will SNF readmissions penalties affect hospitalists?
Starting in 2018, skilled nursing facilities (SNFs), like acute care hospitals before them, will be subject to a penalty of up to 2% of their Medicare reimbursement for posting higher-than-average rates of hospital readmissions.
The Protecting Access to Medicare Act of 2014 established a value-based purchasing component for SNFs, including incentives for high-performing facilities and a measure for all-cause, all-condition readmissions to any hospital from the SNF within 30 days following hospital discharge – designed to recognize and reward, or punish, facilities’ performance on preventing unnecessary readmissions. Public reporting of SNF quality data, including readmission rates, started in October 2017. Penalties follow a year later. Some patients’ readmissions could trigger penalties for both the hospital and the SNF.
According to 2010 data, 23.5% of patients discharged from acute care hospitals to SNFs were readmitted to the hospital within 30 days, at a financial cost of $10,362 per readmission or $4.34 billion per year.1 Seventy eight percent of these readmissions were labeled avoidable. More recent evidence suggests that hospitalization rates for dual-eligible patients living in long-term care facilities decreased by 31% between 2010 and 2015.2As increasing numbers of hospitalists spend some or all of their work week in post-acute care settings, how will the SNF readmission penalty affect their relationships with post-acute facilities?
Experts say SNFs – as with hospitals before them – lack the ability to allocate rewards or penalties for readmission rate performance to individual doctors. But increasingly close collaborative relationships between post-acute facilities and the hospitalists who work in post-acute care mean that the hospitalist has an important role in helping the SNF to manage its readmissions exposure.
“Hospitals and hospitalists want to keep good relationships with the SNFs they partner with, for a variety of reasons,” Dr. Frizner said. “We believe that the best way to reduce readmissions and unplanned transfers from the SNF is for the doctor to know the patient. We need dedicated doctors in the facility. We want hospitalists who already know the patient to come to the facility and see the patient there.”
The hospitalist’s role in post-acute care
Hospitalists who work in post-acute care typically make scheduled, billable medical visits to patients in long-term care facilities, and may also take on roles such as facility medical director or contribute to quality improvement. Relationships may be initiated by a facility seeking more medical coverage, by a hospitalist group seeking additional work or an ability to impact on the post-acute care delivered to hospital patients discharged to the facility, or by health systems, health plans, or accountable care organizations seeking to better manage the quality of care transitions for their beneficiaries.
“What I’m seeing is that with opportunities for bundled payments, we all have new incentives for moving patients along and reducing waste,” Dr. Boutwell said. “For hospitalists practicing in SNFs, it’s going to be a much bigger phenomenon. They’ll be called to reevaluate patients and make more visits than they have been accustomed to.” She hopes SNFs are studying what happened with hospitals’ readmission penalties, and will respond more quickly and effectively to their own penalty exposure.
“What we are seeing is an effort to shift folks to lower cost – but still clinically appropriate – levels of care,” he said. “These dynamics will force SNFs to reevaluate and improve their clinical competencies, to accept patients and then treat them in place. It’s no longer acceptable for the medical director to make rounds in person twice a month and do the rest by telephone.”
Instead, someone needs to be on site several times a week, working with nursing staff and developing protocols and pathways to control variability, Dr. Harrington said. “And in many cases that will be a hospitalist. Hospitalists are finding ways to partner and provide that level of care. I believe good hospitalist groups can change the facility for the better, and fairly quickly.”
What happens in post-acute care
Cari Levy, MD, PhD, who does hospital coverage and post-acute care for a number of facilities and home health agencies in the Denver area, calls the changes coming to SNFs a thrilling time for post-acute care.
“Suddenly medical professionals care about what happens in the post-acute world,” she said. “Everyone is now looking at the same measures. If this works the way it should, there would be a lot more mutual respect between providers.”
SNFs that are concerned about their readmissions rates will want to do root cause analysis to figure out what’s going on, Dr. Levy said. “Maybe the doctor didn’t do a good assessment. Maybe it was just a tough case. Once you start talking, you’ll develop systems to help everyone responsible. Hospitalists can be part of that conversation,” she said.
“You can have a good outcome at Shady Oaks and a terrible outcome at Whispering Pines, for all sorts of reasons. The hospital wants to make sure we’re sending patients to facilities that produce good outcomes,” he explained. “But there has to be communication between providers – the SNF medical director, the hospitalists, and the emergency department.”
A TeamHealth doctor in Phoenix has convened a consortium of providers from different care settings to meet and talk about cases and how they could have gone better. “The reality is, these conversations are going on all over,” Dr. Wilborn said. “What’s driving them is the realization of what we all need to do in this new environment.”
Opportunities from reforms
Robert Burke, MD, FHM, assistant chief of Hospital Medicine at the Denver VA Medical Center, is lead author of a study in the Journal of Hospital Medicine highlighting implications and opportunities from reforms in post-acute care.3 Hospitalists may not appreciate that post-acute care is poised to undergo transformative change from the recently legislated reforms, opening opportunities for hospitalists to improve health care value by improving transitions of care, he noted.
“My sense is that payment reform will put pressure on physicians to use home health care more often than institutional care, because of the cost pressures. We know that hospitalists choose long-term care facility placements less often when participating in bundled payment,” Dr. Burke said. “I think few hospitalists really know what happens on a day-to-day basis in SNFs – or in patients’ homes, for that matter.”
According to Dr. Burke, there’s just not enough data currently to guide these decisions. He said that, based on his research, the best thing hospitalists can do is try to understand what’s available in post-acute spaces, and build relationships with post-acute facilities.
“Find ways to get feedback on your discharge decisions,” he said. “Here in Colorado, we met recently with the local chapter of the Society for Post-Acute and Long-Term Care Medicine, also known as AMDA. It’s been revealing for everyone involved.”
He recommends AMDA’s learning modules – which are designed for doctors who are new to long-term care – to any hospitalist who is entering the post-acute world.
References
1. Mor V et al. The revolving door of rehospitalization from skilled nursing facilities. Health Aff (Millwood). 2010 Jan-Feb;29(1):57-64.
2. Brennan N et al. Data Brief: Sharp reduction in avoidable hospitalizations among long-term care facility residents. The CMS Blog, 2017 Jan 17.
3. Burke RE et al. Post-acute care reform: Implications and opportunities for hospitalists. J Hosp Med. 2017 Jan;12(1);46-51.
Starting in 2018, skilled nursing facilities (SNFs), like acute care hospitals before them, will be subject to a penalty of up to 2% of their Medicare reimbursement for posting higher-than-average rates of hospital readmissions.
The Protecting Access to Medicare Act of 2014 established a value-based purchasing component for SNFs, including incentives for high-performing facilities and a measure for all-cause, all-condition readmissions to any hospital from the SNF within 30 days following hospital discharge – designed to recognize and reward, or punish, facilities’ performance on preventing unnecessary readmissions. Public reporting of SNF quality data, including readmission rates, started in October 2017. Penalties follow a year later. Some patients’ readmissions could trigger penalties for both the hospital and the SNF.
According to 2010 data, 23.5% of patients discharged from acute care hospitals to SNFs were readmitted to the hospital within 30 days, at a financial cost of $10,362 per readmission or $4.34 billion per year.1 Seventy eight percent of these readmissions were labeled avoidable. More recent evidence suggests that hospitalization rates for dual-eligible patients living in long-term care facilities decreased by 31% between 2010 and 2015.2As increasing numbers of hospitalists spend some or all of their work week in post-acute care settings, how will the SNF readmission penalty affect their relationships with post-acute facilities?
Experts say SNFs – as with hospitals before them – lack the ability to allocate rewards or penalties for readmission rate performance to individual doctors. But increasingly close collaborative relationships between post-acute facilities and the hospitalists who work in post-acute care mean that the hospitalist has an important role in helping the SNF to manage its readmissions exposure.
“Hospitals and hospitalists want to keep good relationships with the SNFs they partner with, for a variety of reasons,” Dr. Frizner said. “We believe that the best way to reduce readmissions and unplanned transfers from the SNF is for the doctor to know the patient. We need dedicated doctors in the facility. We want hospitalists who already know the patient to come to the facility and see the patient there.”
The hospitalist’s role in post-acute care
Hospitalists who work in post-acute care typically make scheduled, billable medical visits to patients in long-term care facilities, and may also take on roles such as facility medical director or contribute to quality improvement. Relationships may be initiated by a facility seeking more medical coverage, by a hospitalist group seeking additional work or an ability to impact on the post-acute care delivered to hospital patients discharged to the facility, or by health systems, health plans, or accountable care organizations seeking to better manage the quality of care transitions for their beneficiaries.
“What I’m seeing is that with opportunities for bundled payments, we all have new incentives for moving patients along and reducing waste,” Dr. Boutwell said. “For hospitalists practicing in SNFs, it’s going to be a much bigger phenomenon. They’ll be called to reevaluate patients and make more visits than they have been accustomed to.” She hopes SNFs are studying what happened with hospitals’ readmission penalties, and will respond more quickly and effectively to their own penalty exposure.
“What we are seeing is an effort to shift folks to lower cost – but still clinically appropriate – levels of care,” he said. “These dynamics will force SNFs to reevaluate and improve their clinical competencies, to accept patients and then treat them in place. It’s no longer acceptable for the medical director to make rounds in person twice a month and do the rest by telephone.”
Instead, someone needs to be on site several times a week, working with nursing staff and developing protocols and pathways to control variability, Dr. Harrington said. “And in many cases that will be a hospitalist. Hospitalists are finding ways to partner and provide that level of care. I believe good hospitalist groups can change the facility for the better, and fairly quickly.”
What happens in post-acute care
Cari Levy, MD, PhD, who does hospital coverage and post-acute care for a number of facilities and home health agencies in the Denver area, calls the changes coming to SNFs a thrilling time for post-acute care.
“Suddenly medical professionals care about what happens in the post-acute world,” she said. “Everyone is now looking at the same measures. If this works the way it should, there would be a lot more mutual respect between providers.”
SNFs that are concerned about their readmissions rates will want to do root cause analysis to figure out what’s going on, Dr. Levy said. “Maybe the doctor didn’t do a good assessment. Maybe it was just a tough case. Once you start talking, you’ll develop systems to help everyone responsible. Hospitalists can be part of that conversation,” she said.
“You can have a good outcome at Shady Oaks and a terrible outcome at Whispering Pines, for all sorts of reasons. The hospital wants to make sure we’re sending patients to facilities that produce good outcomes,” he explained. “But there has to be communication between providers – the SNF medical director, the hospitalists, and the emergency department.”
A TeamHealth doctor in Phoenix has convened a consortium of providers from different care settings to meet and talk about cases and how they could have gone better. “The reality is, these conversations are going on all over,” Dr. Wilborn said. “What’s driving them is the realization of what we all need to do in this new environment.”
Opportunities from reforms
Robert Burke, MD, FHM, assistant chief of Hospital Medicine at the Denver VA Medical Center, is lead author of a study in the Journal of Hospital Medicine highlighting implications and opportunities from reforms in post-acute care.3 Hospitalists may not appreciate that post-acute care is poised to undergo transformative change from the recently legislated reforms, opening opportunities for hospitalists to improve health care value by improving transitions of care, he noted.
“My sense is that payment reform will put pressure on physicians to use home health care more often than institutional care, because of the cost pressures. We know that hospitalists choose long-term care facility placements less often when participating in bundled payment,” Dr. Burke said. “I think few hospitalists really know what happens on a day-to-day basis in SNFs – or in patients’ homes, for that matter.”
According to Dr. Burke, there’s just not enough data currently to guide these decisions. He said that, based on his research, the best thing hospitalists can do is try to understand what’s available in post-acute spaces, and build relationships with post-acute facilities.
“Find ways to get feedback on your discharge decisions,” he said. “Here in Colorado, we met recently with the local chapter of the Society for Post-Acute and Long-Term Care Medicine, also known as AMDA. It’s been revealing for everyone involved.”
He recommends AMDA’s learning modules – which are designed for doctors who are new to long-term care – to any hospitalist who is entering the post-acute world.
References
1. Mor V et al. The revolving door of rehospitalization from skilled nursing facilities. Health Aff (Millwood). 2010 Jan-Feb;29(1):57-64.
2. Brennan N et al. Data Brief: Sharp reduction in avoidable hospitalizations among long-term care facility residents. The CMS Blog, 2017 Jan 17.
3. Burke RE et al. Post-acute care reform: Implications and opportunities for hospitalists. J Hosp Med. 2017 Jan;12(1);46-51.
Starting in 2018, skilled nursing facilities (SNFs), like acute care hospitals before them, will be subject to a penalty of up to 2% of their Medicare reimbursement for posting higher-than-average rates of hospital readmissions.
The Protecting Access to Medicare Act of 2014 established a value-based purchasing component for SNFs, including incentives for high-performing facilities and a measure for all-cause, all-condition readmissions to any hospital from the SNF within 30 days following hospital discharge – designed to recognize and reward, or punish, facilities’ performance on preventing unnecessary readmissions. Public reporting of SNF quality data, including readmission rates, started in October 2017. Penalties follow a year later. Some patients’ readmissions could trigger penalties for both the hospital and the SNF.
According to 2010 data, 23.5% of patients discharged from acute care hospitals to SNFs were readmitted to the hospital within 30 days, at a financial cost of $10,362 per readmission or $4.34 billion per year.1 Seventy eight percent of these readmissions were labeled avoidable. More recent evidence suggests that hospitalization rates for dual-eligible patients living in long-term care facilities decreased by 31% between 2010 and 2015.2As increasing numbers of hospitalists spend some or all of their work week in post-acute care settings, how will the SNF readmission penalty affect their relationships with post-acute facilities?
Experts say SNFs – as with hospitals before them – lack the ability to allocate rewards or penalties for readmission rate performance to individual doctors. But increasingly close collaborative relationships between post-acute facilities and the hospitalists who work in post-acute care mean that the hospitalist has an important role in helping the SNF to manage its readmissions exposure.
“Hospitals and hospitalists want to keep good relationships with the SNFs they partner with, for a variety of reasons,” Dr. Frizner said. “We believe that the best way to reduce readmissions and unplanned transfers from the SNF is for the doctor to know the patient. We need dedicated doctors in the facility. We want hospitalists who already know the patient to come to the facility and see the patient there.”
The hospitalist’s role in post-acute care
Hospitalists who work in post-acute care typically make scheduled, billable medical visits to patients in long-term care facilities, and may also take on roles such as facility medical director or contribute to quality improvement. Relationships may be initiated by a facility seeking more medical coverage, by a hospitalist group seeking additional work or an ability to impact on the post-acute care delivered to hospital patients discharged to the facility, or by health systems, health plans, or accountable care organizations seeking to better manage the quality of care transitions for their beneficiaries.
“What I’m seeing is that with opportunities for bundled payments, we all have new incentives for moving patients along and reducing waste,” Dr. Boutwell said. “For hospitalists practicing in SNFs, it’s going to be a much bigger phenomenon. They’ll be called to reevaluate patients and make more visits than they have been accustomed to.” She hopes SNFs are studying what happened with hospitals’ readmission penalties, and will respond more quickly and effectively to their own penalty exposure.
“What we are seeing is an effort to shift folks to lower cost – but still clinically appropriate – levels of care,” he said. “These dynamics will force SNFs to reevaluate and improve their clinical competencies, to accept patients and then treat them in place. It’s no longer acceptable for the medical director to make rounds in person twice a month and do the rest by telephone.”
Instead, someone needs to be on site several times a week, working with nursing staff and developing protocols and pathways to control variability, Dr. Harrington said. “And in many cases that will be a hospitalist. Hospitalists are finding ways to partner and provide that level of care. I believe good hospitalist groups can change the facility for the better, and fairly quickly.”
What happens in post-acute care
Cari Levy, MD, PhD, who does hospital coverage and post-acute care for a number of facilities and home health agencies in the Denver area, calls the changes coming to SNFs a thrilling time for post-acute care.
“Suddenly medical professionals care about what happens in the post-acute world,” she said. “Everyone is now looking at the same measures. If this works the way it should, there would be a lot more mutual respect between providers.”
SNFs that are concerned about their readmissions rates will want to do root cause analysis to figure out what’s going on, Dr. Levy said. “Maybe the doctor didn’t do a good assessment. Maybe it was just a tough case. Once you start talking, you’ll develop systems to help everyone responsible. Hospitalists can be part of that conversation,” she said.
“You can have a good outcome at Shady Oaks and a terrible outcome at Whispering Pines, for all sorts of reasons. The hospital wants to make sure we’re sending patients to facilities that produce good outcomes,” he explained. “But there has to be communication between providers – the SNF medical director, the hospitalists, and the emergency department.”
A TeamHealth doctor in Phoenix has convened a consortium of providers from different care settings to meet and talk about cases and how they could have gone better. “The reality is, these conversations are going on all over,” Dr. Wilborn said. “What’s driving them is the realization of what we all need to do in this new environment.”
Opportunities from reforms
Robert Burke, MD, FHM, assistant chief of Hospital Medicine at the Denver VA Medical Center, is lead author of a study in the Journal of Hospital Medicine highlighting implications and opportunities from reforms in post-acute care.3 Hospitalists may not appreciate that post-acute care is poised to undergo transformative change from the recently legislated reforms, opening opportunities for hospitalists to improve health care value by improving transitions of care, he noted.
“My sense is that payment reform will put pressure on physicians to use home health care more often than institutional care, because of the cost pressures. We know that hospitalists choose long-term care facility placements less often when participating in bundled payment,” Dr. Burke said. “I think few hospitalists really know what happens on a day-to-day basis in SNFs – or in patients’ homes, for that matter.”
According to Dr. Burke, there’s just not enough data currently to guide these decisions. He said that, based on his research, the best thing hospitalists can do is try to understand what’s available in post-acute spaces, and build relationships with post-acute facilities.
“Find ways to get feedback on your discharge decisions,” he said. “Here in Colorado, we met recently with the local chapter of the Society for Post-Acute and Long-Term Care Medicine, also known as AMDA. It’s been revealing for everyone involved.”
He recommends AMDA’s learning modules – which are designed for doctors who are new to long-term care – to any hospitalist who is entering the post-acute world.
References
1. Mor V et al. The revolving door of rehospitalization from skilled nursing facilities. Health Aff (Millwood). 2010 Jan-Feb;29(1):57-64.
2. Brennan N et al. Data Brief: Sharp reduction in avoidable hospitalizations among long-term care facility residents. The CMS Blog, 2017 Jan 17.
3. Burke RE et al. Post-acute care reform: Implications and opportunities for hospitalists. J Hosp Med. 2017 Jan;12(1);46-51.
Transition in care from the MICU to the ward
Editor’s Note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform healthcare and revolutionize patient care. The program has been expanded for the 2017-18 year, offering two options for students to receive funding and engage in scholarly work during their first, second and third years of medical school. As a part of the program, recipients are required to write about their experience on a biweekly basis.
This summer, my research project focused on the highly vulnerable patients who are transferred from the medical intensive care unit to the general floor. Patients who are readmitted tend to have worse health outcomes, longer stays, higher mortality rates, and higher health care costs. Previous research shows that higher quality handoffs, where receiving and transferring providers share the same shared mental model, result in better outcomes. We were interested in learning whether these shared mental models are being formed as a result of handoffs between the ward and the MICU.
The current results reveal that 18% of MICU teams shared a complete mental model, 25% shared a strong shared mental model, 9% shared a weak mental model, 30% shared no mental model, and 18% of patient encounters did not have a sufficient number of MICU respondents. Regarding inter-team communication, 7% shared a full shared mental model, 49% shared a partial mental model, 30% shared no shared mental model, and 14% of unique patient encounters did not have enough respondents.
With complex patient cases, it can be difficult to identify the most important factor of care for a particular patient. However, I think this information would be very useful in identifying whether these exchanges result in individuals prioritizing the same factor of care for their respective patient. I think this information would be very useful in future quality improvement, and seeing whether this communication results in the formation of shared mental models.
Anton Garazha is a medical student at Chicago Medical School at Rosalind Franklin University in North Chicago. He received his bachelor of science degree in biology from Loyola University in Chicago in 2015 and his master of biomedical science degree from Rosalind Franklin University in 2016. Anton is very interested in community outreach and quality improvement, and in his spare time tutors students in science-based subjects.
Editor’s Note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform healthcare and revolutionize patient care. The program has been expanded for the 2017-18 year, offering two options for students to receive funding and engage in scholarly work during their first, second and third years of medical school. As a part of the program, recipients are required to write about their experience on a biweekly basis.
This summer, my research project focused on the highly vulnerable patients who are transferred from the medical intensive care unit to the general floor. Patients who are readmitted tend to have worse health outcomes, longer stays, higher mortality rates, and higher health care costs. Previous research shows that higher quality handoffs, where receiving and transferring providers share the same shared mental model, result in better outcomes. We were interested in learning whether these shared mental models are being formed as a result of handoffs between the ward and the MICU.
The current results reveal that 18% of MICU teams shared a complete mental model, 25% shared a strong shared mental model, 9% shared a weak mental model, 30% shared no mental model, and 18% of patient encounters did not have a sufficient number of MICU respondents. Regarding inter-team communication, 7% shared a full shared mental model, 49% shared a partial mental model, 30% shared no shared mental model, and 14% of unique patient encounters did not have enough respondents.
With complex patient cases, it can be difficult to identify the most important factor of care for a particular patient. However, I think this information would be very useful in identifying whether these exchanges result in individuals prioritizing the same factor of care for their respective patient. I think this information would be very useful in future quality improvement, and seeing whether this communication results in the formation of shared mental models.
Anton Garazha is a medical student at Chicago Medical School at Rosalind Franklin University in North Chicago. He received his bachelor of science degree in biology from Loyola University in Chicago in 2015 and his master of biomedical science degree from Rosalind Franklin University in 2016. Anton is very interested in community outreach and quality improvement, and in his spare time tutors students in science-based subjects.
Editor’s Note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform healthcare and revolutionize patient care. The program has been expanded for the 2017-18 year, offering two options for students to receive funding and engage in scholarly work during their first, second and third years of medical school. As a part of the program, recipients are required to write about their experience on a biweekly basis.
This summer, my research project focused on the highly vulnerable patients who are transferred from the medical intensive care unit to the general floor. Patients who are readmitted tend to have worse health outcomes, longer stays, higher mortality rates, and higher health care costs. Previous research shows that higher quality handoffs, where receiving and transferring providers share the same shared mental model, result in better outcomes. We were interested in learning whether these shared mental models are being formed as a result of handoffs between the ward and the MICU.
The current results reveal that 18% of MICU teams shared a complete mental model, 25% shared a strong shared mental model, 9% shared a weak mental model, 30% shared no mental model, and 18% of patient encounters did not have a sufficient number of MICU respondents. Regarding inter-team communication, 7% shared a full shared mental model, 49% shared a partial mental model, 30% shared no shared mental model, and 14% of unique patient encounters did not have enough respondents.
With complex patient cases, it can be difficult to identify the most important factor of care for a particular patient. However, I think this information would be very useful in identifying whether these exchanges result in individuals prioritizing the same factor of care for their respective patient. I think this information would be very useful in future quality improvement, and seeing whether this communication results in the formation of shared mental models.
Anton Garazha is a medical student at Chicago Medical School at Rosalind Franklin University in North Chicago. He received his bachelor of science degree in biology from Loyola University in Chicago in 2015 and his master of biomedical science degree from Rosalind Franklin University in 2016. Anton is very interested in community outreach and quality improvement, and in his spare time tutors students in science-based subjects.
Consider ‘impactibility’ to prevent hospital readmissions
With the goal of reducing 28-day or 30-day readmissions, some health care teams are turning to predictive models to identify patients at high risk for readmission and to efficiently focus resource-intensive prevention strategies. Recently, there’s been a rapid multiplying of these models.
Many of these models do accurately predict readmission risk, according to a recent BMJ editorial. “Among the 14 published models that target all unplanned readmissions (rather than readmissions for specific patient groups), the ‘C statistic’ ranges from 0.55 to 0.80, meaning that, when presented with two patients, these models correctly identify the higher risk individual between 55% and 80% of the time,” the authors wrote.
But, the authors suggested, the real value is not in simply making predictions but in using predictive models in ways that improve outcomes for patients.
“This will require linking predictive models to actionable opportunities for improving care,” they wrote. “Such linkages will most likely be identified through close collaboration between analytical teams, health care practitioners, and patients.” Being at high risk of readmission is not the only consideration; the patient must also be able to benefit from interventions being considered – they must be “impactible.”
“The distinction between predictive risk and impactibility might explain why practitioners tend to identify quite different patients for intervention than predictive risk models,” the authors wrote.
But together, predictive models and clinicians might produce more effective decisions than either does alone. “One of the strengths of predictive models is that they produce objective and consistent judgments regarding readmission risk, whereas clinical judgment can be affected by personal attitudes or attentiveness. Predictive risk models can also be operationalised across whole populations, and might therefore identify needs that would otherwise be missed by clinical teams (e.g., among more socioeconomically deprived neighbourhoods or groups with inadequate primary care). On the other hand, clinicians have access to a much wider range of information regarding patients than predictive risk models, which is essential to judge impactibility.”
The authors conclude, “The predictive modelling enterprise would benefit enormously from such collaboration because the real goal of this activity lies not in predicting the risk of readmission but in identifying patients at risk for preventable readmissions and ‘impactible’ by available interventions.”
Reference
Steventon A et al. Preventing hospital readmissions: The importance of considering ‘impactibility,’ not just predicted risk. BMJ Qual Saf. 2017 Oct;26(10):782-5. Accessed Oct. 9, 2017.
With the goal of reducing 28-day or 30-day readmissions, some health care teams are turning to predictive models to identify patients at high risk for readmission and to efficiently focus resource-intensive prevention strategies. Recently, there’s been a rapid multiplying of these models.
Many of these models do accurately predict readmission risk, according to a recent BMJ editorial. “Among the 14 published models that target all unplanned readmissions (rather than readmissions for specific patient groups), the ‘C statistic’ ranges from 0.55 to 0.80, meaning that, when presented with two patients, these models correctly identify the higher risk individual between 55% and 80% of the time,” the authors wrote.
But, the authors suggested, the real value is not in simply making predictions but in using predictive models in ways that improve outcomes for patients.
“This will require linking predictive models to actionable opportunities for improving care,” they wrote. “Such linkages will most likely be identified through close collaboration between analytical teams, health care practitioners, and patients.” Being at high risk of readmission is not the only consideration; the patient must also be able to benefit from interventions being considered – they must be “impactible.”
“The distinction between predictive risk and impactibility might explain why practitioners tend to identify quite different patients for intervention than predictive risk models,” the authors wrote.
But together, predictive models and clinicians might produce more effective decisions than either does alone. “One of the strengths of predictive models is that they produce objective and consistent judgments regarding readmission risk, whereas clinical judgment can be affected by personal attitudes or attentiveness. Predictive risk models can also be operationalised across whole populations, and might therefore identify needs that would otherwise be missed by clinical teams (e.g., among more socioeconomically deprived neighbourhoods or groups with inadequate primary care). On the other hand, clinicians have access to a much wider range of information regarding patients than predictive risk models, which is essential to judge impactibility.”
The authors conclude, “The predictive modelling enterprise would benefit enormously from such collaboration because the real goal of this activity lies not in predicting the risk of readmission but in identifying patients at risk for preventable readmissions and ‘impactible’ by available interventions.”
Reference
Steventon A et al. Preventing hospital readmissions: The importance of considering ‘impactibility,’ not just predicted risk. BMJ Qual Saf. 2017 Oct;26(10):782-5. Accessed Oct. 9, 2017.
With the goal of reducing 28-day or 30-day readmissions, some health care teams are turning to predictive models to identify patients at high risk for readmission and to efficiently focus resource-intensive prevention strategies. Recently, there’s been a rapid multiplying of these models.
Many of these models do accurately predict readmission risk, according to a recent BMJ editorial. “Among the 14 published models that target all unplanned readmissions (rather than readmissions for specific patient groups), the ‘C statistic’ ranges from 0.55 to 0.80, meaning that, when presented with two patients, these models correctly identify the higher risk individual between 55% and 80% of the time,” the authors wrote.
But, the authors suggested, the real value is not in simply making predictions but in using predictive models in ways that improve outcomes for patients.
“This will require linking predictive models to actionable opportunities for improving care,” they wrote. “Such linkages will most likely be identified through close collaboration between analytical teams, health care practitioners, and patients.” Being at high risk of readmission is not the only consideration; the patient must also be able to benefit from interventions being considered – they must be “impactible.”
“The distinction between predictive risk and impactibility might explain why practitioners tend to identify quite different patients for intervention than predictive risk models,” the authors wrote.
But together, predictive models and clinicians might produce more effective decisions than either does alone. “One of the strengths of predictive models is that they produce objective and consistent judgments regarding readmission risk, whereas clinical judgment can be affected by personal attitudes or attentiveness. Predictive risk models can also be operationalised across whole populations, and might therefore identify needs that would otherwise be missed by clinical teams (e.g., among more socioeconomically deprived neighbourhoods or groups with inadequate primary care). On the other hand, clinicians have access to a much wider range of information regarding patients than predictive risk models, which is essential to judge impactibility.”
The authors conclude, “The predictive modelling enterprise would benefit enormously from such collaboration because the real goal of this activity lies not in predicting the risk of readmission but in identifying patients at risk for preventable readmissions and ‘impactible’ by available interventions.”
Reference
Steventon A et al. Preventing hospital readmissions: The importance of considering ‘impactibility,’ not just predicted risk. BMJ Qual Saf. 2017 Oct;26(10):782-5. Accessed Oct. 9, 2017.
Using post-acute and long-term care quality report cards
The challenges of hospital discharge planning are well known and yet have not been adequately addressed by hospitalists and discharge teams. As the complexity of patient care needs has grown, so has the difficulty in developing appropriate discharge goals for post-acute and long term care (LTC), choosing the appropriate setting(s), and selecting appropriate providers. Post-acute and LTC needs may include rehabilitation, nursing care, home health, supportive services, and/or palliative care1 in an institutional setting or at home from a wide array of providers with varying levels of quality.
Even though 52% of U.S. hospitals received penalties for having higher-than-expected readmissions between 2013 and 2017,2 inadequate discharge planning for post-acute and LTC continues to contribute to high rates of all-cause 30-day rehospitalization. The discharge process sometimes is deficient in: discussion of goals; assessment of discharge needs; appropriate choice of discharge locations; and the provision of additional or different home services.3 Discharge decisions are complicated by the stressful circumstances of hospitalization and discharge deadlines.
Hospital discharge planning decisions fall heavily on patients, families, and caregivers, often with inadequate information about choices and options. More than 30 states have passed the Caregiver Advise, Record, and Enable (CARE) Act into law to require hospitals to provide resources for family caregiver education and instruction,7 but hospitals do not have to provide information on all LTC options and provider quality ratings.
Quality report cards about LTC providers – a major innovation for consumer education and choice – are often not used in the discharge process for a number of reasons. A significant concern is that using report cards will extend the length of stay. Rather than extending the decision-making time and the length of stay, the use of report cards can reduce length of stay.9 A focus on identifying the first available nursing home bed or LTC provider often ignores the need to identify the most appropriate high-quality providers.
Hospitals and health plans often have established networks of post-acute and LTC providers and these networks must be taken into account in the discharge process. Most hospital and health plan networks have providers with a wide range of ratings, allowing for choices within networks.
The Centers for Medicare and Medicaid Services (CMS) established a web-based nursing home report card called Nursing Home Compare in 1998 that includes information on facility characteristics, deficiencies, staffing information (since 2000), and resident quality indicators (since 2002). In 2008, the website added a “five-star” rating system for all U.S. nursing homes and all-cause 30-day readmission rates and successful discharge rates from nursing homes were incorporated into the ratings in 2016.
CMS also established a web-based home health website, which provides quality ratings. This website has general information, quality measures, and patient surveys with information on readmission rates from home health agency services.
After establishment of the CMS Nursing Home Compare rating system in 2008, nursing homes improved their scores on certain quality measures and consumer demand significantly increased for the best (5-star) facilities and decreased for 1-star facilities.10 More recently, a clinical trial of the use of a personalized version of Nursing Home Compare in the hospital discharge planning process found greater patient satisfaction, patients being more likely to go to higher ranked nursing homes, patients traveling further to nursing homes, and patients having shorter hospital stays, compared with the control group.9
Quality report cards show wide variations within and across states ranging from one star (poorest quality) to five stars (highest quality). More than one-third of nursing homes had relatively low overall star ratings (1 or 2 stars) serving 39 percent of residents in 2015.11 Federal nursing home regulatory violations range from zero to more than 40 deficiencies (average of 7) with a scope and severity ranging from minor to widespread harm or jeopardy (including deaths).12 Total nurse staffing hours (average, 4.1 hours per resident day) range from less than 3 hours to more than 5.5 hours per resident day and RN hours are 3.5 times higher in some nursing homes than in the lowest staffed homes.13 Hospital readmission rates for short-stay residents from nursing homes also vary widely (4%-52%; average, 21%).12,14
Hospitalists and discharge planners should inform patients, families, and caregivers about the federal and state LTC quality report cards, provide education and choices, and engage and assist them in the decision making process. Hospitals, health plans, and accountable care organizations also need to be more informed about the availability of and benefits of using quality report cards for developing post-acute and LTC provider networks. The use of high quality LTC network providers should be able to reduce hospital length of stay and hospital readmission rates, and improve patient and caregiver satisfaction.
Charlene Harrington, PhD, RN, is professor of sociology and nursing; Leslie Ross, PhD, is a research specialist and principal investigator of the Calqualitycare.org website project; and Jeffrey Newman, MD, MPH, is a professor at the Institute for Health and Aging, all at the University of California, San Francisco.
References
1. Mor V et al. The revolving door of rehospitalization from skilled nursing facilities. Health Aff (Millwood). 2010;29(1):57-64.
2. Thompson, MP, Waters, TM, Kaplan et al. Most hospitals received annual penalties for excess readmissions, but some fared better than others. Health Aff (Millwood). 36(5):893-901.
3. Auerbach AD et al. Preventability and causes of readmissions in a national cohort of general medicine patients. JAMA Intern Med. 2016;176(4):484-93.
4. Jack B et al. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med. 2009;150(3):178-87.
5. Hansen LO et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8(8)421-7.
6. Naylor MD et al. The care span: The importance of transitional care in achieving health reform. Health Aff (Millwood). 2011;30(4):746-54.
7. Coleman EA. Family caregivers as partners in care transitions: The caregiver advise record and enable act. J Hosp Med. 2016 Dec;11(12):883-5.
8. Leppin AL et al. Preventing 30-day hospital readmissions: a systematic review and meta-analysis of randomized trials. JAMA Internal Med. 2014;174(7):1095-107.
9. Mukamel DB et al. Personalizing nursing home compare and the discharge from hospitals to nursing homes. Health Serv Res. 2016;1(6):2076-2094.
10. Werner RM et al. Changes in consumer demand following public reporting of summary quality ratings: An evaluation in nursing homes. Health Serv Res. 2016;51 Suppl 2:1291-309.
11. Boccuti C et al. Reading the stars: nursing home quality star ratings, nationally and by state. Kaiser Family Foundation Issue Brief. May 2015.
12. Centers for Medicare and Medicaid Services. Nursing home compare data archives. May 2017 monthly files. Quality MSR Claims data. https://data.medicare.gov/data/archives/nursing-home-compare. Accessed July 15, 2017.
13. Harrington C et al. The need for higher minimum staffing standards in U.S. nursing homes. Health Serv Insights. 2016;9:13-9.
14. Mor V et al. The revolving door of rehospitalization from skilled nursing facilities. Health Aff (Millwood). 2010;29(1):57-64.
The challenges of hospital discharge planning are well known and yet have not been adequately addressed by hospitalists and discharge teams. As the complexity of patient care needs has grown, so has the difficulty in developing appropriate discharge goals for post-acute and long term care (LTC), choosing the appropriate setting(s), and selecting appropriate providers. Post-acute and LTC needs may include rehabilitation, nursing care, home health, supportive services, and/or palliative care1 in an institutional setting or at home from a wide array of providers with varying levels of quality.
Even though 52% of U.S. hospitals received penalties for having higher-than-expected readmissions between 2013 and 2017,2 inadequate discharge planning for post-acute and LTC continues to contribute to high rates of all-cause 30-day rehospitalization. The discharge process sometimes is deficient in: discussion of goals; assessment of discharge needs; appropriate choice of discharge locations; and the provision of additional or different home services.3 Discharge decisions are complicated by the stressful circumstances of hospitalization and discharge deadlines.
Hospital discharge planning decisions fall heavily on patients, families, and caregivers, often with inadequate information about choices and options. More than 30 states have passed the Caregiver Advise, Record, and Enable (CARE) Act into law to require hospitals to provide resources for family caregiver education and instruction,7 but hospitals do not have to provide information on all LTC options and provider quality ratings.
Quality report cards about LTC providers – a major innovation for consumer education and choice – are often not used in the discharge process for a number of reasons. A significant concern is that using report cards will extend the length of stay. Rather than extending the decision-making time and the length of stay, the use of report cards can reduce length of stay.9 A focus on identifying the first available nursing home bed or LTC provider often ignores the need to identify the most appropriate high-quality providers.
Hospitals and health plans often have established networks of post-acute and LTC providers and these networks must be taken into account in the discharge process. Most hospital and health plan networks have providers with a wide range of ratings, allowing for choices within networks.
The Centers for Medicare and Medicaid Services (CMS) established a web-based nursing home report card called Nursing Home Compare in 1998 that includes information on facility characteristics, deficiencies, staffing information (since 2000), and resident quality indicators (since 2002). In 2008, the website added a “five-star” rating system for all U.S. nursing homes and all-cause 30-day readmission rates and successful discharge rates from nursing homes were incorporated into the ratings in 2016.
CMS also established a web-based home health website, which provides quality ratings. This website has general information, quality measures, and patient surveys with information on readmission rates from home health agency services.
After establishment of the CMS Nursing Home Compare rating system in 2008, nursing homes improved their scores on certain quality measures and consumer demand significantly increased for the best (5-star) facilities and decreased for 1-star facilities.10 More recently, a clinical trial of the use of a personalized version of Nursing Home Compare in the hospital discharge planning process found greater patient satisfaction, patients being more likely to go to higher ranked nursing homes, patients traveling further to nursing homes, and patients having shorter hospital stays, compared with the control group.9
Quality report cards show wide variations within and across states ranging from one star (poorest quality) to five stars (highest quality). More than one-third of nursing homes had relatively low overall star ratings (1 or 2 stars) serving 39 percent of residents in 2015.11 Federal nursing home regulatory violations range from zero to more than 40 deficiencies (average of 7) with a scope and severity ranging from minor to widespread harm or jeopardy (including deaths).12 Total nurse staffing hours (average, 4.1 hours per resident day) range from less than 3 hours to more than 5.5 hours per resident day and RN hours are 3.5 times higher in some nursing homes than in the lowest staffed homes.13 Hospital readmission rates for short-stay residents from nursing homes also vary widely (4%-52%; average, 21%).12,14
Hospitalists and discharge planners should inform patients, families, and caregivers about the federal and state LTC quality report cards, provide education and choices, and engage and assist them in the decision making process. Hospitals, health plans, and accountable care organizations also need to be more informed about the availability of and benefits of using quality report cards for developing post-acute and LTC provider networks. The use of high quality LTC network providers should be able to reduce hospital length of stay and hospital readmission rates, and improve patient and caregiver satisfaction.
Charlene Harrington, PhD, RN, is professor of sociology and nursing; Leslie Ross, PhD, is a research specialist and principal investigator of the Calqualitycare.org website project; and Jeffrey Newman, MD, MPH, is a professor at the Institute for Health and Aging, all at the University of California, San Francisco.
References
1. Mor V et al. The revolving door of rehospitalization from skilled nursing facilities. Health Aff (Millwood). 2010;29(1):57-64.
2. Thompson, MP, Waters, TM, Kaplan et al. Most hospitals received annual penalties for excess readmissions, but some fared better than others. Health Aff (Millwood). 36(5):893-901.
3. Auerbach AD et al. Preventability and causes of readmissions in a national cohort of general medicine patients. JAMA Intern Med. 2016;176(4):484-93.
4. Jack B et al. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med. 2009;150(3):178-87.
5. Hansen LO et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8(8)421-7.
6. Naylor MD et al. The care span: The importance of transitional care in achieving health reform. Health Aff (Millwood). 2011;30(4):746-54.
7. Coleman EA. Family caregivers as partners in care transitions: The caregiver advise record and enable act. J Hosp Med. 2016 Dec;11(12):883-5.
8. Leppin AL et al. Preventing 30-day hospital readmissions: a systematic review and meta-analysis of randomized trials. JAMA Internal Med. 2014;174(7):1095-107.
9. Mukamel DB et al. Personalizing nursing home compare and the discharge from hospitals to nursing homes. Health Serv Res. 2016;1(6):2076-2094.
10. Werner RM et al. Changes in consumer demand following public reporting of summary quality ratings: An evaluation in nursing homes. Health Serv Res. 2016;51 Suppl 2:1291-309.
11. Boccuti C et al. Reading the stars: nursing home quality star ratings, nationally and by state. Kaiser Family Foundation Issue Brief. May 2015.
12. Centers for Medicare and Medicaid Services. Nursing home compare data archives. May 2017 monthly files. Quality MSR Claims data. https://data.medicare.gov/data/archives/nursing-home-compare. Accessed July 15, 2017.
13. Harrington C et al. The need for higher minimum staffing standards in U.S. nursing homes. Health Serv Insights. 2016;9:13-9.
14. Mor V et al. The revolving door of rehospitalization from skilled nursing facilities. Health Aff (Millwood). 2010;29(1):57-64.
The challenges of hospital discharge planning are well known and yet have not been adequately addressed by hospitalists and discharge teams. As the complexity of patient care needs has grown, so has the difficulty in developing appropriate discharge goals for post-acute and long term care (LTC), choosing the appropriate setting(s), and selecting appropriate providers. Post-acute and LTC needs may include rehabilitation, nursing care, home health, supportive services, and/or palliative care1 in an institutional setting or at home from a wide array of providers with varying levels of quality.
Even though 52% of U.S. hospitals received penalties for having higher-than-expected readmissions between 2013 and 2017,2 inadequate discharge planning for post-acute and LTC continues to contribute to high rates of all-cause 30-day rehospitalization. The discharge process sometimes is deficient in: discussion of goals; assessment of discharge needs; appropriate choice of discharge locations; and the provision of additional or different home services.3 Discharge decisions are complicated by the stressful circumstances of hospitalization and discharge deadlines.
Hospital discharge planning decisions fall heavily on patients, families, and caregivers, often with inadequate information about choices and options. More than 30 states have passed the Caregiver Advise, Record, and Enable (CARE) Act into law to require hospitals to provide resources for family caregiver education and instruction,7 but hospitals do not have to provide information on all LTC options and provider quality ratings.
Quality report cards about LTC providers – a major innovation for consumer education and choice – are often not used in the discharge process for a number of reasons. A significant concern is that using report cards will extend the length of stay. Rather than extending the decision-making time and the length of stay, the use of report cards can reduce length of stay.9 A focus on identifying the first available nursing home bed or LTC provider often ignores the need to identify the most appropriate high-quality providers.
Hospitals and health plans often have established networks of post-acute and LTC providers and these networks must be taken into account in the discharge process. Most hospital and health plan networks have providers with a wide range of ratings, allowing for choices within networks.
The Centers for Medicare and Medicaid Services (CMS) established a web-based nursing home report card called Nursing Home Compare in 1998 that includes information on facility characteristics, deficiencies, staffing information (since 2000), and resident quality indicators (since 2002). In 2008, the website added a “five-star” rating system for all U.S. nursing homes and all-cause 30-day readmission rates and successful discharge rates from nursing homes were incorporated into the ratings in 2016.
CMS also established a web-based home health website, which provides quality ratings. This website has general information, quality measures, and patient surveys with information on readmission rates from home health agency services.
After establishment of the CMS Nursing Home Compare rating system in 2008, nursing homes improved their scores on certain quality measures and consumer demand significantly increased for the best (5-star) facilities and decreased for 1-star facilities.10 More recently, a clinical trial of the use of a personalized version of Nursing Home Compare in the hospital discharge planning process found greater patient satisfaction, patients being more likely to go to higher ranked nursing homes, patients traveling further to nursing homes, and patients having shorter hospital stays, compared with the control group.9
Quality report cards show wide variations within and across states ranging from one star (poorest quality) to five stars (highest quality). More than one-third of nursing homes had relatively low overall star ratings (1 or 2 stars) serving 39 percent of residents in 2015.11 Federal nursing home regulatory violations range from zero to more than 40 deficiencies (average of 7) with a scope and severity ranging from minor to widespread harm or jeopardy (including deaths).12 Total nurse staffing hours (average, 4.1 hours per resident day) range from less than 3 hours to more than 5.5 hours per resident day and RN hours are 3.5 times higher in some nursing homes than in the lowest staffed homes.13 Hospital readmission rates for short-stay residents from nursing homes also vary widely (4%-52%; average, 21%).12,14
Hospitalists and discharge planners should inform patients, families, and caregivers about the federal and state LTC quality report cards, provide education and choices, and engage and assist them in the decision making process. Hospitals, health plans, and accountable care organizations also need to be more informed about the availability of and benefits of using quality report cards for developing post-acute and LTC provider networks. The use of high quality LTC network providers should be able to reduce hospital length of stay and hospital readmission rates, and improve patient and caregiver satisfaction.
Charlene Harrington, PhD, RN, is professor of sociology and nursing; Leslie Ross, PhD, is a research specialist and principal investigator of the Calqualitycare.org website project; and Jeffrey Newman, MD, MPH, is a professor at the Institute for Health and Aging, all at the University of California, San Francisco.
References
1. Mor V et al. The revolving door of rehospitalization from skilled nursing facilities. Health Aff (Millwood). 2010;29(1):57-64.
2. Thompson, MP, Waters, TM, Kaplan et al. Most hospitals received annual penalties for excess readmissions, but some fared better than others. Health Aff (Millwood). 36(5):893-901.
3. Auerbach AD et al. Preventability and causes of readmissions in a national cohort of general medicine patients. JAMA Intern Med. 2016;176(4):484-93.
4. Jack B et al. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med. 2009;150(3):178-87.
5. Hansen LO et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8(8)421-7.
6. Naylor MD et al. The care span: The importance of transitional care in achieving health reform. Health Aff (Millwood). 2011;30(4):746-54.
7. Coleman EA. Family caregivers as partners in care transitions: The caregiver advise record and enable act. J Hosp Med. 2016 Dec;11(12):883-5.
8. Leppin AL et al. Preventing 30-day hospital readmissions: a systematic review and meta-analysis of randomized trials. JAMA Internal Med. 2014;174(7):1095-107.
9. Mukamel DB et al. Personalizing nursing home compare and the discharge from hospitals to nursing homes. Health Serv Res. 2016;1(6):2076-2094.
10. Werner RM et al. Changes in consumer demand following public reporting of summary quality ratings: An evaluation in nursing homes. Health Serv Res. 2016;51 Suppl 2:1291-309.
11. Boccuti C et al. Reading the stars: nursing home quality star ratings, nationally and by state. Kaiser Family Foundation Issue Brief. May 2015.
12. Centers for Medicare and Medicaid Services. Nursing home compare data archives. May 2017 monthly files. Quality MSR Claims data. https://data.medicare.gov/data/archives/nursing-home-compare. Accessed July 15, 2017.
13. Harrington C et al. The need for higher minimum staffing standards in U.S. nursing homes. Health Serv Insights. 2016;9:13-9.
14. Mor V et al. The revolving door of rehospitalization from skilled nursing facilities. Health Aff (Millwood). 2010;29(1):57-64.
Delving into the details
Editor’s note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform health care and revolutionize patient care. The program has been expanded for the 2017-2018 year, offering two options for students to receive funding and engage in scholarly work during their first, second, and third years of medical school. As a part of the longitudinal (18-month) program, recipients are required to write about their experience on a monthly basis.
For my research project, we are looking to develop a tool that would use data from within 24 hours of a patient’s admission to the hospital to predict whether they will require post-acute care placement after discharge. While I have often been summarizing my project with this broad one-liner, in the last two weeks I have been delving more into the details of what exactly we mean by “data from within 24 hours of a patient’s admission.”
We are going through each of the variables systematically to take into account prior literature on how they were treated in other studies, as well as the practical limitations imposed by the data-gathering within our own system to choose how these values will be selected for each admission. My mentor Dr. Eduard Vasilevskis is helping me with making these decisions, based on the prototype model that was the inspiration for this project. Once we have identified all of the details of each variable we want to track, Dr. Jesse Ehrenfeld will be facilitating our use of the database.
Certainly this project has helped illuminate not only research-specific hurdles, but also underscores the fundamental difficulty of clinical decision-making in the first 24 hours of a patient’s admission. With data changing rapidly and sometimes incomplete data, clinicians need to quickly make care decisions that can impact a lot more than the patient’s post-discharge destination.
We anticipate that once we’ve made these choices, there will be further choices to make about how to treat these variables in the analysis. We hope to have the assistance of an experienced statistician to help guide us in making those decisions.
Monisha Bhatia, a native of Nashville, Tenn., is a fourth-year medical student at Vanderbilt University in Nashville. She is hoping to pursue either a residency in internal medicine or a combined internal medicine/emergency medicine program. Prior to medical school, she completed a JD/MPH program at Boston University, and she hopes to use her legal training in working with regulatory authorities to improve access to health care for all Americans.
Editor’s note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform health care and revolutionize patient care. The program has been expanded for the 2017-2018 year, offering two options for students to receive funding and engage in scholarly work during their first, second, and third years of medical school. As a part of the longitudinal (18-month) program, recipients are required to write about their experience on a monthly basis.
For my research project, we are looking to develop a tool that would use data from within 24 hours of a patient’s admission to the hospital to predict whether they will require post-acute care placement after discharge. While I have often been summarizing my project with this broad one-liner, in the last two weeks I have been delving more into the details of what exactly we mean by “data from within 24 hours of a patient’s admission.”
We are going through each of the variables systematically to take into account prior literature on how they were treated in other studies, as well as the practical limitations imposed by the data-gathering within our own system to choose how these values will be selected for each admission. My mentor Dr. Eduard Vasilevskis is helping me with making these decisions, based on the prototype model that was the inspiration for this project. Once we have identified all of the details of each variable we want to track, Dr. Jesse Ehrenfeld will be facilitating our use of the database.
Certainly this project has helped illuminate not only research-specific hurdles, but also underscores the fundamental difficulty of clinical decision-making in the first 24 hours of a patient’s admission. With data changing rapidly and sometimes incomplete data, clinicians need to quickly make care decisions that can impact a lot more than the patient’s post-discharge destination.
We anticipate that once we’ve made these choices, there will be further choices to make about how to treat these variables in the analysis. We hope to have the assistance of an experienced statistician to help guide us in making those decisions.
Monisha Bhatia, a native of Nashville, Tenn., is a fourth-year medical student at Vanderbilt University in Nashville. She is hoping to pursue either a residency in internal medicine or a combined internal medicine/emergency medicine program. Prior to medical school, she completed a JD/MPH program at Boston University, and she hopes to use her legal training in working with regulatory authorities to improve access to health care for all Americans.
Editor’s note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform health care and revolutionize patient care. The program has been expanded for the 2017-2018 year, offering two options for students to receive funding and engage in scholarly work during their first, second, and third years of medical school. As a part of the longitudinal (18-month) program, recipients are required to write about their experience on a monthly basis.
For my research project, we are looking to develop a tool that would use data from within 24 hours of a patient’s admission to the hospital to predict whether they will require post-acute care placement after discharge. While I have often been summarizing my project with this broad one-liner, in the last two weeks I have been delving more into the details of what exactly we mean by “data from within 24 hours of a patient’s admission.”
We are going through each of the variables systematically to take into account prior literature on how they were treated in other studies, as well as the practical limitations imposed by the data-gathering within our own system to choose how these values will be selected for each admission. My mentor Dr. Eduard Vasilevskis is helping me with making these decisions, based on the prototype model that was the inspiration for this project. Once we have identified all of the details of each variable we want to track, Dr. Jesse Ehrenfeld will be facilitating our use of the database.
Certainly this project has helped illuminate not only research-specific hurdles, but also underscores the fundamental difficulty of clinical decision-making in the first 24 hours of a patient’s admission. With data changing rapidly and sometimes incomplete data, clinicians need to quickly make care decisions that can impact a lot more than the patient’s post-discharge destination.
We anticipate that once we’ve made these choices, there will be further choices to make about how to treat these variables in the analysis. We hope to have the assistance of an experienced statistician to help guide us in making those decisions.
Monisha Bhatia, a native of Nashville, Tenn., is a fourth-year medical student at Vanderbilt University in Nashville. She is hoping to pursue either a residency in internal medicine or a combined internal medicine/emergency medicine program. Prior to medical school, she completed a JD/MPH program at Boston University, and she hopes to use her legal training in working with regulatory authorities to improve access to health care for all Americans.
Patient handoffs and research methods
Editor’s Note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform healthcare and revolutionize patient care. The program has been expanded for the 2017-18 year, offering two options for students to receive funding and engage in scholarly work during their first, second and third years of medical school. As a part of the program, recipients are required to write about their experience on a biweekly basis.
As I wrap up my work for the summer, I am happy to reflect on my wonderful experiences. One of my greatest lessons from my mentors, Dr. Vineet Arora and Dr. Juan Rojas, is the development of a complete methods section and the careful necessity of approaching data and writing the abstract. I now realize the necessity of carefully maintaining a written account of how we approached the data, as it allows us to both communicate it to our audience and to look back on how to further organize it.
Furthermore, my approach towards research significantly shifted in the time I spent this summer. Previously, I would focus primarily on results; however, from having performed a comprehensive literature review, I now focus on the way the data was approached and presented, the way the team kept careful track of methods, and the way they use previous research to establish their project. My previous experience was around quantitative research; the way that research teams approach qualitative research often differs from one another, often requiring a special level of ingenuity in approach and analysis, often due to the highly variable data.
After my experience at University of Chicago, I feel significantly more comfortable approaching research. One of my greatest goals regarding my research was to gain a better understanding of the interaction between various departments and the general ward in order to better prepare myself to be an effective physician. By asking the question, “What do you think is the most important factor regarding the management of this patient?”, I fully realized my deep interest in medical management: any research I approach as a physician would be closely intertwined to clinical medicine.
I am very, very thankful for the opportunity to learn from highly experienced physicians and researchers, and I will use this experience going forward with any clinical and research experiences I encounter.
Anton Garazha is a medical student at Chicago Medical School at Rosalind Franklin University in North Chicago. He received his bachelor of science degree in biology from Loyola University in Chicago in 2015 and his master of biomedical science degree from Rosalind Franklin University in 2016. Anton is very interested in community outreach and quality improvement, and in his spare time tutors students in science-based subjects.
Editor’s Note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform healthcare and revolutionize patient care. The program has been expanded for the 2017-18 year, offering two options for students to receive funding and engage in scholarly work during their first, second and third years of medical school. As a part of the program, recipients are required to write about their experience on a biweekly basis.
As I wrap up my work for the summer, I am happy to reflect on my wonderful experiences. One of my greatest lessons from my mentors, Dr. Vineet Arora and Dr. Juan Rojas, is the development of a complete methods section and the careful necessity of approaching data and writing the abstract. I now realize the necessity of carefully maintaining a written account of how we approached the data, as it allows us to both communicate it to our audience and to look back on how to further organize it.
Furthermore, my approach towards research significantly shifted in the time I spent this summer. Previously, I would focus primarily on results; however, from having performed a comprehensive literature review, I now focus on the way the data was approached and presented, the way the team kept careful track of methods, and the way they use previous research to establish their project. My previous experience was around quantitative research; the way that research teams approach qualitative research often differs from one another, often requiring a special level of ingenuity in approach and analysis, often due to the highly variable data.
After my experience at University of Chicago, I feel significantly more comfortable approaching research. One of my greatest goals regarding my research was to gain a better understanding of the interaction between various departments and the general ward in order to better prepare myself to be an effective physician. By asking the question, “What do you think is the most important factor regarding the management of this patient?”, I fully realized my deep interest in medical management: any research I approach as a physician would be closely intertwined to clinical medicine.
I am very, very thankful for the opportunity to learn from highly experienced physicians and researchers, and I will use this experience going forward with any clinical and research experiences I encounter.
Anton Garazha is a medical student at Chicago Medical School at Rosalind Franklin University in North Chicago. He received his bachelor of science degree in biology from Loyola University in Chicago in 2015 and his master of biomedical science degree from Rosalind Franklin University in 2016. Anton is very interested in community outreach and quality improvement, and in his spare time tutors students in science-based subjects.
Editor’s Note: The Society of Hospital Medicine’s (SHM’s) Physician in Training Committee launched a scholarship program in 2015 for medical students to help transform healthcare and revolutionize patient care. The program has been expanded for the 2017-18 year, offering two options for students to receive funding and engage in scholarly work during their first, second and third years of medical school. As a part of the program, recipients are required to write about their experience on a biweekly basis.
As I wrap up my work for the summer, I am happy to reflect on my wonderful experiences. One of my greatest lessons from my mentors, Dr. Vineet Arora and Dr. Juan Rojas, is the development of a complete methods section and the careful necessity of approaching data and writing the abstract. I now realize the necessity of carefully maintaining a written account of how we approached the data, as it allows us to both communicate it to our audience and to look back on how to further organize it.
Furthermore, my approach towards research significantly shifted in the time I spent this summer. Previously, I would focus primarily on results; however, from having performed a comprehensive literature review, I now focus on the way the data was approached and presented, the way the team kept careful track of methods, and the way they use previous research to establish their project. My previous experience was around quantitative research; the way that research teams approach qualitative research often differs from one another, often requiring a special level of ingenuity in approach and analysis, often due to the highly variable data.
After my experience at University of Chicago, I feel significantly more comfortable approaching research. One of my greatest goals regarding my research was to gain a better understanding of the interaction between various departments and the general ward in order to better prepare myself to be an effective physician. By asking the question, “What do you think is the most important factor regarding the management of this patient?”, I fully realized my deep interest in medical management: any research I approach as a physician would be closely intertwined to clinical medicine.
I am very, very thankful for the opportunity to learn from highly experienced physicians and researchers, and I will use this experience going forward with any clinical and research experiences I encounter.
Anton Garazha is a medical student at Chicago Medical School at Rosalind Franklin University in North Chicago. He received his bachelor of science degree in biology from Loyola University in Chicago in 2015 and his master of biomedical science degree from Rosalind Franklin University in 2016. Anton is very interested in community outreach and quality improvement, and in his spare time tutors students in science-based subjects.
Identifying high-value care practices
A new tool can help where hospitalists need it most: at the bedside.
The focus on providing high-value care (HVC) continues to grow and expand in health care today. Still, most education around HVC currently happens in a formalized setting – lectures, modules, and so on, says Carolyn D. Sy, MD, interim director of the Hospital Medicine Service at the University of Washington, Seattle, and coauthor of a recent abstract about a new tool to address this shortcoming. “There are no instruments for measuring HVC discussions or practices at the bedside, confounding efforts to assess behavior changes associated with curricular interventions,” she said.
So she and other doctors undertook a study to identify 10 HVC topics in three domains (quality, cost, patient values), then measured their reliability with the goal of designing an HVC Rounding Tool and showing that it is an effective tool to measure observable markers of HVC at the bedside. “This is critical as it addresses an important educational gap in translating HVC from theoretical knowledge to bedside practice,” Dr. Sy said.
The tool is designed to capture multidisciplinary participation, she says, including involvement from not only faculty, fellows, or trainees, but also nursing, pharmacists, families, and other members of the health care team. The tool can be used as a peer feedback instrument to help physicians integrate HVC topics during bedside rounds or as a metric to assess the educational efficacy of future curriculum.
“The HVC Rounding Tool provides an opportunity for faculty development through peer observation and feedback on the integration and role modeling of HVC at the bedside,” Dr. Sy said. “It also is an instrument to help assess the educational efficacy of formal HVC curriculum and translation into bedside practice. Lastly, it is a tool that could be used to measure the relationship between HVC behaviors and actual patient outcomes such as length of stay, readmissions, cost of hospitalization – a feature with increasing importance given our move toward value-based health care.”
Reference
Sy CD, McDaniel C, Bradford M, et al. The Development and Validation of a High Value Care Rounding Tool Using the Delphi Method [abstract]. J Hosp Med. 2017; 12 (suppl 2). http://www.shmabstracts.com/abstract/the-development-and-validation-of-a-high-value-care-rounding-tool-using-the-delphi-method/. Accessed June 6, 2017.
A new tool can help where hospitalists need it most: at the bedside.
The focus on providing high-value care (HVC) continues to grow and expand in health care today. Still, most education around HVC currently happens in a formalized setting – lectures, modules, and so on, says Carolyn D. Sy, MD, interim director of the Hospital Medicine Service at the University of Washington, Seattle, and coauthor of a recent abstract about a new tool to address this shortcoming. “There are no instruments for measuring HVC discussions or practices at the bedside, confounding efforts to assess behavior changes associated with curricular interventions,” she said.
So she and other doctors undertook a study to identify 10 HVC topics in three domains (quality, cost, patient values), then measured their reliability with the goal of designing an HVC Rounding Tool and showing that it is an effective tool to measure observable markers of HVC at the bedside. “This is critical as it addresses an important educational gap in translating HVC from theoretical knowledge to bedside practice,” Dr. Sy said.
The tool is designed to capture multidisciplinary participation, she says, including involvement from not only faculty, fellows, or trainees, but also nursing, pharmacists, families, and other members of the health care team. The tool can be used as a peer feedback instrument to help physicians integrate HVC topics during bedside rounds or as a metric to assess the educational efficacy of future curriculum.
“The HVC Rounding Tool provides an opportunity for faculty development through peer observation and feedback on the integration and role modeling of HVC at the bedside,” Dr. Sy said. “It also is an instrument to help assess the educational efficacy of formal HVC curriculum and translation into bedside practice. Lastly, it is a tool that could be used to measure the relationship between HVC behaviors and actual patient outcomes such as length of stay, readmissions, cost of hospitalization – a feature with increasing importance given our move toward value-based health care.”
Reference
Sy CD, McDaniel C, Bradford M, et al. The Development and Validation of a High Value Care Rounding Tool Using the Delphi Method [abstract]. J Hosp Med. 2017; 12 (suppl 2). http://www.shmabstracts.com/abstract/the-development-and-validation-of-a-high-value-care-rounding-tool-using-the-delphi-method/. Accessed June 6, 2017.
A new tool can help where hospitalists need it most: at the bedside.
The focus on providing high-value care (HVC) continues to grow and expand in health care today. Still, most education around HVC currently happens in a formalized setting – lectures, modules, and so on, says Carolyn D. Sy, MD, interim director of the Hospital Medicine Service at the University of Washington, Seattle, and coauthor of a recent abstract about a new tool to address this shortcoming. “There are no instruments for measuring HVC discussions or practices at the bedside, confounding efforts to assess behavior changes associated with curricular interventions,” she said.
So she and other doctors undertook a study to identify 10 HVC topics in three domains (quality, cost, patient values), then measured their reliability with the goal of designing an HVC Rounding Tool and showing that it is an effective tool to measure observable markers of HVC at the bedside. “This is critical as it addresses an important educational gap in translating HVC from theoretical knowledge to bedside practice,” Dr. Sy said.
The tool is designed to capture multidisciplinary participation, she says, including involvement from not only faculty, fellows, or trainees, but also nursing, pharmacists, families, and other members of the health care team. The tool can be used as a peer feedback instrument to help physicians integrate HVC topics during bedside rounds or as a metric to assess the educational efficacy of future curriculum.
“The HVC Rounding Tool provides an opportunity for faculty development through peer observation and feedback on the integration and role modeling of HVC at the bedside,” Dr. Sy said. “It also is an instrument to help assess the educational efficacy of formal HVC curriculum and translation into bedside practice. Lastly, it is a tool that could be used to measure the relationship between HVC behaviors and actual patient outcomes such as length of stay, readmissions, cost of hospitalization – a feature with increasing importance given our move toward value-based health care.”
Reference
Sy CD, McDaniel C, Bradford M, et al. The Development and Validation of a High Value Care Rounding Tool Using the Delphi Method [abstract]. J Hosp Med. 2017; 12 (suppl 2). http://www.shmabstracts.com/abstract/the-development-and-validation-of-a-high-value-care-rounding-tool-using-the-delphi-method/. Accessed June 6, 2017.