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Marr J, Shen K. Medicare Advantage growth and skilled nursing facility finances. Health Serv Res 2024; 59:e14298. [PMID: 38450687 PMCID: PMC11063089 DOI: 10.1111/1475-6773.14298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024] Open
Abstract
OBJECTIVE To examine the relationship between growth in Medicare Advantage (MA) enrollment and changes in finances at skilled nursing facilities (SNFs). DATA SOURCES Medicare SNF cost reports, LTCFocus.org data, and county MA penetration rates. STUDY DESIGN We used ordinary least squares regression with SNF and year fixed effects. Our primary outcomes were SNF revenues, expenses, profits, and occupancy. Our primary independent variable was the yearly county Medicare Advantage penetration. DATA COLLECTION/EXTRACTION We linked facility-year data from 2012 to 2019 obtained from cost reports and LTCFocus.org to county-year MA penetration. PRINCIPAL FINDINGS A 10 percentage point increase in county MA enrollment was associated with a $213,883.89 (95% Confidence Interval [CI]: -296,869.08, -130,898.71) decrease in revenue, a $132,456.19 (95% CI: -203,852.28, -61,060.10) decrease in expenses, and a 0.59 percentage point (95% CI: -0.97, -0.21) decrease in profit margin. A 10 percentage point increase in county MA enrollment was associated with a decline (-318.93; 95% CI: -468.84, -169.02) in the number of resident-days (a measure of occupancy) as well as a decline in the revenue per resident day ($4.50; 95% CI: -6.81, -2.20), potentially because of lower prices in MA. There was also a decline in expenses per patient day (-2.35; 95% CI: -4.76, 0.05), though this was only statistically significant at the 10% level. While increased MA enrollment was associated with a substantial decline in the number of Medicare resident days (487.53; 95% CI: -588.70, -386.37), this was partially offset by an increase in other payer (e.g., private pay) resident days (285.91; 95% CI: 128.18, 443.63). Increased MA enrollment was not associated with changes in the number of Medicaid resident days or a decrease in staffing per resident day. CONCLUSION SNFs in counties with more MA growth had substantially greater relative declines in revenue, expenses, and profit margins. The continued growth of MA may result in significant changes in the SNF industry.
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Affiliation(s)
- Jeffrey Marr
- Department of Health Policy and ManagementJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Karen Shen
- Department of Health Policy and ManagementJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
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Liu R, Wyk BV, Quiñones AR, Allore HG. Longitudinal Care Network Changes and Associated Healthcare Utilization Among Care Recipients. Res Aging 2024; 46:327-338. [PMID: 38261524 DOI: 10.1177/01640275241229162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
This study examines caregiver networks, including size, composition, and stability, and their associations with the likelihood of hospitalization and skilled-nursing facility (SNF) admissions. Data from the National Health and Aging Trends Study linked to Center for Medicare and Medicaid Services data were analyzed for 3855 older adults across five survey waves. Generalized estimating equation models assessed the associations. The findings indicate each additional paid caregiver was associated with higher adjusted risk ratios (aRR) for hospitalization (aRR = 1.24, 95% CI 1.10-1.41) and SNF admission (aRR = 1.28, 95% CI 1.06-1.54) among care recipients, a pattern that is also observed with the addition of unpaid caregivers (hospitalization: aRR = 1.13, 95% CI 1.06-1.20; SNF: aRR = 1.12, 95% CI 1.02-1.23). These results suggest that policies and approaches to enhance the quality and coordination of caregivers may be warranted to support improved outcomes for care recipients.
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Affiliation(s)
- Ruotong Liu
- Department of Family Medicine, Oregon Health and Science University, Portland, OR, USA
| | - Brent Vander Wyk
- Department of Biostatistics, Yale University, New Haven, CT, USA
| | - Ana R Quiñones
- Department of Family Medicine, Oregon Health and Science University, Portland, OR, USA
- OHSU-PSU School of Public Health, Portland, OR, USA
| | - Heather G Allore
- Department of Biostatistics, Yale University, New Haven, CT, USA
- Department of Internal Medicine, Yale University, New Haven, CT, USA
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Kuye IO, Prichett LM, Stewart RW, Berkowitz SA, Buresh ME. The association between opioid use disorder and skilled nursing facility acceptances: A multicenter retrospective cohort study. J Hosp Med 2024; 19:377-385. [PMID: 38458154 DOI: 10.1002/jhm.13302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 01/21/2024] [Accepted: 01/31/2024] [Indexed: 03/10/2024]
Abstract
BACKGROUND Prior single-hospital studies have documented barriers to acceptance that hospitalized patients with opioid use disorder (OUD) face when referred to skilled nursing facilities (SNFs). OBJECTIVE To examine the impact of OUD on the number of SNF referrals and the proportion of referrals accepted. DESIGN, SETTINGS, AND PARTICIPANTS A retrospective cohort study of hospitalizations with SNF referrals in 2019 at two academic hospitals in Baltimore, MD. EXPOSURE OUD status was determined by receipt of medications for OUD during admission, upon discharge, or the presence of a diagnosis code for OUD. KEY RESULTS The cohort included 6043 hospitalizations (5440 hospitalizations of patients without OUD and 603 hospitalizations of patients with OUD). Hospitalizations of patients with OUD had more SNF referrals sent (8.9 vs. 5.6, p < .001), had a lower proportion of SNF referrals accepted (31.3% vs. 46.9%, p < .001), and were less likely to be discharged to an SNF (65.6% vs. 70.3%, p = .003). The effect of OUD status on the number of SNF referrals and the proportion of referrals accepted remained significant in multivariable analyses. Our subanalysis showed that reduced acceptances were driven by the hospitalizations of patients discharged without medications for OUD and those receiving methadone. Hospitalizations of patients discharged on buprenorphine were accepted at the same rates as hospitalizations of patients without OUD. CONCLUSIONS This multicenter retrospective cohort study found that hospitalizations of patients with OUD had more SNF referrals sent and fewer referrals accepted. Further work is needed to address the limited discharge options for patients with OUD.
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Affiliation(s)
- Ifedayo O Kuye
- Division of Hospital Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Laura M Prichett
- Biostatistics, Epidemiology and Data Management Core, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Rosalyn W Stewart
- Division of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Division of Addiction Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Scott A Berkowitz
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Megan E Buresh
- Division of Addiction Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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Abstract
BACKGROUND Despite widespread adoption of surveillance testing for coronavirus disease 2019 (Covid-19) among staff members in skilled nursing facilities, evidence is limited regarding its relationship with outcomes among facility residents. METHODS Using data obtained from 2020 to 2022, we performed a retrospective cohort study of testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among staff members in 13,424 skilled nursing facilities during three pandemic periods: before vaccine approval, before the B.1.1.529 (omicron) variant wave, and during the omicron wave. We assessed staff testing volumes during weeks without Covid-19 cases relative to other skilled nursing facilities in the same county, along with Covid-19 cases and deaths among residents during potential outbreaks (defined as the occurrence of a case after 2 weeks with no cases). We reported adjusted differences in outcomes between high-testing facilities (90th percentile of test volume) and low-testing facilities (10th percentile). The two primary outcomes were the weekly cumulative number of Covid-19 cases and related deaths among residents during potential outbreaks. RESULTS During the overall study period, 519.7 cases of Covid-19 per 100 potential outbreaks were reported among residents of high-testing facilities as compared with 591.2 cases among residents of low-testing facilities (adjusted difference, -71.5; 95% confidence interval [CI], -91.3 to -51.6). During the same period, 42.7 deaths per 100 potential outbreaks occurred in high-testing facilities as compared with 49.8 deaths in low-testing facilities (adjusted difference, -7.1; 95% CI, -11.0 to -3.2). Before vaccine availability, high- and low-testing facilities had 759.9 cases and 1060.2 cases, respectively, per 100 potential outbreaks (adjusted difference, -300.3; 95% CI, -377.1 to -223.5), along with 125.2 and 166.8 deaths (adjusted difference, -41.6; 95% CI, -57.8 to -25.5). Before the omicron wave, the numbers of cases and deaths were similar in high- and low-testing facilities; during the omicron wave, high-testing facilities had fewer cases among residents, but deaths were similar in the two groups. CONCLUSIONS Greater surveillance testing of staff members at skilled nursing facilities was associated with clinically meaningful reductions in Covid-19 cases and deaths among residents, particularly before vaccine availability.
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Affiliation(s)
- Brian E McGarry
- From the Division of Geriatrics and Aging, Department of Medicine, University of Rochester, Rochester, NY (B.E.M.); the Anderson School of Management, University of California, Los Angeles, Los Angeles (A.D.G.); and the Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, and the Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital - both in Boston (M.L.B.)
| | - Ashvin D Gandhi
- From the Division of Geriatrics and Aging, Department of Medicine, University of Rochester, Rochester, NY (B.E.M.); the Anderson School of Management, University of California, Los Angeles, Los Angeles (A.D.G.); and the Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, and the Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital - both in Boston (M.L.B.)
| | - Michael L Barnett
- From the Division of Geriatrics and Aging, Department of Medicine, University of Rochester, Rochester, NY (B.E.M.); the Anderson School of Management, University of California, Los Angeles, Los Angeles (A.D.G.); and the Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, and the Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital - both in Boston (M.L.B.)
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Larkin H. High COVID-19 Rates Prompt Call for Better Nursing Home Protections. JAMA 2023; 329:531. [PMID: 36723972 DOI: 10.1001/jama.2023.0740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
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Barnett ML, Waken RJ, Zheng J, Orav EJ, Epstein AM, Grabowski DC, Joynt Maddox KE. Changes in Health and Quality of Life in US Skilled Nursing Facilities by COVID-19 Exposure Status in 2020. JAMA 2022; 328:941-950. [PMID: 36036916 PMCID: PMC9425288 DOI: 10.1001/jama.2022.15071] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
IMPORTANCE During the COVID-19 pandemic, the US federal government required that skilled nursing facilities (SNFs) close to visitors and eliminate communal activities. Although these policies were intended to protect residents, they may have had unintended negative effects. OBJECTIVE To assess health outcomes among SNFs with and without known COVID-19 cases. DESIGN, SETTING, AND PARTICIPANTS This retrospective observational study used US Medicare claims and Minimum Data Set 3.0 for January through November in each year beginning in 2018 and ending in 2020 including 15 477 US SNFs with 2 985 864 resident-years. EXPOSURES January through November of calendar years 2018, 2019, and 2020. COVID-19 diagnoses were used to assign SNFs into 2 mutually exclusive groups with varying membership by month in 2020: active COVID-19 (≥1 COVID-19 diagnosis in the current or past month) or no-known COVID-19 (no observed diagnosis by that month). MAIN OUTCOMES AND MEASURES Monthly rates of mortality, hospitalization, emergency department (ED) visits, and monthly changes in activities of daily living (ADLs), body weight, and depressive symptoms. Each SNF in 2018 and 2019 served as its own control for 2020. RESULTS In 2018-2019, mean monthly mortality was 2.2%, hospitalization 3.0%, and ED visit rate 2.9% overall. In 2020, among active COVID-19 SNFs compared with their own 2018-2019 baseline, mortality increased by 1.60% (95% CI, 1.58% to 1.62%), hospitalizations decreased by 0.10% (95% CI, -0.12% to -0.09%), and ED visit rates decreased by 0.57% (95% CI, -0.59% to -0.55%). Among no-known COVID-19 SNFs, mortality decreased by 0.15% (95% CI, -0.16% to -0.13%), hospitalizations by 0.83% (95% CI, -0.85% to -0.81%), and ED visits by 0.79% (95% CI, -0.81% to -0.77%). All changes were statistically significant. In 2018-2019, across all SNFs, residents required assistance with an additional 0.89 ADLs between January and November, and lost 1.9 lb; 27.1% had worsened depressive symptoms. In 2020, residents in active COVID-19 SNFs required assistance with an additional 0.36 ADLs (95% CI, 0.34 to 0.38), lost 3.1 lb (95% CI, -3.2 to -3.0 lb) more weight, and were 4.4% (95% CI, 4.1% to 4.7%) more likely to have worsened depressive symptoms, all statistically significant changes. In 2020, residents in no-known COVID-19 SNFs had no significant change in ADLs (-0.06 [95% CI, -0.12 to 0.01]), but lost 1.8 lb (95% CI, -2.1 to -1.5 lb) more weight and were 3.2% more likely (95% CI, 2.3% to 4.1%) to have worsened depressive symptoms, both statistically significant changes. CONCLUSIONS AND RELEVANCE Among skilled nursing facilities in the US during the first year of the COVID-19 pandemic and prior to the availability of COVID-19 vaccination, mortality and functional decline significantly increased at facilities with active COVID-19 cases compared with the prepandemic period, while a modest statistically significant decrease in mortality was observed at facilities that had never had a known COVID-19 case. Weight loss and depressive symptoms significantly increased in skilled nursing facilities in the first year of the pandemic, regardless of COVID-19 status.
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Affiliation(s)
- Michael L. Barnett
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - R. J. Waken
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine in St Louis, Missouri
- Center for Health Economics and Policy, Institute of Public Health at Washington University in St Louis, Missouri
| | - Jie Zheng
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - E. John Orav
- Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Arnold M. Epstein
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - David C. Grabowski
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
| | - Karen E. Joynt Maddox
- Cardiovascular Division, Department of Medicine, Washington University School of Medicine in St Louis, Missouri
- Center for Health Economics and Policy, Institute of Public Health at Washington University in St Louis, Missouri
- Associate Editor, JAMA
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Antony AR, Champion JD. Predictors of Acute Care Transfers From Skilled Nursing Facilities: Recommendations for Preventing Unnecessary Hospitalization. Res Gerontol Nurs 2022; 15:172-178. [PMID: 35708962 DOI: 10.3928/19404921-20220609-01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Preventing acute care transfers from skilled nursing facilities (SNFs) is a challenge secondary to residents' associated debilitated status and comorbidities. Acute care transfers often result in serious complications and unnecessary health care expenditure. Literature implies that approximately two thirds of these acute care transfers could be prevented using proactive interventions. The purpose of the current study was to identify the predictors of acute care transfers for SNF residents in developing relevant prevention strategies. A retrospective chart review using multivariate logistic regression analysis showed increased odds of SNF hospitalization was significantly associated with impaired cognition, chronic obstructive pulmonary disease, and chronic kidney disease, whereas decreased odds of hospitalization was identified among non-Hispanic White residents. Study recommendations include prompt assessment of comorbid symptomatology among SNF residents for the timely management and prevention of unnecessary acute care transfers. [Research in Gerontological Nursing, xx(x), xx-xx.].
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Ying M, Temkin-Greener H, Thirukumaran CP, Maddox KEJ, Holloway RG, Li Y. Skilled Nursing Facility Participation in a Voluntary Medicare Bundled Payment Program: Association With Facility Financial Performance. Med Care 2022; 60:83-92. [PMID: 34812788 PMCID: PMC8665005 DOI: 10.1097/mlr.0000000000001659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
IMPORTANCE Model 3 of the Bundled Payments for Care Improvement (BPCI) is an alternative payment model in which an entity takes accountability for the episode costs. It is unclear how BPCI affected the overall skilled nursing facility (SNF) financial performance and the differences between facilities with differing racial/ethnic and socioeconomic status (SES) composition of the residents. OBJECTIVE The objective of this study was to determine associations between BPCI participation and SNF finances and across-facility differences in SNF financial performance. DESIGN, SETTING, AND PARTICIPANTS A longitudinal study spanning 2010-2017, based on difference-in-differences analyses for 575 persistent-participation SNFs, 496 dropout SNFs, and 13,630 eligible nonparticipating SNFs. MAIN OUTCOME MEASURES Inflation-adjusted operating expenses, revenues, profit, and profit margin. RESULTS BPCI was associated with reductions of $0.63 million in operating expenses and $0.57 million in operating revenues for the persistent-participation group but had no impact on the dropout group compared with nonparticipating SNFs. Among persistent-participation SNFs, the BPCI-related declines were $0.74 million in operating expenses and $0.52 million in operating revenues for majority-serving SNFs; and $1.33 and $0.82 million in operating expenses and revenues, respectively, for non-Medicaid-dependent SNFs. The between-facility SES gaps in operating expenses were reduced (differential difference-in-differences estimate=$1.09 million). Among dropout SNFs, BPCI showed mixed effects on across-facility SES and racial/ethnic differences in operating expenses and revenues. The BPCI program showed no effect on operating profit measures. CONCLUSIONS BPCI led to reduced operating expenses and revenues for SNFs that participated and remained in the program but had no effect on operating profit indicators and mixed effects on SES and racial/ethnic differences across SNFs.
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Affiliation(s)
- Meiling Ying
- Department of Public Health Sciences, Division of Health Policy and Outcomes Research, University of Rochester Medical Center, Rochester, NY
| | - Helena Temkin-Greener
- Department of Public Health Sciences, Division of Health Policy and Outcomes Research, University of Rochester Medical Center, Rochester, NY
| | - Caroline Pinto Thirukumaran
- Department of Public Health Sciences, Division of Health Policy and Outcomes Research, University of Rochester Medical Center, Rochester, NY
- Department of Orthopaedics, University of Rochester Medical Center, Rochester, NY
| | - Karen E. Joynt Maddox
- Cardiovascular Division, School of Medicine, Washington University in St. Louis, St. Louis, MO
- Center for Health Economics and Policy, Washington University Institute for Public Health, St. Louis, MO
| | - Robert G. Holloway
- Department of Neurology, University of Rochester Medical Center, Rochester, NY
| | - Yue Li
- Department of Public Health Sciences, Division of Health Policy and Outcomes Research, University of Rochester Medical Center, Rochester, NY
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Sharma H, Hefele JG, Xu L, Conkling B, Wang XJ. First Year of Skilled Nursing Facility Value-based Purchasing Program Penalizes Facilities With Poorer Financial Performance. Med Care 2021; 59:1099-1106. [PMID: 34593708 DOI: 10.1097/mlr.0000000000001648] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND The Skilled Nursing Facility Value-based Purchasing Program (SNF-VBP) incentivizes facilities to coordinate care, improve quality, and lower hospital readmissions. However, SNF-VBP may unintentionally punish facilities with lower profit margins struggling to invest resources to lower readmissions. OBJECTIVE The objective of this study was to estimate the SNF-VBP penalty amounts by skilled nursing facility (SNF) profit margin quintiles and examine whether facilities with lower profit margins are more likely to be penalized by SNF-VBP. RESEARCH DESIGN We combined the first round of SNF-VBP performance data with SNF profit margins and characteristics data. Our outcome variables included estimated penalty amount and a binary measure for whether facilities were penalized by the SNF-VBP. We categorized SNFs into 5 profit margin quintiles and examined the relationship between profit margins and SNF-VBP performance using descriptive and regression analysis. RESULTS The average profit margins for SNFs in the lowest profit margin quintile was -14.4% compared with the average profit margin of 11.1% for SNFs in the highest profit margin quintile. In adjusted regressions, SNFs in the lowest profit margin quintile had 17% higher odds of being penalized under SNF-VBP compared with facilities in the highest profit margin quintile. The average penalty for SNFs in the lowest profit margin quintile was $22,312. CONCLUSIONS SNFs in the lowest profit margins are more likely to be penalized by the SNF-VBP, and these losses can exacerbate quality problems in SNFs with lower quality. Alternative approaches to measuring and rewarding SNFs under SNF-VBP or programs to assist struggling SNFs is warranted, particularly considering the coronavirus disease 2019 pandemic, which requires resources for prevention and management.
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Affiliation(s)
- Hari Sharma
- Department of Health Management and Policy, The University of Iowa, Iowa City, IA
| | | | - Lili Xu
- Department of Health Management and Policy, The University of Iowa, Iowa City, IA
| | | | - Xiao Joyce Wang
- McCormack Graduate School of Policy and Global Studies, University of Massachusetts, Boston, MA
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White EM, Saade EA, Yang X, Canaday DH, Blackman C, Santostefano CM, Nanda A, Feifer RA, Mor V, Rudolph JL, Gravenstein S. SARS-CoV-2 antibody detection in skilled nursing facility residents. J Am Geriatr Soc 2021; 69:1722-1728. [PMID: 33544876 PMCID: PMC8013911 DOI: 10.1111/jgs.17061] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 01/15/2021] [Accepted: 01/21/2021] [Indexed: 01/19/2023]
Abstract
OBJECTIVE To describe the frequency and timing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody detection in a convenience sample of skilled nursing facility (SNF) residents with and without confirmed SARS-CoV-2 infection. DESIGN Retrospective analysis of SNF electronic health records. SETTING Qualitative SARS-CoV-2 antibody test results were available from 81 SNFs in 16 states. PARTICIPANTS Six hundred and sixty nine SNF residents who underwent both polymerase chain reaction (PCR) and antibody testing for SARS-CoV-2. MEASUREMENTS Presence of SARS-CoV-2 antibodies following the first positive PCR test for confirmed cases, or first PCR test for non-cases. RESULTS Among 397 residents with PCR-confirmed infection, antibodies were detected in 4 of 7 (57.1%) tested within 7-14 days of their first positive PCR test; in 44 of 47 (93.6%) tested within 15-30 days; in 182 of 219 (83.1%) tested within 31-60 days; and in 110 of 124 (88.7%) tested after 60 days. Among 272 PCR negative residents, antibodies were detected in 2 of 9 (22.2%) tested within 7-14 days of their first PCR test; in 41 of 81 (50.6%) tested within 15-30 days; in 65 of 148 (43.9%) tested within 31-60 days; and in 9 of 34 (26.5%) tested after 60 days. No significant differences in baseline resident characteristics or symptoms were observed between those with versus without antibodies. CONCLUSIONS These findings suggest that vulnerable older adults can mount an antibody response to SARS-CoV-2, and that antibodies are most likely to be detected within 15-30 days of diagnosis. That antibodies were detected in a large proportion of residents with no confirmed SARS-CoV-2 infection highlights the complexity of identifying who is infected in real time. Frequent surveillance and diagnostic testing based on low thresholds of clinical suspicion for symptoms and/or exposure will remain critical to inform strategies designed to mitigate outbreaks in SNFs while community SARS-CoV-2 prevalence remains high.
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Affiliation(s)
- Elizabeth M. White
- Department of Health Services, Policy, and PracticeBrown University School of Public HealthProvidenceRhode IslandUSA
| | - Elie A. Saade
- Case Western Reserve University School of MedicineDivision of Infectious Diseases and HIV MedicineClevelandOhioUSA
- Louis Stokes Veterans Administration Medical CenterClevelandOhioUSA
| | - Xiaofei Yang
- Department of Health Services, Policy, and PracticeBrown University School of Public HealthProvidenceRhode IslandUSA
| | - David H. Canaday
- Case Western Reserve University School of MedicineDivision of Infectious Diseases and HIV MedicineClevelandOhioUSA
- Louis Stokes Veterans Administration Medical CenterClevelandOhioUSA
| | | | - Christopher M. Santostefano
- Department of Health Services, Policy, and PracticeBrown University School of Public HealthProvidenceRhode IslandUSA
| | - Aman Nanda
- Division of Geriatrics and Palliative MedicineBrown University Alpert Medical SchoolProvidenceRhode IslandUSA
| | | | - Vincent Mor
- Department of Health Services, Policy, and PracticeBrown University School of Public HealthProvidenceRhode IslandUSA
- Providence Veterans Administration Medical Center Research ServiceProvidenceRhode IslandUSA
| | - James L. Rudolph
- Department of Health Services, Policy, and PracticeBrown University School of Public HealthProvidenceRhode IslandUSA
- Providence Veterans Administration Medical Center Research ServiceProvidenceRhode IslandUSA
| | - Stefan Gravenstein
- Department of Health Services, Policy, and PracticeBrown University School of Public HealthProvidenceRhode IslandUSA
- Division of Geriatrics and Palliative MedicineBrown University Alpert Medical SchoolProvidenceRhode IslandUSA
- Providence Veterans Administration Medical Center Research ServiceProvidenceRhode IslandUSA
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Ifejika NL, Vahidy F, Reeves M, Xian Y, Liang L, Matsouaka R, Fonarow GC, Savitz SI. Association Between 2010 Medicare Reforms and Utilization of Postacute Inpatient Rehabilitation in Ischemic Stroke. Am J Phys Med Rehabil 2021; 100:675-682. [PMID: 33002913 PMCID: PMC8004542 DOI: 10.1097/phm.0000000000001605] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The aim of the study was to investigate whether the elimination of trial admissions and the initiation of documentation requirements, via the 2010 Centers for Medicare and Medicaid Services Inpatient Rehabilitation Facility Prospective Payment System Rule, limited inpatient rehabilitation facility access while increasing skilled nursing facility utilization compared with home discharge in ischemic stroke patients. DESIGN This is a retrospective observational study using Get with the Guidelines - Stroke hospital data between January 1, 2008 and December 31, 2015 (N = 1,643,553). RESULTS Between January 1, 2008 and December 31, 2009, 54.1% of patients went home, 25.4% to inpatient rehabilitation facility and 20.5% to skilled nursing facility. Between January 1, 2010 and December 31, 2015, there was a 1.4% absolute increase in home discharge, a 1.1% inpatient rehabilitation facility decline and a 0.3% skilled nursing facility decline.Within the 1.1% absolute decline in inpatient rehabilitation facility discharge, the adjusted odds of inpatient rehabilitation facility versus home discharge decreased 12% after 2010 Rule (adjusted odds ratio = 0.88, 95% confidence interval = 0.87-0.89, P < 0.0001). There was no statistically significant change in skilled nursing facility versus home discharge.Lower adjusted odds of inpatient rehabilitation facility discharge versus home discharge were identical across age groups and were present in all geographic regions. CONCLUSIONS In populations with ischemic stroke, the Centers for Medicare and Medicaid Services 2010 Inpatient Rehabilitation Facility Prospective Payment System Rule was associated with a 1.1% absolute decrease in inpatient rehabilitation facility discharge, with a concomitant increase in home discharge rather than to skilled nursing facility.
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Affiliation(s)
- Nneka L Ifejika
- From the Department of Physical Medicine and Rehabilitation, UT Southwestern Medical Center, Dallas, Texas (NLI); Department of Neurology and Neurotherapeutics, UT Southwestern Medical Center, Dallas, Texas (NLI); Department of Population and Data Sciences, UT Southwestern Medical Center, Dallas, Texas (NLI); Centers for Outcomes Research, Houston Methodist Research Institute, Houston, Texas (FV); Department of Epidemiology and Biostatistics, College of Human Medicine, Michigan State University, Lansing, Michigan (MR); Department of Neurology, Duke University Hospital, Durham, North Carolina (YX); Duke Clinical Research Institute, Durham, North Carolina (YX, LL, RM); Division of Cardiology, Ahmanson - UCLA Cardiomyopathy Center, University of California, Los Angeles Medical Center, Los Angeles, California (GCF); Institute for Stroke and Cerebrovascular Disease, UTHealth, Houston, Texas (SIS); and Department of Neurology, McGovern Medical School at UTHealth, Houston, Texas (SIS)
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Anderson MC, Evans E, Zonfrillo MR, Thomas KS. Rural/urban differences in discharge from rehabilitation in older adults with traumatic brain injury. J Am Geriatr Soc 2021; 69:1601-1608. [PMID: 33675540 PMCID: PMC8192484 DOI: 10.1111/jgs.17065] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Revised: 01/13/2021] [Accepted: 01/26/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND/OBJECTIVES Rates of traumatic brain injury (TBI) among older adults and treatment of this population in nursing homes are increasing. The objective of this study is to examine differences in the quality of care and outcomes of older adults with TBI in rural and urban settings by (1) comparing the rates of successful community discharge; and (2) reasons for not achieving successful discharge among patients in rural and urban environments. DESIGN Retrospective national cohort study of skilled nursing facility (SNF) patients using Medicare inpatient claims linked with Minimum Data Set assessments. Demographic, health, and facility characteristics were compared between rural and urban settings using descriptive statistics. Logistic regression with state random effects was used to identify characteristics that predicted successful discharge. SETTING U.S. skilled nursing facilities (n = 11,771). PARTICIPANTS Medicare beneficiaries aged 66 and older discharged to a SNF following hospitalization for TBI between 2011 and 2015 (n = 61,021). MEASUREMENTS Successful community discharge defined as discharge from SNF within 100 days of admission and remaining in the community for ≥30 days without dying or admission to an inpatient healthcare facility. RESULTS Unadjusted rates of successful discharge were significantly lower for patients in rural settings compared with patients in urban settings (52.1% vs 58.5%, p < 0.01). Patients in rural settings had lower adjusted odds (odds ratio 0.84, 95% confidence interval = 0.80-0.89) of successful discharge. Reasons for not discharging successfully differed between rural and urban settings with rural patients less likely to discharge from SNF within 100 days though also less likely to be rehospitalized within 30 days of SNF discharge. CONCLUSION Given the low overall rate of successful community discharge and worse outcomes among rural patients, further research to explore interventions to improve SNF care and discharge planning in this population is warranted.
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Affiliation(s)
| | - Emily Evans
- Brown University School of Public Health, Department of Health Services, Policy and Practice
| | - Mark R. Zonfrillo
- Warren Alpert Medical School of Brown University, Departments of Emergency Medicine and Pediatrics
| | - Kali S. Thomas
- Brown University School of Public Health, Department of Health Services, Policy and Practice
- Providence VA Medical Center
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Reistetter TA, Eschbach K, Prochaska J, Jupiter DC, Hong I, Haas AM, Ottenbacher KJ. Understanding Variation in Postacute Care: Developing Rehabilitation Service Areas Through Geographic Mapping. Am J Phys Med Rehabil 2021; 100:465-472. [PMID: 32858537 PMCID: PMC8262929 DOI: 10.1097/phm.0000000000001577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The aims of the study were to demonstrate a method for developing rehabilitation service areas and to compare service areas based on postacute care rehabilitation admissions to service areas based on acute care hospital admissions. DESIGN We conducted a secondary analysis of 2013-2014 Medicare records for older patients in Texas (N = 469,172). Our analysis included admission records for inpatient rehabilitation facilities, skilled nursing facilities, long-term care hospitals, and home health agencies. We used Ward's algorithm to cluster patient ZIP Code Tabulation Areas based on which facilities patients were admitted to for rehabilitation. For comparison, we set the number of rehabilitation clusters to 22 to allow for comparison to the 22 hospital referral regions in Texas. Two methods were used to evaluate rehabilitation service areas: intraclass correlation coefficient and variance in the number of rehabilitation beds across areas. RESULTS Rehabilitation service areas had a higher intraclass correlation coefficient (0.081 vs. 0.076) and variance in beds (27.8 vs. 21.4). Our findings suggest that service areas based on rehabilitation admissions capture has more variation than those based on acute hospital admissions. CONCLUSIONS This study suggests that the use of rehabilitation service areas would lead to more accurate assessments of rehabilitation geographic variations and their use in understanding rehabilitation outcomes.
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Affiliation(s)
- Timothy A Reistetter
- From the Department of Occupational Therapy, University of Texas Health Science Center at San Antonio, School of Health Professions, San Antonio, Texas (TAR); Department of Preventive Medicine and Population Health, University of Texas Medical Branch, School of Medicine, Galveston, Texas (KE, JP, DCJ, AMH); Department of Occupational Therapy, Yonsei University, College of Health Sciences, Gangwon-do, Republic of Korea (IH); and Division of Rehabilitation Sciences, University of Texas Medical Branch, School of Health Professions, Galveston, Texas (KJO)
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14
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Affiliation(s)
- Radhika Gharpure
- COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Anita Patel
- COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Ruth Link-Gelles
- COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia
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15
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Downer B, Pritchard K, Thomas KS, Ottenbacher K. Improvement in Activities of Daily Living during a Nursing Home Stay and One-Year Mortality among Older Adults with Sepsis. J Am Geriatr Soc 2021; 69:938-945. [PMID: 33155268 PMCID: PMC8049879 DOI: 10.1111/jgs.16915] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 10/09/2020] [Accepted: 10/09/2020] [Indexed: 11/30/2022]
Abstract
BACKGROUND/OBJECTIVE To describe the recovery of activities of daily living (ADLs) during a skilled nursing facility (SNF) stay and the association with 1-year mortality after SNF discharge among Medicare beneficiaries treated in intensive care for sepsis. DESIGN Retrospective cohort study. SETTING Skilled nursing facilities in the United States. PARTICIPANTS Medicare fee-for-service beneficiaries admitted to an SNF within 3 days of discharge from a hospitalization that included an intensive care unit (ICU) stay for sepsis between January 1, 2013, and September 30, 2015 (N = 59,383). MEASUREMENTS Data from the Minimum Data Set (MDS) were used to calculate a total score for seven ADLs. Improvement was determined by comparing the total ADL scores from the first and last MDS assessments of the SNF stay. Proportional hazard models were used to estimate the association between improvement in ADL function and 1-year mortality after SNF discharge. RESULTS Approximately 58% of SNF residents had any improvement in ADL function. Residents who had improvement in ADL function had 0.72 (95% confidence interval (CI) = 0.69-0.74) lower risk for mortality following SNF discharge than residents who did not improve. Residents who improved 1-3 points (hazard ratio (HR) = 0.82, 95% CI = 0.79-0.84) and four or more points (HR = 0.57, 95% CI = 0.55-0.60) in ADL function had significantly lower mortality risk than residents who did not improve. CONCLUSION Older adults treated in an ICU with sepsis can improve in ADL function during an SNF stay. This improvement is associated with lower 1-year mortality risk after SNF discharge. These findings provide evidence that ADL recovery during an SNF stay is associated with better health outcomes for older adults who have survived an ICU stay for sepsis.
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Affiliation(s)
- Brian Downer
- University of Texas Medical Branch, Division of Rehabilitation Sciences, Galveston, TX, US
- University of Texas Medical Branch, Sealy Center on Aging, Galveston, TX, US
| | - Kevin Pritchard
- University of Texas Medical Branch, Division of Rehabilitation Sciences, Galveston, TX, US
| | - Kali S. Thomas
- Brown University, School of Public Health, Providence, RI, US
- United States Department of Veterans Affairs Medical Center, Providence, RI, US
| | - Kenneth Ottenbacher
- University of Texas Medical Branch, Division of Rehabilitation Sciences, Galveston, TX, US
- University of Texas Medical Branch, Sealy Center on Aging, Galveston, TX, US
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Gu J, Huckfeldt P, Sood N. The Effects of Accountable Care Organizations Forming Preferred Skilled Nursing Facility Networks on Market Share, Patient Composition, and Outcomes. Med Care 2021; 59:354-361. [PMID: 33704104 PMCID: PMC7959004 DOI: 10.1097/mlr.0000000000001493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Through participation in payment reforms such as bundled payment and accountable care organizations (ACOs), hospitals are increasingly financially responsible for health care use and adverse health events occurring after hospital discharge. To improve management and coordination of postdischarge care, ACO hospitals are establishing a closer relationship with skilled nursing facilities (SNFs) through the formation of preferred SNF networks. RESEARCH DESIGN We evaluated the effects of preferred SNF network formation on care patterns and outcomes. We included 10 ACOs that established preferred SNF networks between 2014 and 2015 in the sample. We first investigated whether hospitals "steer" patients to preferred SNFs by examining the percentage of patients sent to preferred SNFs within each hospital before and after network formation. We then used a difference-in-difference model with SNF fixed effects to evaluate the changes in patient composition and outcomes of preferred SNF patients from ACO hospitals after network formation relative to patients from other hospitals. RESULTS We found that preferred network formation was not associated with higher market share or better outcomes for preferred SNF patients from ACO hospitals. However, we found a small increase in the average number of Elixhauser comorbidities for patients from ACO hospitals after network formation, relative to patients from non-ACO hospitals. CONCLUSIONS After preferred SNF network formation, there is some evidence that ACO hospitals sent more complex patients to preferred SNFs, but there was no change in the volume of patients received by these SNFs. Furthermore, preferred network formation was not associated with improvement in patient outcomes.
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Affiliation(s)
- Jing Gu
- School of Pharmacy, University of Southern California, Los Angeles, CA
| | - Peter Huckfeldt
- Sol Price School of Public Policy, University of Southern California, Los Angeles, CA
| | - Neeraj Sood
- School of Public Health, University of Minnesota, Minneapolis, MN
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Abdelfattah OM, Saad AM, Abushouk A, Hassanein M, Isogai T, Gad MM, Ahuja KR, Yun J, Krishnaswamy A, Kapadia S. Short-Term Outcomes of Transcatheter Aortic Valve Implantation Versus Surgical Aortic Valve Replacement in Kidney Transplant Recipients (from the US Nationwide Representative Study). Am J Cardiol 2021; 144:83-90. [PMID: 33383014 DOI: 10.1016/j.amjcard.2020.12.048] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 12/14/2020] [Accepted: 12/15/2020] [Indexed: 11/28/2022]
Abstract
Kidney transplant recipients (KTRs) are considered high-risk patients for surgical interventions. Transcatheter aortic valve implantation (TAVI) has been introduced as an alternative to surgical aortic valve replacement (SAVR) in patients with aortic stenosis (AS) at high operative risk. However, the outcomes of TAVI compared with SAVR KTRs have not been well-studied in nationally representative data. Patients with prior history of functioning kidney transplant who were hospitalized for TAVI and SAVR between January 2012 and December 2017 were identified retrospectively in the Nationwide Readmissions Database. Our study included 762 TAVI and 1,278 SAVR KTRs. Compared with SAVR, TAVI patients generally had higher rates of co-morbidities with lower risk of in-hospital mortality (3.1% vs 6.3, p = 0.002), blood transfusion (11.5% vs 38.6%, p <0.001), acute myocardial infarction (3.9% vs 6.5%, p = 0.16), acute kidney injury (24.5% vs 42.1%, p <0.001), sepsis (3.9% vs 9.5%, p <0.001) and discharge with disability (42.6% vs 68.4%, p <0.001). However, the rate of permanent pacemaker implantation was significantly higher in TAVI group (11.4% vs 3.9%, p <0.001). Of note, in-hospital stroke and 30-day readmission were comparable between both groups. These findings were confirmed after adjusting for other co-morbidities. TAVI is growing as a valid and safe alternative for KTRs with severe AS.
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Affiliation(s)
- Omar M Abdelfattah
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio; Internal Medicine Department, Morristown Medical Center, Atlantic Health System, Morristown, New Jersey
| | - Anas M Saad
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio
| | - Abdelrahman Abushouk
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio
| | - Mohamed Hassanein
- Glickman Urological Institute, Department of Nephrology and Hypertension, Cleveland Clinic, Cleveland, Ohio
| | - Toshiaki Isogai
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio
| | - Mohamed M Gad
- Internal Medicine Department, Cleveland Clinic, Cleveland, Ohio
| | | | - James Yun
- Department of Cardiovascular & Thoracic Surgery, Heart and Vascular Institute, Cleveland Clinic, Ohio
| | - Amar Krishnaswamy
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio
| | - Samir Kapadia
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, Ohio.
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Bardenheier BH, Rahman M, Kosar C, Werner RM, Mor V. Successful Discharge to Community Gap of FFS Medicare Beneficiaries With and Without ADRD Narrowed. J Am Geriatr Soc 2021; 69:972-978. [PMID: 33300605 PMCID: PMC8049962 DOI: 10.1111/jgs.16965] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 11/09/2020] [Accepted: 11/12/2020] [Indexed: 11/30/2022]
Abstract
BACKGROUND/OBJECTIVES We sought to compare the post-acute and long-term care experience of Medicare beneficiaries with and without Alzheimer Disease and Related Dementias (ADRD), and whether differences changed from January 1, 2007 to September 30, 2015. DESIGN Retrospective cross-sectional trend study using Medicare claims linked to the Centers for Medicare & Medicaid Services' (CMS) Minimum Data Set. SETTING CMS-certified skilled nursing facilities (skilled nursing facility (SNF), n = 17,043). PARTICIPANTS Fee-for-service Medicare beneficiaries aged ≥66 years (n = 6,614,939) discharged from a hospital to a SNF who had not lived in a nursing home during the year before hospitalization. MEASUREMENTS ADRD was defined by the Chronic Condition Data Warehouse. Outcome measures included: (1) successful discharge defined as being in SNF less than 90 days, then discharged back to the community, alive without subsequent inpatient health care for 30 continuous days; (2) became long-stay resident in SNF; (3) death in SNF within 90 days; (4) hospital readmission within 30 days of entering SNF; and (5) transferred to another nursing home within 30 days of entering SNF. RESULTS Successful discharge of beneficiaries with ADRD increased from 43.4% in 2007 to 53.9% in 2015 (average annual percent change (AAPC) = 2.1 (95% CI = 2.0-2.2)); those without ADRD also increased (from 59.1% to 63.6%, AAPC = 0.9 (95% CI = 0.7-1.1)) but not as fast as those with ADRD (P < .01). The proportion of all beneficiaries who became long-stay or were readmitted to the hospital decreased (P < .05). The proportion with ADRD who became long-stay was nearly three times higher than those without throughout the study (15.0% vs 5.5% in 2007; 11.3% vs 4.3% in 2015). CONCLUSION Though disparity in ADRD in becoming long-stay residents remains, the increase in successful discharges among those with ADRD also stresses the increasing importance of community as a care setting for adults with ADRD.
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Affiliation(s)
- Barbara H. Bardenheier
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
| | - Momotazur Rahman
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
| | - Cyrus Kosar
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
| | - Rachel M. Werner
- Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Vincent Mor
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
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Commodore-Mensah Y, DePriest K, Samuel LJ, Hanson G, D’Aoust R, Slade EP. Prevalence and Characteristics of Non-US-Born and US-Born Health Care Professionals, 2010-2018. JAMA Netw Open 2021; 4:e218396. [PMID: 33914048 PMCID: PMC8085726 DOI: 10.1001/jamanetworkopen.2021.8396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Accepted: 03/11/2021] [Indexed: 11/14/2022] Open
Abstract
Importance Immigration to the US results in greater racial/ethnic diversity. However, the contribution of immigration to the diversity of the US health care professional (HCP) work force and its contribution to health care are poorly documented. Objective To examine the sociodemographic characteristics and workforce outcomes of non-US-born and US-born HCPs. Design, Setting, and Participants This cross-sectional study used national US Census Bureau data on US-born and non-US-born HCPs from the American Community Survey between 2010 and 2018. Demographic characteristics and occupational data for physicians, advanced practice registered nurses, physician assistants, registered nurses, licensed practical nurses or licensed vocational nurses, and other HCPs were included for analysis. Data were analyzed between December 2020 and February 2021. Exposures Nativity status, defined as US-born HCP vs non-US-born HCP (further stratified by <10 years or ≥10 years of stay in the US). Main Outcomes and Measures Annual hours worked, proportion of work done at night, residence in medically underserved areas and populations, and work in skilled nursing/home health settings. Inverse probability weighting of 3 nativity status groups was carried out using logistic regression. F test statistics were used to test across-group differences. Data were weighted using American Community Survey sampling weights. Results Of a total of 657 455 HCPs analyzed (497 180 [75.5%] women; mean [SD] age, 43.7 [13.0] years; 518 317 [75.6%] White, 54 233 [10.8%] Black, and 60 680 [9.6%] Asian), non-US-born HCPs (105 331 in total) represented 17.3% (95% CI, 17.2%-17.4%) of HCPs between 2010 and 2018. They were older (mean [SD] age, 44.7 [11.6] years) and had more education (75 227 [70.1%] HCPs completed college) compared with US-born HCPs (mean [SD] age, 43.4 [13.3] years; 304 601 [55.2%] completed college). Nearly half of non-US-born HCPs (47 735 [43.0%]) were Asian. In major metropolitan areas, non-US-born HCPs represented 40% or more of all HCPs. Compared with US-born HCPs, non-US-born HCPs with less than 10 years and 10 or more years of stay worked 32.3 hours (95% CI, 19.2 to 45.4 hours) and 71.6 hours (95% CI, 65.1 to 78.2 hours) more per year, respectively. Compared with US-born HCPs, non-US-born HCPs were more likely to reside in areas with shortages of health care professionals (estimated percentage: <10 years, 75.3%; ≥10 years, 62.8% vs US-born, 8.3%) and work in home health settings (estimated percentage: <10 years, 17.5%; ≥10 years, 13.1% vs US-born, 12.8%). Conclusions and Relevance The contributions of non-US-born HCPs to US health care are substantial and vary by profession. Greater efforts should be made to streamline their immigration process and to harmonize training and licensure requirements.
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Affiliation(s)
- Yvonne Commodore-Mensah
- Johns Hopkins School of Nursing, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | | | - Ginger Hanson
- Johns Hopkins School of Nursing, Baltimore, Maryland
| | - Rita D’Aoust
- Johns Hopkins School of Nursing, Baltimore, Maryland
| | - Eric P. Slade
- Johns Hopkins School of Nursing, Baltimore, Maryland
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Hathaway EE, Carnahan JL, Unroe KT, Stump TE, Phillips EO, Hickman SE, Fowler NR, Sachs GA, Bateman DR. Nursing Home Transfers for Behavioral Concerns: Findings from the OPTIMISTIC Demonstration Project. J Am Geriatr Soc 2021; 69:415-423. [PMID: 33216954 PMCID: PMC10602584 DOI: 10.1111/jgs.16920] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 09/19/2020] [Accepted: 09/26/2020] [Indexed: 12/13/2022]
Abstract
OBJECTIVES To characterize pretransfer on-site nursing home (NH) management, transfer disposition, and hospital discharge diagnoses of long-stay residents transferred for behavioral concerns. DESIGN This was a secondary data analysis of the Optimizing Patient Transfers, Impacting Medical Quality, Improving Symptoms: Transforming Institutional Care project, in which clinical staff employed in the NH setting conducted medical, transitional, and palliative care quality improvement initiatives and gathered data related to resident transfers to the emergency department/hospital setting. R software and Microsoft Excel were used to characterize a subset of transfers prompted by behavioral concerns. SETTING NHs in central Indiana were utilized (N = 19). PARTICIPANTS This study included long-stay NH residents with behavioral concerns prompting transfer for acute emergency department/hospital evaluation (N = 355 transfers). MEASUREMENTS The measures used in this study were symptoms prompting transfer, resident demographics and baseline characteristics (Minimum Data Set 3.0 variables including scores for the Cognitive Function Scale, ADL Functional Status, behavioral symptoms directed toward others, and preexisting psychiatric diagnoses), on-site management (e.g., medical evaluation in person or by phone, testing, and interventions), avoidability rating, transfer disposition (inpatient vs emergency department only), and hospital discharge diagnoses. RESULTS Over half of the transfers, 56%, had a medical evaluation before transfer, and diagnostic testing was conducted before 31% of transfers. After transfer, 80% were admitted. The most common hospital discharge diagnoses were dementia-related behaviors (27%) and altered mental status (27%), followed by a number of medical diagnoses. CONCLUSION Most transfers for behavioral concerns merited hospital admission, and medical discharge diagnoses were common. There remain significant opportunities to improve pretransfer management of NH transfers for behavioral concerns.
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Affiliation(s)
- Elizabeth E. Hathaway
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jennifer L. Carnahan
- Regenstrief Institute, Inc., Indiana University Center for Aging Research, Indianapolis, IN, USA
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kathleen T. Unroe
- Regenstrief Institute, Inc., Indiana University Center for Aging Research, Indianapolis, IN, USA
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Timothy E. Stump
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Erin O’Kelly Phillips
- Regenstrief Institute, Inc., Indiana University Center for Aging Research, Indianapolis, IN, USA
| | - Susan E. Hickman
- Regenstrief Institute, Inc., Indiana University Center for Aging Research, Indianapolis, IN, USA
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University School of Nursing, Indianapolis, IN, USA
| | - Nicole R. Fowler
- Regenstrief Institute, Inc., Indiana University Center for Aging Research, Indianapolis, IN, USA
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Greg A. Sachs
- Regenstrief Institute, Inc., Indiana University Center for Aging Research, Indianapolis, IN, USA
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Daniel R. Bateman
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
- Regenstrief Institute, Inc., Indiana University Center for Aging Research, Indianapolis, IN, USA
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Sheehy AM, Powell WR, Kaiksow FA, Buckingham WR, Bartels CM, Birstler J, Yu M, Bykovskyi AG, Shi F, Kind AJH. Thirty-Day Re-observation, Chronic Re-observation, and Neighborhood Disadvantage. Mayo Clin Proc 2020; 95:2644-2654. [PMID: 33276837 PMCID: PMC7720926 DOI: 10.1016/j.mayocp.2020.06.059] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 05/28/2020] [Accepted: 06/25/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To determine whether neighborhood socioeconomic disadvantage, as determined by the Area Deprivation Index, increases 30-day hospital re-observation risk. PARTICIPANTS AND METHODS This retrospective study of 20% Medicare fee-for-service beneficiary observation stays from January 1, 2014, to November 30, 2014, included 319,980 stays among 273,308 beneficiaries. We evaluated risk for a 30-day re-observation following an index observation stay for those living in the 15% most disadvantaged compared with the 85% least disadvantaged neighborhoods. RESULTS Overall, 4.5% (270,600 of 6,080,664) of beneficiaries had index observation stays, which varied by disadvantage (4.3% [232,568 of 5,398,311] in the least disadvantaged 85% compared with 5.6% [38,032 of 682,353] in the most disadvantaged 15%). Patients in the most disadvantaged neighborhoods had a higher 30-day re-observation rate (2857 of 41,975; 6.8%) compared with least disadvantaged neighborhoods (13,543 of 278,005; 4.9%); a 43% increased risk (unadjusted odds ratio [OR], 1.43; 95% CI, 1.31 to 1.55). After adjustment, this risk remained (adjusted OR, 1.13; 95% CI, 1.04 to 1.22). Discharge to a skilled nursing facility reduced 30-day re-observation risk (OR, 0.63; 95% CI, 0.57 to 0.69), whereas index observation length of stay of 4 or more days (3 midnights) conferred increased risk (OR, 1.29; 95% CI, 1.09 to 1.52); those living in disadvantaged neighborhoods were less likely to discharge to skilled nursing facilities and more likely to have long index stays. Beneficiaries with more than one 30-day re-observation (chronic re-observation) had progressively greater disadvantage by number of stays (adjusted incident rate ratio, 1.08; 95% CI, 1.02 to 1.14). Observation prevalence varied nationally. CONCLUSION Thirty-day re-observation, especially chronic re-observation, is highly associated with socioeconomic neighborhood disadvantage, even after accounting for factors such as race, disability, and Medicaid eligibility. Beneficiaries least able to pay are potentially most vulnerable to costs from serial re-observations and challenges of Medicare observation policy, which may discourage patients from seeking necessary care.
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Affiliation(s)
- Ann M Sheehy
- Health Services and Care Research Program, Department of Medicine, University of Wisconsin, Madison, WI.
| | - W Ryan Powell
- Health Services and Care Research Program, Department of Medicine, University of Wisconsin, Madison, WI; Divisions of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Farah A Kaiksow
- Health Services and Care Research Program, Department of Medicine, University of Wisconsin, Madison, WI; Hospital Medicine, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - William R Buckingham
- Health Services and Care Research Program, Department of Medicine, University of Wisconsin, Madison, WI; Applied Population Laboratory, University of Wisconsin, Madison, WI
| | - Christie M Bartels
- Health Services and Care Research Program, Department of Medicine, University of Wisconsin, Madison, WI; Division of Rheumatology, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Jen Birstler
- Department of Biostatistics & Medical Informatics, University of Wisconsin, Madison, WI
| | - Menggang Yu
- Department of Biostatistics & Medical Informatics, University of Wisconsin, Madison, WI
| | - Andrea Gilmore Bykovskyi
- Health Services and Care Research Program, Department of Medicine, University of Wisconsin, Madison, WI; School of Nursing, University of Wisconsin, Madison, WI
| | - Fangfang Shi
- Health Services and Care Research Program, Department of Medicine, University of Wisconsin, Madison, WI; Divisions of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Amy J H Kind
- Health Services and Care Research Program, Department of Medicine, University of Wisconsin, Madison, WI; Divisions of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI; Department of Veterans Affairs Geriatrics Research Education and Clinical Center, Madison, WI
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Briesacher BA, Koethe B, Olivieri-Mui B, Saczynski JS, Fick DM, Devlin JW, Marcantonio ER. Association of Positive Delirium Screening with Incident Dementia in Skilled Nursing Facilities. J Am Geriatr Soc 2020; 68:2931-2936. [PMID: 32965034 PMCID: PMC8114416 DOI: 10.1111/jgs.16830] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 07/27/2020] [Accepted: 08/11/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND AND OBJECTIVE Early detection of delirium in skilled nursing facilities (SNFs) is a priority. The extent to which delirium screening leads to a potentially inappropriate diagnosis of Alzheimer's disease and related dementia (ADRD) is unknown. DESIGN Nationwide retrospective cohort study from 2011 to 2013. SETTING An SNF. PARTICIPANTS A total of 1,175,550 Medicare enrollees who entered the SNF from a hospital and had no prior diagnosis of dementia. EXPOSURE A positive screen for delirium using the validated Confusion Assessment Method (CAM), performed as part of the federally mandated Minimum Data Set (MDS) assessment. MEASUREMENTS Incident all-cause dementia, ascertained through International Classification of Diseases, Ninth Revision (ICD-9), diagnosis in Medicare claims or active diagnoses in MDS. RESULTS Positive screening for delirium was identified in 7.7% of cases (n = 90,449), and most occurred within the first 7 days of SNF admission (62.5%). The overall incidence of ADRD was 6.3% (n = 73,542). Nearly all new diagnoses of ADRD (93.5%) occurred within the first 30 days of SNF admission. Patients who screened CAM positive for delirium had a nearly threefold increased risk of receiving an incident ADRD diagnosis on the same day (hazard ratio (HR) = 2.63; 95% confidence interval (CI) = 1.50-4.63). Among patients who screened CAM positive for delirium, those who were cognitively intact or had mild cognitive impairments were, on average, six times more likely to receive an incident ADRD diagnosis (HR = 6.64; 95% CI = 1.76-25.0) relative to those testing CAM negative. CONCLUSION AND RELEVANCE Among older adults not previously diagnosed with dementia, a positive screen for delirium was significantly associated with higher risk of ADRD diagnosis after admission to a SNF. This risk was highest for patients in the first days of their stay and with the least cognitive impairment, suggesting that the ADRD diagnosis was potentially inappropriate.
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Affiliation(s)
- Becky A. Briesacher
- Bouvé College of Health Sciences, School of Pharmacy, Northeastern University, Boston, Massachusetts
| | - Benjamin Koethe
- Bouvé College of Health Sciences, School of Pharmacy, Northeastern University, Boston, Massachusetts
| | - Brianne Olivieri-Mui
- Hebrew SeniorLife, The Marcus Institute for Aging Research, Harvard Medical School, Boston, Massachusetts
| | - Jane S. Saczynski
- Bouvé College of Health Sciences, School of Pharmacy, Northeastern University, Boston, Massachusetts
| | - Donna Marie Fick
- Penn State College of Nursing, Center of Geriatric Nursing Excellence, University Park, Pennsylvania
| | - John W. Devlin
- Bouvé College of Health Sciences, School of Pharmacy, Northeastern University, Boston, Massachusetts
| | - Edward R. Marcantonio
- Divisions of General Medicine and Gerontology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
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23
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Affiliation(s)
- Mandy Waldon
- Advanced Nurse Practitioner, Rapid Response and Treatment (RRaT) Service-Clinical Lead, Berkshire Healthcare NHS Foundation Trust
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24
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Carey N, Alkhamees N, Cox A, Sund-Levander M, Tingström P, Mold F. Exploring views and experiences of how infections are detected and managed in practice by nurses, care workers and manager's in nursing homes in England and Sweden: a survey protocol. BMJ Open 2020; 10:e038390. [PMID: 33004397 PMCID: PMC7534694 DOI: 10.1136/bmjopen-2020-038390] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
INTRODUCTION In order to avoid unnecessary hospital admission and associated complications, there is an urgent need to improve the early detection of infection in nursing home residents. Monitoring signs and symptoms with checklists or aids called decision support tools may help nursing home staff to detect infection in residents, particularly during the current COVID-19 pandemic.We plan to conduct a survey exploring views and experiences of how infections are detected and managed in practice by nurses, care workers and managers in nursing homes in England and Sweden. METHODS AND ANALYSIS An international cross-sectional descriptive survey, using a pretested questionnaire, will be used to explore nurses, care workers and managers views and experiences of how infections are detected and managed in practice in nursing homes. Data will be analysed descriptively and univariate associations between personal and organisational factors explored. This will help identify important factors related to awareness, knowledge, attitudes, belief and skills likely to affect future implementation of a decision support tool for the early detection of infection in nursing home residents. ETHICS AND DISSEMINATION This study was approved using the self-certification process at the University of Surrey and Linköping University ethics committee (Approval 2018/514-32) in 2018. Study findings will be disseminated through community/stakeholder/service user engagement events in each country, publication in academic peer-reviewed journals and conference presentations. A LAY summary will be provided to participants who indicate they would like to receive this information.This is the first stage of a plan of work to revise and evaluate the Early Detection of Infection Scale (EDIS) tool and its effect on managing infections and reducing unplanned hospital admissions in nursing home residents. Implementation of the EDIS tool may have important implications for the healthcare economy; this will be explored in cost-benefit analyses as the work progresses.
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Affiliation(s)
- N Carey
- School of Health Sciences, University of Surrey, Guildford, Surrey, UK
| | - Nouf Alkhamees
- College of Health and Rehabilitation Sciences, Princess Noura Bint Abdul Rahman University, Riyadh, Saudi Arabia
| | - Anna Cox
- School of Health Sciences, University of Surrey, Guildford, Surrey, UK
| | - Marta Sund-Levander
- Division of Nursing, Department of Medical and Health Sciences, Linkoping University, Linkoping, Sweden
| | - Pia Tingström
- Division of Nursing, Department of Medical and Health Sciences, Linkoping University, Linkoping, Sweden
| | - Freda Mold
- School of Health Sciences, University of Surrey, Guildford, Surrey, UK
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25
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Schuman AD, Syrjamaki JD, Norton EC, Hallstrom BR, Regenbogen SE. Effect of statewide reduction in extended care facility use after joint replacement on hospital readmission. Surgery 2020; 169:341-346. [PMID: 32900495 DOI: 10.1016/j.surg.2020.07.043] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 07/21/2020] [Accepted: 07/23/2020] [Indexed: 11/18/2022]
Abstract
BACKGROUND Extended care facility use is a primary driver of variation in hospitalization-associated health care payments and is increasingly a focus for savings under episode-based payment. However, concerns remain that extended care facility limits could incur rising readmissions, emergency department use, or other costs. We analyzed the effects of a statewide value improvement initiative to decrease extended care facility use after lower extremity arthroplasty on extended care facility use, readmission, emergency department use, and payments. METHODS We performed a retrospective cohort study using complete claims from the Michigan Value Collaborative for patients undergoing lower extremity joint replacement. We compared the change in extended care facility use before (2012-2013) and after (2016-2017) the aforementioned statewide initiative with 90-day postacute care, readmission, and emergency department rates and payments using t tests. RESULTS Of the patients included, 68,537 underwent total knee arthroplasty; 27,131 underwent total hip arthroplasty. Statewide, extended care facility use and postacute care payments decreased (extended care facility: 27.5% before vs 18.1% after, payments: $4,999 vs $3,832, P < .0001) without increased readmission rates (8.0% vs 7.6%, P = .10) or payments ($1,087 vs $1,026, P = .14). Emergency department use increased (7.8% vs 8.9%, P < .0001). Per hospital, there was no association between extended care facility use change and readmission rate change (r = 0.05). Hospital change in extended care facility use ranged from +2.3% (no extended care facility decrease group) to -16.6% (large extended care facility decrease group) and was associated with lower total episode payments without differences in change in readmission rate/payments or emergency department use. CONCLUSION Despite decreased use of extended care facilities, there was no compensatory increase in readmission rate or payments. Reducing excess use of extended care facilities after joint replacement may be an important opportunity for savings in episode-based reimbursement.
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Affiliation(s)
- Ari D Schuman
- Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor, MI; Department of Otolaryngology-Head and Neck Surgery, Baylor College of Medicine, Houston, TX
| | - John D Syrjamaki
- Michigan Value Collaborative, Ann Arbor, MI; Department of Surgery, University of Michigan Medical School, Ann Arbor, MI
| | - Edward C Norton
- Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor, MI; Michigan Value Collaborative, Ann Arbor, MI
| | - Brian R Hallstrom
- Department of Orthopedic Surgery, University of Michigan Medical School, Ann Arbor, MI
| | - Scott E Regenbogen
- Center for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor, MI; Michigan Value Collaborative, Ann Arbor, MI; Department of Surgery, University of Michigan Medical School, Ann Arbor, MI.
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Abstract
This study uses Medicare’s Nursing Home Compare and a university long-term care database to compare census, admissions, discharges, and mortality at skilled nursing facilities (SNFs) in 3 metropolitan areas during March-May 2020 vs March-May 2019.
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Affiliation(s)
- Michael L. Barnett
- Department of Health Policy and Management, Harvard T. H. Chan School of Public Health, Boston, Massachusetts
| | - Lissy Hu
- CarePort Health Inc, Boston, Massachusetts
| | | | - David C. Grabowski
- Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts
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27
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Feaster M, Goh YY. High Proportion of Asymptomatic SARS-CoV-2 Infections in 9 Long-Term Care Facilities, Pasadena, California, USA, April 2020. Emerg Infect Dis 2020; 26:2416-2419. [PMID: 32614768 PMCID: PMC7510707 DOI: 10.3201/eid2610.202694] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Our analysis of coronavirus disease prevalence in 9 long-term care facilities demonstrated a high proportion (40.7%) of asymptomatic infections among residents and staff members. Infection control measures in congregate settings should include mass testing–based strategies in concert with symptom screening for greater effectiveness in preventing the spread of severe acute respiratory syndrome coronavirus 2.
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Razak F, Shin S, Pogacar F, Jung HY, Pus L, Moser A, Lapointe-Shaw L, Tang T, Kwan JL, Weinerman A, Rawal S, Kushnir V, Mak D, Martin D, Shojania KG, Bhatia S, Agarwal P, Mukerji G, Fralick M, Kapral MK, Morgan M, Wong B, Chan TCY, Verma AA. Modelling resource requirements and physician staffing to provide virtual urgent medical care for residents of long-term care homes: a cross-sectional study. CMAJ Open 2020; 8:E514-E521. [PMID: 32819964 PMCID: PMC7850232 DOI: 10.9778/cmajo.20200098] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND The coronavirus disease 2019 (COVID-19) outbreak increases the importance of strategies to enhance urgent medical care delivery in long-term care (LTC) facilities that could potentially reduce transfers to emergency departments. The study objective was to model resource requirements to deliver virtual urgent medical care in LTC facilities. METHODS We used data from all general medicine inpatient admissions at 7 hospitals in the Greater Toronto Area, Ontario, Canada, over a 7.5-year period (Apr. 1, 2010, to Oct. 31, 2017) to estimate historical patterns of hospital resource use by LTC residents. We estimated an upper bound of potentially avoidable transfers by combining data on short admissions (≤ 72 h) with historical data on the proportion of transfers from LTC facilities for which patients were discharged from the emergency department without admission. Regression models were used to extrapolate future resource requirements, and queuing models were used to estimate physician staffing requirements to perform virtual assessments. RESULTS There were 235 375 admissions to general medicine wards, and residents of LTC facilities (age 16 yr or older) accounted for 9.3% (n = 21 948) of these admissions. Among the admissions of residents of LTC facilities, short admissions constituted 24.1% (n = 5297), and for 99.8% (n = 5284) of these admissions, the patient received laboratory testing, for 86.9% (n = 4604) the patient received plain radiography, for 41.5% (n = 2197) the patient received computed tomography and for 81.2% (n = 4300) the patient received intravenous medications. If all patients who have short admissions and are transferred from the emergency department were diverted to outpatient care, the average weekly demand for outpatient imaging per hospital would be 2.6 ultrasounds, 11.9 computed tomographic scans and 23.9 radiographs per week. The average daily volume of urgent medical virtual assessments would range from 2.0 to 5.8 per hospital. A single centralized virtual assessment centre staffed by 2 or 3 physicians would provide services similar in efficiency (measured by waiting time for physician assessment) to 7 separate centres staffed by 1 physician each. INTERPRETATION The provision of acute medical care to LTC residents at their facility would probably require rapid access to outpatient diagnostic imaging, within-facility access to laboratory services and intravenous medication and virtual consultations with physicians. The results of this study can inform efforts to deliver urgent medical care in LTC facilities in light of a potential surge in COVID-19 cases.
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Affiliation(s)
- Fahad Razak
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont.
| | - Saeha Shin
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Frances Pogacar
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Hae Young Jung
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Laura Pus
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Andrea Moser
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Lauren Lapointe-Shaw
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Terence Tang
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Janice L Kwan
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Adina Weinerman
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Shail Rawal
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Vladyslav Kushnir
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Denise Mak
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Danielle Martin
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Kaveh G Shojania
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Sacha Bhatia
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Payal Agarwal
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Geetha Mukerji
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Michael Fralick
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Moira K Kapral
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Matthew Morgan
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Brian Wong
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Timothy C Y Chan
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
| | - Amol A Verma
- Division of General Internal Medicine (Razak, Verma), St. Michael's Hospital; Department of Medicine (Razak, Moser, Lapointe-Shaw, Tang, Kwan, Weinerman, Rawal, Shojania, Bhatia, Mukerji, Kapral, Morgan, Verma), University of Toronto; Li Ka Shing Knowledge Institute (Razak, Shin, Pogacar, Jung, Kushnir, Mak, Fralick, Chan, Verma), St. Michael's Hospital; Department of Mechanical and Industrial Engineering (Pogacar, Chan), University of Toronto; Women's College Hospital Institute for Health Systems Solutions and Virtual Care (Pus, Martin, Bhatia, Agarwal, Mukerji), Women's College Hospital; Baycrest Geriatric Health Care System (Moser); Division of General Internal Medicine (Lapointe-Shaw, Rawal, Fralick), University Health Network, Toronto, Ont.; Trillium Health Partners (Tang), Mississauga, Ont.; Department of Medicine (Kwan, Fralick, Morgan), Mount Sinai Hospital; Sunnybrook Health Sciences Centre (Weinerman, Shojania, Wong); Department of Family and Community Medicine (Martin, Agarwal), University of Toronto, Toronto, Ont
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Shin JH, Shin IS. Investigation of Longitudinal Data Analysis: Hierarchical Linear Model and Latent Growth Model Using a Longitudinal Nursing Home Dataset. Res Gerontol Nurs 2020; 12:275-283. [PMID: 31755964 DOI: 10.3928/19404921-20191024-02] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Accepted: 06/19/2019] [Indexed: 01/11/2023]
Abstract
The appropriate use of the data analysis method in a longitudinal design remains controversial in gerontological nursing research. The objective of the current study is to compare statistical approaches between a hierarchical-linear model (HLM) and a latent-growth model (LGM) in random effects, variance explained, growth trajectory, and model fitness. Secondary analysis of longitudinal data was used. Two variables were chosen to demonstrate the comparison between statistical methods. The HLM was superior in addressing unbalanced data in repeated-measures analysis of variance (ANOVA) and multivariate ANOVA because its nested data structure and random effects could be estimated. The LGM had advantages in modeling growth trajectories and model-fit comparisons. Superior to the HLM, the LGM reported more acceptable data fit, reporting a quadratic model, and successfully differentiated between and within components. The current research provides some evidence for applying appropriate statistical methods when addressing longitudinal datasets in gerontological nursing research. [Research in Gerontological Nursing, 12(6), 275-283.].
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Lai KY, Pathipati MP, Blumenkranz MS, Leung LS, Moshfeghi DM, Toy BC, Myung D. Assessment of Eye Disease and Visual Impairment in the Nursing Home Population Using Mobile Health Technology. Ophthalmic Surg Lasers Imaging Retina 2020; 51:262-270. [PMID: 32511729 DOI: 10.3928/23258160-20200501-03] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 03/26/2020] [Indexed: 11/20/2022]
Abstract
BACKGROUND AND OBJECTIVE To characterize the burden of eye disease and the utility of teleophthalmology in nursing home patients, a population with ophthalmic needs not commensurate with care received. PATIENTS AND METHODS Informed consent was obtained from 78 California Bay Area skilled nursing facility patients. Near visual acuity (VA) and anterior/posterior segment photographs were taken with a smartphone-based VA app and ophthalmic camera system. The Nursing Home Vision-Targeted Health-Related Quality of Life questionnaire was also administered. Risk factors for visual impairment were assessed. Institutional review board approval was obtained from Stanford University. RESULTS Cataracts (51%), diabetic retinopathy (DR) (12%), optic neuropathy (12%), and age-related macular degeneration (AMD) (10%) were common findings; 11.7% had other referral-warranted findings. AMD and DR correlated with a higher risk of poor VA, with adjusted odds ratios of 22 (P = .01) and 43 (P = .004). CONCLUSIONS This study demonstrated a high prevalence of poor VA and ophthalmic disease in the nursing home population impacting quality of life. Smartphone-based teleophthalmology platforms have the potential to increase access to eye care for nursing home patients. [Ophthalmic Surg Lasers Imaging Retina. 2020;51:262-270.].
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Sivasundaram L, Tanenbaum JE, Mengers SR, Trivedi NN, Su CA, Salata MJ, Ochenjele G, Voos JE, Wetzel RJ. Identifying a clinical decision tool to predict discharge disposition following operative treatment of hip fractures in the United States. Injury 2020; 51:1015-1020. [PMID: 32122627 DOI: 10.1016/j.injury.2020.02.108] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Accepted: 02/19/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND Post-discharge management following operative treatment of hip fractures continues to be performed on a case-by-case basis, with no uniform guidelines dictating management. Predicting discharge to post-acute care (PAC) facilities (i.e. skilled nursing facilities and inpatient rehabilitation facilities) can assist preoperative planning and potentially decrease length of stay secondary to disposition issues. The goal of this study was to develop a nomogram using easily identified variables to preoperatively predict discharge disposition following operative treatment of hip fractures. METHODS Using the National Surgical Quality Improvement Program database, patients who underwent surgical intervention for hip fractures between 2012 and 2015 were identified. A multivariable logistic regression model was used to identify risk factors for discharge to a PAC facility, and a predictive nomogram was created based on these results. RESULTS From 2012 to 2015, 33,371 hip fractures were identified: 13,336 (40%) femoral neck fractures, and 20,035 (60%) intertrochanteric femur fractures. Of the patients identified, 26,082 (78.2%) were discharged to a PAC while the remainder were discharged home with or without home health. 70% of patients were female and 92.4% were Caucasian. When accounting for comorbidities, using the American Society of Anesthesiologists (ASA) classification system, 6,122 patients (18.4%) had 'Mild Systemic Disease' (ASA 2), 20,872 (62.6%) patients had 'Severe Systemic Disease' (ASA 3), and 6,006 (18.1%) had 'Life Threatening Disease' (ASA 4/5). The majority of patients were brought in from a 'Home' setting, while 10.4% of patients were admitted from a 'Long-Term Care' setting. After controlling for confounding variables, older age and increasing ASA class were predictive of an increased risk of discharge to a PAC. Diabetes, dyspnea, congestive heart failure, and chronic obstructive pulmonary disease were not associated with an increased risk of discharge to a PAC. DISCUSSION Discharge disposition following operative treatment of hip fractures can be reliably predicted using a nomogram with commonly identified preoperative variables. LEVEL OF EVIDENCE Level III, Retrospective Cohort Design, Observational Study.
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Affiliation(s)
- Lakshmanan Sivasundaram
- University Hospitals of Cleveland, Case Western Reserve University, Cleveland, OH, United States; MetroHealth Medical Center, Cleveland, OH, United States
| | - Joseph E Tanenbaum
- University Hospitals of Cleveland, Case Western Reserve University, Cleveland, OH, United States
| | - Sunita Rp Mengers
- University Hospitals of Cleveland, Case Western Reserve University, Cleveland, OH, United States.
| | - Nikunj N Trivedi
- University Hospitals of Cleveland, Case Western Reserve University, Cleveland, OH, United States
| | - Charles A Su
- University Hospitals of Cleveland, Case Western Reserve University, Cleveland, OH, United States
| | - Michael J Salata
- University Hospitals of Cleveland, Case Western Reserve University, Cleveland, OH, United States
| | - George Ochenjele
- University Hospitals of Cleveland, Case Western Reserve University, Cleveland, OH, United States
| | - James E Voos
- University Hospitals of Cleveland, Case Western Reserve University, Cleveland, OH, United States
| | - Robert J Wetzel
- University Hospitals of Cleveland, Case Western Reserve University, Cleveland, OH, United States
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Abstract
IMPORTANCE Although people living in rural areas of the United States are disproportionately older and more likely to die of conditions that require postacute care than those living in urban areas, rural-urban differences in postacute care utilization and outcomes have been understudied. OBJECTIVE To describe rural-urban differences in postacute care utilization and postdischarge outcomes. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study used data from Medicare beneficiaries 66 years and older admitted to 4738 US acute care hospitals for stroke, hip fracture, chronic obstructive pulmonary disease, congestive heart failure, or pneumonia between January 1, 2011, and September 30, 2015. Participants were tracked for 180 days after discharge. Data analyses were conducted between October 1, 2018, and May 30, 2019. EXPOSURES County of residence was classified as urban or rural using the US Department of Agriculture Rural-Urban Continuum Codes. Rural counties were divided into those adjacent and not adjacent to urban counties. MAIN OUTCOMES AND MEASURES Primary outcomes were discharge to community vs a formal postacute care setting (ie, skilled nursing facility, home health care, or inpatient rehabilitation facility) and readmission and mortality within 30, 90, and 180 days of hospital discharge. RESULTS Among 2 044 231 hospitalizations from 2011 to 2015, 1 538 888 (75.2%; mean [SD] age, 80.4 [8.3] years; 866 540 [56.3%] women) were among patients from urban counties, 322 360 (15.8%; mean [SD] age, 79.6 [8.1] years; 175 806 [54.5%] women) were among patients from urban-adjacent rural counties, and 182 983 (9.0%; mean [SD] age, 79.8 [8.1] years; 98 775 [54.0%] women) were among patients from urban-nonadjacent rural counties. The probability of discharge to community without postacute care did not differ by rurality. However, compared with patients from urban counties, patients from the most rural counties were more frequently discharged to a skilled nursing facility (adjusted difference, 3.5 [95% CI, 2.8-4.3] percentage points), while discharge to an inpatient rehabilitation facility was less common among patients from rural counties than among those from urban counties (urban vs urban-adjacent rural: adjusted difference, -1.9 [95% CI, -2.4 to -1.4] percentage points; urban vs urban-nonadjacent rural: adjusted difference, -1.8 [95% CI, -2.4 to -1.2] percentage points) as was discharge to home health care (urban vs urban-adjacent rural: adjusted difference, -1.7 [95% CI, -2.3 to -1.2] percentage points; urban vs urban-nonadjacent rural: adjusted difference, -2.4 [95% CI, -3.0 to -1.8]). For patients from the most rural counties, adjusted 30-day readmission rates were 0.4 (95% CI, 0.2-0.6) percentage points higher than those of patients from urban counties among those who were discharged to the community but 0.3 (95% CI, -0.6 to -0.1) percentage points lower among patients receiving postacute care. Adjusted 30-day mortality rates were 0.4 (95% CI, 0.3-0.5) percentage points higher for patients from the most rural counties discharged to the community and 2.0 (95% CI, -1.7 to 2.3) percentage points higher among those receiving postacute care. Rural-urban differences in 90-day and 180-day outcomes were similar. CONCLUSIONS AND RELEVANCE These findings suggest that rates of discharge to the community and postacute care settings were similar among patients from rural and urban counties. Rural-urban differences in mortality following discharge were much larger for patients receiving postacute care compared with patients discharged to the community setting. Improving postacute care in rural areas may reduce rural-urban disparities in patient outcomes.
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Affiliation(s)
- Cyrus M. Kosar
- Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, Brown University, Providence, Rhode Island
| | - Lacey Loomer
- Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, Brown University, Providence, Rhode Island
| | - Nasim B. Ferdows
- Edward R. Roybal Institute on Aging, University of Southern California, Los Angeles
| | - Amal N. Trivedi
- Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, Brown University, Providence, Rhode Island
| | - Orestis A. Panagiotou
- Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, Brown University, Providence, Rhode Island
| | - Momotazur Rahman
- Department of Health Services, Policy and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, Brown University, Providence, Rhode Island
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Abstract
Context: Medicaid has been linked to worse outcomes in a variety of diagnoses such as lung cancer, uterine cancer, and cardiac valve procedures. It has furthermore been linked to the reduced health-related quality of life outcomes after traumatic injuries when compared to other insurance groups. In spinal cord injury (SCI), the care provided in the subacute setting may vary based upon payor status, which may have implications on outcomes and cost of care.Design: A retrospective review utilizing the institutional trauma databank was performed for all adult patients with spinal cord injury since 2009. Pediatric patients were excluded. Insurance type, race, length of stay, discharge status (alive/dead), discharge disposition, injury severity score (ISS), and hospital charges billed were recorded.Results: Two hundred patients were identified. Overall 27.5% of patients with SCI during the period of our review were Medicaid beneficiaries. ISS was similar between Medicaid and non-Medicaid patients, but the Medicaid beneficiaries were younger (37 vs 50 years of age; P < .001). Medicaid beneficiaries had a significantly longer length of stay (20.9 days; P < .001) when compared to all other patients. They furthermore were more likely to be discharged home or to a skilled nursing facility rather than an acute rehabilitation center. Inpatient charges billed for Medicaid beneficiaries were significantly higher than those of non-Medicaid patients (203,264 USD vs 140,114 USD; P = .015), likely reflecting the increased length of stay while awaiting appropriate disposition.Conclusion: Medicaid patients with SCI in West Virginia had a longer hospital stay, higher charges billed, and were more likely to be discharged home or to a skilled nursing facility rather than an acute rehabilitation center, when compared to non-Medicaid patients. The lack of availability of rehabilitation facilities for Medicaid beneficiaries likely explains this difference.
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Affiliation(s)
- Cara L. Sedney
- Department of Neurosurgery, West Virginia University, Morgantown, West Virginia, USA
| | - Uzer Khan
- Department of Surgery, West Virginia University, Morgantown, West Virginia, USA
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Hong I, Goodwin JS, Reistetter TA, Kuo YF, Mallinson T, Karmarkar A, Lin YL, Ottenbacher KJ. Comparison of Functional Status Improvements Among Patients With Stroke Receiving Postacute Care in Inpatient Rehabilitation vs Skilled Nursing Facilities. JAMA Netw Open 2019; 2:e1916646. [PMID: 31800069 PMCID: PMC6902754 DOI: 10.1001/jamanetworkopen.2019.16646] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
IMPORTANCE Health care reform legislation and Medicare plans for unified payment for postacute care highlight the need for research examining service delivery and outcomes. OBJECTIVE To compare functional outcomes in patients with stroke after postacute care in inpatient rehabilitation facilities (IRF) vs skilled nursing facilities (SNF). DESIGN, SETTING, AND PARTICIPANTS This cohort study included patients with stroke who were discharged from acute care hospitals to IRF or SNF from January 1, 2013, to November 30, 2014. Medicare claims were used to link to IRF and SNF assessments. Data analyses were conducted from January 17, 2017, through April 25, 2019. EXPOSURES Inpatient rehabilitation received in IRFs vs SNFs. MAIN OUTCOMES AND MEASURES Changes in mobility and self-care measures during an IRF or SNF stay were compared using multivariate analyses, inverse probability weighting with propensity score, and instrumental variable analyses. Mortality between 30 and 365 days after discharge was included as a control outcome as an indicator for unmeasured confounders. RESULTS Among 99 185 patients who experienced a stroke between January 1, 2013, and November 30, 2014, 66 082 patients (66.6%) were admitted to IRFs and 33 103 patients (33.4%) were admitted to SNFs. A higher proportion of women were admitted to SNFs (21 466 [64.8%] women) than IRFs (36 462 [55.2%] women) (P < .001). Compared with patients admitted to IRFs, patients admitted to SNFs were older (mean [SD] age, 79.4 [7.6] years vs 83.3 [7.8] years; P < .001) and had longer hospital length of stay (mean [SD], 4.6 [3.0] days vs 5.9 [4.2] days; P < .001) than those admitted to IRFs. In unadjusted analyses, patients with stroke admitted to IRF compared with those admitted to SNF had higher mean scores for mobility on admission (44.2 [95% CI, 44.1-44.3] points vs 40.8 [95% CI, 40.7-40.9] points) and at discharge (55.8 [95% CI, 55.7-55.9] points vs 44.4 [95% CI, 44.3-44.5] points), and for self-care on admission (45.0 [95% CI, 44.9-45.1] points vs 41.8 [95% CI, 41.7-41.9] points) and at discharge (58.6 [95% CI, 58.5-58.7] points vs 45.1 [95% CI, 45.0-45.2] points). Additionally, patients in IRF compared with those in SNF had larger improvements for mobility score (11.6 [95% CI, 11.5-11.7] points vs 3.5 [95% CI, 3.4-3.6] points) and for self-care score (13.6 [95% CI, 13.5-13.7] points vs 3.2 [95% CI, 3.1-3.3] points). Multivariable, propensity score, and instrumental variable analyses showed a similar magnitude of better improvements in patients admitted to IRF vs those admitted to SNF. The differences between SNF and IRF in odds of 30- to 365-day mortality (unadjusted odds ratio, 0.48 [95% CI, 0.46-0.49]) were reduced but not eliminated in multivariable analysis (adjusted odds ratio, 0.72 [95% CI, 0.69-0.74]) and propensity score analysis (adjusted odds ratio, 0.75 [95% CI, 0.72-0.77]). These differences were no longer statistically significant in the instrumental variable analyses. CONCLUSIONS AND RELEVANCE In this cohort study of a large national sample, inpatient rehabilitation in IRFs for patients with stroke was associated with substantially improved physical mobility and self-care function compared with rehabilitation in SNFs. This finding raises questions about the value of any policy that would reimburse IRFs or SNFs at the same standard rate for stroke.
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Affiliation(s)
- Ickpyo Hong
- University of Texas Medical Branch, School of Health Professions, Division of Rehabilitation Sciences, Galveston
| | - James S. Goodwin
- University of Texas Medical Branch, School of Medicine, Sealy Center on Aging, Department of Internal Medicine, Galveston
| | - Timothy A. Reistetter
- University of Texas Health Science Center at San Antonio, School of Health Professions, Department of Occupational Therapy, San Antonio
| | - Yong-Fang Kuo
- University of Texas Medical Branch, School of Medicine, Sealy Center on Aging, Department of Preventive Medicine and Population Health, Galveston
| | - Trudy Mallinson
- George Washington University, School of Medicine and Health Sciences, Clinical Research and Leadership, Washington, DC
| | - Amol Karmarkar
- University of Texas Medical Branch, School of Health Professions, Division of Rehabilitation Sciences, Galveston; now with Department of Physical Medicine and Rehabilitation, School of Medicine, Virginia Commonwealth University, Richmond
| | - Yu-Li Lin
- University of Texas Medical Branch, School of Medicine, Department of Preventive Medicine and Population Health, Galveston
| | - Kenneth J. Ottenbacher
- University of Texas Medical Branch, School of Health Professions, Sealy Center on Aging, Division of Rehabilitation Sciences, Galveston
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Abstract
OBJECTIVE To investigate the impact of Medicare's skilled nursing facility (SNF) copayment policy, with a large increase in the daily copayment rate on the 20th day of a benefit period, on length of stay, patient outcomes, and costs. DATA SOURCES AND STUDY SETTING Retrospective cohort study from 2012 to 2016 using Medicare claims and SNF assessment data, including SNF admissions for Medicare fee-for-service beneficiaries. STUDY DESIGN We first estimate how changes in Medicare's SNF copayment on the 21st day of a patient's benefit period affect length of SNF stay. We then use benefit day on admission as an instrumental variable to estimate the impact of SNF length of stay related to the copayment policy on readmission and Medicare payment. PRINCIPAL FINDINGS From 2012 to 2016, we examined 291 134 SNF admissions. Higher benefit day on SNF admission was strongly associated with shorter SNF stays. A 1-day shorter SNF stay was associated with higher readmission rate within 30 days of hospital discharge (1.5 percentage points; 95% CI 1.4-1.6, P < .001) and within 30 days of SNF discharge (0.9 percentage points; 95% CI 0.8-1.0), lower total Medicare payment for the 90-day episode after hospital discharge ($396; 95% CI 361-431, P < .001), but $179 higher payment for the 90 days after SNF discharge (95% CI 149-210, P < .001), offsetting the lower payment for the shorter index SNF stay. CONCLUSIONS Medicare's SNF copayment policy is associated with shorter lengths of stay and worse patient outcomes, suggesting the copayment policy has unintended and negative effects on patient outcomes.
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Affiliation(s)
- Rachel M. Werner
- Department of MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Leonard Davis Institute of Health EconomicsUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Center for Health Equity Research and PromotionCrescenz VA Medical CenterPhiladelphiaPennsylvania
| | - R. Tamara Konetzka
- Department of Public Health SciencesUniversity of ChicagoChicagoIllinois
| | - Mingyu Qi
- Department of MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Norma B. Coe
- Leonard Davis Institute of Health EconomicsUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of Medical Ethics and Health PolicyPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvania
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Dworsky JQ, Childers CP, Copeland T, Maggard-Gibbons M, Tan HJ, Saliba D, Russell MM. Geriatric Events Among Older Adults Undergoing Nonelective Surgery Are Associated with Poor Outcomes. Am Surg 2019; 85:1089-1093. [PMID: 31657300 PMCID: PMC8019520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Older adults undergoing nonelective surgery are at risk for geriatric events (GEs: delirium, dehydration, falls/fractures, failure to thrive, and pressure ulcers), but the impact of GEs on postoperative outcomes is unclear. Using the 2013 to 2014 National Inpatient Sample, we analyzed nonelective hospital admissions for five common operations (laparoscopic cholecystectomy, colectomy, soft tissue debridement, small bowel resection, and laparoscopic appendectomy) in older adults (aged ≥65 years) and a younger referent group (aged 55-64 years). Nationally weighted descriptive statistics were generated for GEs. Logistic regression controlling for patient, procedure, and hospital characteristics estimated the association of 1) age with GEs and 2) GEs with outcomes. Of 471,325 overall admissions, 64.7 per cent were aged ≥65 years. The rate of any GE in older adults was 26.9 per cent; GEs varied by age and procedure (P < 0.001). After adjustment, the probability of any GE increased with age category (P < 0.001); having any GE was associated with higher probability of all outcomes (P < 0.001): mortality (4.5% vs 0.8%), postoperative complications (61.7% vs 24.9%), prolonged length of stay (24.3% vs 7.9%), and skilled nursing facility discharge (46.6% vs 10.3%). In addition, there was a dose-response relationship between GEs and negative outcomes. GEs are prevalent in the nonelective surgery setting and associated with worse clinical outcomes. Quality improvement efforts should focus on addressing GEs.
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Affiliation(s)
- Jill Q. Dworsky
- Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, CA
- Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, CA
| | - Christopher P. Childers
- Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, CA
- Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, CA
| | - Timothy Copeland
- Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, CA
| | | | - Hung-Jui Tan
- Department of Urology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Debra Saliba
- Geriatric Research Education and Clinical Center, VA Greater Los Angeles Healthcare System, Los Angeles, CA
- UCLA/JH Borun Center for Gerontological Research, Los Angeles, CA
- RAND Corporation, Santa Monica, CA
| | - Marcia M. Russell
- Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, CA
- Department of Surgery, VA Greater Los Angeles Healthcare System, Los Angeles, CA
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McGarry BE, Grabowski DC. Managed care for long-stay nursing home residents: an evaluation of Institutional Special Needs Plans. Am J Manag Care 2019; 25:438-443. [PMID: 31518093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
OBJECTIVES To evaluate the patterns of clinical service use for long-term nursing home residents enrolled in UnitedHealthcare's Medicare Advantage Institutional Special Needs Plans (I-SNPs), which provide on-site direct coordinated care for beneficiaries through the use of advanced practice clinicians. STUDY DESIGN Observational analysis of 8052 I-SNP members and 12,982 Medicare fee-for-service (FFS) long-term nursing home residents across 13 states. METHODS Multivariate analyses were performed to compare rates of emergency department (ED), inpatient, and skilled nursing facility (SNF) use between I-SNP members and Medicare FFS long-term nursing home residents. RESULTS In comparison with FFS institutionalized Medicare beneficiaries, I-SNP members had 51% lower ED use, 38% fewer hospitalizations, and 45% fewer readmissions, whereas their SNF use was 112% higher. CONCLUSIONS "At-risk" models, administered through specialized Medicare Advantage plans, that invest in clinical management in the nursing home setting have the potential to allow individuals to receive care on-site and avoid costly inpatient transfers.
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Affiliation(s)
| | - David C Grabowski
- Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA 02115-5899.
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Rivera-Hernandez M, Rahman M, Mor V, Trivedi AN. Racial Disparities in Readmission Rates among Patients Discharged to Skilled Nursing Facilities. J Am Geriatr Soc 2019; 67:1672-1679. [PMID: 31066913 PMCID: PMC6684399 DOI: 10.1111/jgs.15960] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Revised: 04/02/2019] [Accepted: 04/03/2019] [Indexed: 11/30/2022]
Abstract
OBJECTIVES Prior studies have reported mixed findings about the existence of racial disparities in readmission rates among Medicare Advantage beneficiaries, but these studies used data from one state, focused on black-white disparities, and did not focus on patients discharged to skilled nursing facilities (SNFs). The objective of the study was to characterize racial and ethnic disparities in rates of 30-day rehospitalization directly from SNFs among fee-for-service and Medicare Advantage patients. DESIGN A cross-sectional study of admissions to SNFs in 2015 was conducted. SETTING SNFs across the United States. PARTICIPANTS The sample included 1 500 334 white, 213 848 African American, and 99 781 Hispanic Medicare patients who were admitted to 13 375 SNFs. MEASUREMENTS The main outcome of interest was readmission, identified as patients sent back to any hospital directly from the SNF within 30 days of admission, as indicated on the Minimum Data Set discharge assessment. RESULTS Overall readmission rates for fee-for-service patients were 16.7% (95% confidence interval [CI] = 16.7%-16.8%) for whites, 18.8% (95% CI = 18.7%-19.0%) for African Americans, and 17.4% (95% CI = 17.1%-17.7%) for Hispanics. Readmission rates in Medicare Advantage were 14.7% (95% CI = 14.5%-14.8%) for whites, 16.8% (95% CI = 16.6%-17.1%) for African Americans, and 15.3% (95% CI = 14.9%-15.6%) for Hispanics. We also found that African Americans had about 1% higher readmission rates than whites, even when they received care within the same SNF. No statistically significant differences were found in the magnitude of within-SNF racial disparities in Medicare Advantage compared with Medicare fee-for-service. CONCLUSION We found racial disparities in readmission rates even within the same facility for both Medicare Advantage and fee-for-service beneficiaries. Intervention to reduce disparities in readmission rates, as well as more comprehensive quality measures that incorporate outcomes for Medicare Advantage enrollees, are needed. J Am Geriatr Soc 67:1672-1679, 2019.
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Affiliation(s)
- Maricruz Rivera-Hernandez
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology & Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
| | - Momotazur Rahman
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology & Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
| | - Vincent Mor
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology & Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
- Providence VA Medical Center, Providence, Rhode Island
| | - Amal N Trivedi
- Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology & Healthcare Research, Brown University School of Public Health, Providence, Rhode Island
- Providence VA Medical Center, Providence, Rhode Island
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Cornell PY, Grabowski DC, Norton EC, Rahman M. Do report cards predict future quality? The case of skilled nursing facilities. J Health Econ 2019; 66:208-221. [PMID: 31280055 PMCID: PMC7248645 DOI: 10.1016/j.jhealeco.2019.05.008] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 04/23/2019] [Accepted: 05/20/2019] [Indexed: 05/20/2023]
Abstract
Report cards on provider performance are intended to improve consumer decision-making and address information gaps in the market for quality. However, inadequate risk adjustment of report-card measures often biases comparisons across providers. We test whether going to a skilled nursing facility (SNF) with a higher star rating leads to better quality outcomes for a patient. We exploit variation over time in the distance from a patient's residential ZIP code to SNFs with different ratings to estimate the causal effect of admission to a higher-rated SNF on health care outcomes, including mortality. We found that patients who go to higher-rated SNFs achieved better outcomes, supporting the validity of the SNF report card ratings.
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Affiliation(s)
- Portia Y Cornell
- Department of Health Services Policy and Practice, Brown University, Box G-S121(6), Providence, RI, 02912, United States; Providence Veterans Administration Medical Center, United States.
| | - David C Grabowski
- Department of Health Care Policy, Harvard Medical School, 180 Longwood Avenue, Boston, MA, 02115, United States.
| | - Edward C Norton
- Department of Health Management and Policy and Department of Economics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI, 48109, United States; National Bureau of Economic Research, United States.
| | - Momotazur Rahman
- Department of Health Services Policy and Practice, Brown University, Box G-S121(6), Providence, RI, 02912, United States.
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Zhu JM, Navathe A, Yuan Y, Dykstra S, Werner RM. Medicare's bundled payment model did not change skilled nursing facility discharge patterns. Am J Manag Care 2019; 25:329-334. [PMID: 31318505 PMCID: PMC6788623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
OBJECTIVES To evaluate whether participation in Medicare's voluntary Bundled Payments for Care Improvement (BPCI) model was associated with changes in discharge referral patterns to skilled nursing facilities (SNFs), specifically number of SNF partners and discharge concentration. STUDY DESIGN Retrospective observational study using difference-in-differences analysis. METHODS We used Medicare claims data from 2010 to 2015 to identify admissions for lower joint replacement surgery and the following medical conditions: congestive heart failure, renal failure, sepsis, pneumonia, urinary tract and kidney infections, chronic obstructive pulmonary disease, and stroke. We used difference-in-differences analyses to assess changes in discharge patterns among BPCI-participating hospitals compared with matched control hospitals. RESULTS Our analytic sample included 3078 acute care hospitals and 14,866 Medicare-certified SNFs in the United States, encompassing more than 47 million hospital discharges. Of these hospitals, 416 participated in BPCI, with the majority selecting into joint replacement episodes (n = 295). BPCI participation was not associated with any change in number of SNF partners (increase by 0.8 SNFs among BPCI hospitals relative to non-BPCI hospitals; 95% CI, -0.2 to 1.9; P = .11) or in discharge concentration (increase in Herfindahl-Hirschman Index of 0.2 among BPCI hospitals relative to non-BPCI hospitals; 95% CI, -68.7 to 69.1; P = .36). Results did not vary across clinical conditions and were robust across duration of BPCI participation and with different comparison groups. CONCLUSIONS Hospital participation in BPCI was not associated with changes in the number of SNF partners or in discharge concentration relative to non-BPCI hospitals. More research is needed to understand how hospitals are responding to bundled payment incentives and specific practices that contribute to improvements in cost and quality.
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Affiliation(s)
- Jane M Zhu
- Oregon Health and Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239.
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Bain AM, Werner RM, Yuan Y, Navathe AS. Do Hospitals Participating in Accountable Care Organizations Discharge Patients to Higher Quality Nursing Homes? J Hosp Med 2019; 14:288-289. [PMID: 30897056 PMCID: PMC7172035 DOI: 10.12788/jhm.3147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2018] [Accepted: 12/11/2018] [Indexed: 11/20/2022]
Abstract
We examined whether hospitals participating in Medicare's Shared Saving Program increased the use of highly rated skilled nursing facilities (SNFs) or decreased the use of low-rated SNFs hospital-wide after initiation of their accountable care organization (ACO) contracts compared with non-ACO hospitals. Using a difference-in-differences design, we estimated the change in the probability of discharge to 5-star and 1-star SNFs among all beneficiaries discharged from ACO-participating hospitals after the hospital initiated ACO participation. After joining an ACO, the percentage of hospital discharges going to a high-quality SNF increased by 3.4 percentage points on a base of 15.4% (95% confidence interval [CI] 1.3-5.5, P = .002) compared with non-ACO-participating hospitals. The probability of discharge from an ACO-participating hospital to low-quality SNFs did not change significantly compared with non-ACO-participating hospitals. Our findings indicate that ACO-participating hospitals were more likely to discharge patients to highly rated SNFs after they began their ACO contract but did not change the likelihood of discharge to lower rated SNFs in comparison with non-ACO hospitals.
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Affiliation(s)
- Alexander M Bain
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Rachel M Werner
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Corporal Michael J. Cresencz VA Medical Center, Philadelphia, Pennsylvania
- Leonard Davis Institute of Health Economics, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Yihao Yuan
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Amol S Navathe
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Corporal Michael J. Cresencz VA Medical Center, Philadelphia, Pennsylvania
- Leonard Davis Institute of Health Economics, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania
- Corresponding Author: Amol S. Navathe, MD, PhD; E-mail: ; Telephone: 215-573-4047; Twitter: @AmolNavathe
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San-Juan-Rodriguez A, Zhang Y, He M, Hernandez I. Association of Antidementia Therapies With Time to Skilled Nursing Facility Admission and Cardiovascular Events Among Elderly Adults With Alzheimer Disease. JAMA Netw Open 2019; 2:e190213. [PMID: 30821828 PMCID: PMC6484658 DOI: 10.1001/jamanetworkopen.2019.0213] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
IMPORTANCE To date, no study has compared time to skilled nursing facility (SNF) admission and cardiovascular events across medications available to treat Alzheimer disease. OBJECTIVE To compare time to SNF admission and cardiovascular events between acetylcholinesterase inhibitor (AChEI) monotherapy, memantine hydrochloride monotherapy, and combination therapy with an AChEI and memantine in treating elderly adults with Alzheimer disease. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study uses January 1, 2006, to December 31, 2014, claims data from a 5% random sample of Medicare beneficiaries who had received a new diagnosis of Alzheimer disease between January 1, 2007, and December 31, 2013, and who initiated AChEI monotherapy, memantine monotherapy, or combination therapy with an AChEI and memantine (N = 73 475). Patients were followed up until discontinuation of treatment, switch of treatment, death, or the end of the study period. Statistical analysis was conducted from February 15, 2018, to June 15, 2018. EXPOSURES Acetylcholinesterase inhibitor monotherapy (n = 44 424), memantine monotherapy (n = 11 809), and combination therapy with an AChEI and memantine (n = 17 242). MAIN OUTCOMES AND MEASURES Primary outcomes were time to SNF admission and the composite of the following cardiovascular events: acute myocardial infarction, bradycardia, syncope, atrioventricular block, QT interval prolongation, and ventricular tachycardia. Cox proportional hazards regression models were constructed to compare outcomes between each pair of treatment groups, controlling for a comprehensive list of patient characteristics. RESULTS The study population included 73 475 participants (53 068 women and 20 407 men; mean [SD] age, 81.8 [8.3] years); 25.5% of the participants initiating AChEI monotherapy, 25.6% of participants initiating memantine monotherapy, and 29.7% of participants initiating combination therapy with an AChEI and memantine were admitted to an SNF. Similarly, 22.2% of the participants initiating AChEI monotherapy, 20.0% of those initiating memantine monotherapy, and 24.5% of those initiating combination therapy experienced at least 1 cardiovascular event. No difference in time to SNF admission was found across the 3 treatment groups. The risk of the composite measure of any cardiovascular event did not differ between the combination therapy and AChEI monotherapy groups (adjusted hazard ratio [aHR], 0.99; 95% CI, 0.96-1.03); however, it was higher for both AChEI monotherapy (aHR, 1.07; 95% CI, 1.02-1.12) and combination therapy (aHR, 1.07; 95% CI, 1.01-1.12), relative to memantine monotherapy. This result was mainly driven by the lower risk of bradycardia and syncope observed for the memantine monotherapy group relative to both AChEI monotherapy (bradycardia: aHR, 0.88; 95% CI, 0.82-0.95; and syncope: aHR, 0.92; 95% CI, 0.86-0.97) and combination therapy (bradycardia: aHR, 0.89; 95% CI, 0.82-0.97; and syncope: aHR, 0.87; 95% CI, 0.83-0.94). CONCLUSIONS AND RELEVANCE Time to SNF admission did not differ across treatment groups, but memantine monotherapy was associated with a lower risk of cardiovascular events compared with both AChEI monotherapy and combination therapy with an AChEI and memantine.
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Affiliation(s)
- Alvaro San-Juan-Rodriguez
- Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Yuting Zhang
- Melbourne Institute, Faculty of Business and Economics, University of Melbourne, Melbourne, Victoria, Australia
| | - Meiqi He
- Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Inmaculada Hernandez
- Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania
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Weissblum L, Huckfeldt P, Escarce J, Karaca-Mandic P, Sood N. Skilled Nursing Facility Participation in Medicare's Bundled Payments for Care Improvement Initiative: A Retrospective Study. Arch Phys Med Rehabil 2019; 100:307-314. [PMID: 30291827 PMCID: PMC6348124 DOI: 10.1016/j.apmr.2018.08.186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Revised: 06/13/2018] [Accepted: 08/26/2018] [Indexed: 11/24/2022]
Abstract
OBJECTIVE To investigate differences in facility characteristics, patient characteristics, and outcomes between skilled nursing facilities (SNFs) that participated in Medicare's voluntary Bundled Payments for Care Improvement (BPCI) initiative and nonparticipants, prior to BPCI. DESIGN Retrospective, cross-sectional comparison of BPCI participants and nonparticipants. SETTING SNFs. PARTICIPANTS All Medicare-certified SNFs (N=15,172) and their 2011-2012 episodes of care for chronic obstructive pulmonary disease, congestive heart failure, femur and hip/pelvis fracture, hip and femur procedures, lower extremity joint replacement, and pneumonia (N=873,739). INTERVENTIONS Participation in a bundled payment program that included taking financial responsibility for care within a 90-day episode. MAIN OUTCOME MEASURES This study investigates the characteristics of bundled payment participants and their patient characteristics and outcomes relative to nonparticipants prior to BPCI, to understand the implications of a broader implementation of bundled payments. RESULTS SNFs participating in BPCI were more likely to be in urban areas (80.8%-98.4% vs 69.5%) and belong to a chain or system (73.8%-85.5% vs 55%), and were less likely to be located in the south (13.1%-20.2% vs 35.4%). Quality performance was similar or higher in most cases for SNFs participating in BPCI relative to nonparticipants. In addition, BPCI participants admitted higher socioeconomic status patients with similar clinical characteristics. Initial SNF length of stay was shorter and hospital readmission rates were lower for BPCI patients compared to nonparticipant patients. CONCLUSIONS We found that SNFs participating in the second financial risk-bearing phase of BPCI represented a diversity of SNF types, regions, and levels of quality and the results may provide insight into a broader adoption of bundled payment for postacute providers.
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Affiliation(s)
- Lianna Weissblum
- Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Peter Huckfeldt
- Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN
| | - José Escarce
- David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA
| | - Pinar Karaca-Mandic
- Department of Finance, Carlson School of Management, University of Minnesota, Minneapolis, MN
| | - Neeraj Sood
- Sol Price School of Public Policy, University of Southern California, Los Angeles, CA.
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Cross DA, McCullough JS, Adler-Milstein J. Drivers of health information exchange use during postacute care transitions. Am J Manag Care 2019; 25:e7-e13. [PMID: 30667612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
OBJECTIVES To characterize the drivers of the use of electronic health information exchange (HIE) by skilled nursing facilities (SNFs) to access patient hospital data during care transitions. STUDY DESIGN Explanatory, sequential mixed-methods study. Quantitative data from an audit log captured HIE use by 3 SNFs to retrieve hospitalization information for the 5487 patients discharged to their care between June 2014 and March 2017, along with patient demographic data. Qualitative inquiry included 16 interviews at the discharging hospital and HIE-enabled SNFs. METHODS Multivariate probit models determined patient-level factors associated with SNF HIE use. These models informed subsequent in-depth, semistructured interviews to refine our understanding of usage patterns, as well as facilitators of and barriers to use. RESULTS HIE was used by SNFs for 46% of patients for whom it was available; 29% of patients had records accessed within 3 days of hospital discharge. Overall HIE use was more likely for new versus returning SNF patients (3.8%; P <.001) and when a patient was discharged from the emergency department rather than an inpatient unit (6.8%; P = .027). HIE use was less likely on weekends (-4.3%; P = .036) and for more complex patients, as measured by length of stay (-0.4% per day; P ≤.001) or number of conditions (-0.3% per diagnosis; P ≤.001). Interviews revealed distinct HIE use cases across SNFs; perceiving ability to access information not otherwise available in paper discharge materials, as well as workflow integration, were critical facilitators of use during transitional care. CONCLUSIONS HIE between hospitals and SNFs is underused. A mixed-methods approach is critical to understanding and explaining variation in implementation and use. Creating value requires hospitals and SNFs to codevelop system design, usage guidelines, and workflows that meaningfully integrate HIE into care delivery.
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Affiliation(s)
- Dori A Cross
- Division of Health Policy and Management, University of Minnesota School of Public Health, 420 Delaware St SE, MMC 729, Minneapolis, MN 55455.
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Schreiner N, Schreiner S, Daly B. The Association Between Chronic Condition Symptoms and Treatment Burden in a Skilled Nursing Population. J Gerontol Nurs 2018; 44:45-52. [PMID: 30484847 PMCID: PMC6747057 DOI: 10.3928/00989134-20181019-01] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Accepted: 09/24/2018] [Indexed: 11/20/2022]
Abstract
The purpose of the current study was to determine the relationship between chronic condition symptoms and treatment burden in older adults transitioning from skilled nursing facilities to home. Treatment burden is defined as the burden associated with adhering to a prescribed chronic condition self-management regimen. Analysis of correlations between chronic condition symptoms and treatment burden revealed that symptoms and treatment burden are positively correlated (p < 0.05). Multivariate analysis (adjusted R2 = 0.40, F[10, 63] = 5.96, p < 0.001), controlling for other known antecedents of treatment burden, demonstrated that fatigue (standardized beta coefficient = 0.47, p < 0.001) predicted higher levels of treatment burden. Post hoc analysis revealed caregiver presence partially mediated the effect of fatigue on treatment burden, decreasing treatment burden during transition. Findings support existing transitional care literature suggesting that clinical assessment, including symptom screening, treatment of symptoms, and/or intervention reducing the impact of symptoms on patients' health and well-being, may lower treatment burden, thus improving self-management adherence. [Journal of Gerontological Nursing, 44(12), 45-52.].
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Halevi AE, Mauer E, Saldinger P, Hagler DJ. Predictors of Dependency in Geriatric Trauma Patients with Rib Fractures: A Population Study. Am Surg 2018; 84:1856-1860. [PMID: 30606339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The geriatric trauma population is unique. These patients are at risk of being discharged to rehabilitation or a skilled nursing facility, instead of being returned to their homes, placing a significant burden on both the patient families and society. This study evaluated which patient characteristics increase the likelihood of a previously independent geriatric blunt trauma becoming functionally dependent and being discharged to a location other than home. Data were extracted from the National Trauma Data Bank from 2012 to 2014 for blunt trauma patients ≥65 years old, admitted from home, with one or more rib fractures. Primary outcomes were discharge home versus a facility. Subgroup analysis evaluated disposition to acute short-term rehabilitation or subacute rehabilitation or skilled nursing facility. Multivariable analysis was used to calculate probabilities of disposition based on the above variables, controlling for comorbidities. Sixteen thousand six hundred thirty-two patients were included. Only 58 per cent were discharged home. Increased age, ≥4 rib fractures, white race, and female gender were found to increase the risk of discharge to a facility. In addition, patients with chronic renal failure, history of diabetes, obesity, or heart failure were less likely to be discharged home. This study shows that age, gender, race, and the number of rib fractures are statistically significant in predicting which patients are less likely to be discharged home. This reinforces the need for the development of triage and treatment protocols in this higher risk population, to decrease the social and financial burden of these injuries.
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Huckfeldt PJ, Weissblum L, Escarce JJ, Karaca‐Mandic P, Sood N. Do Skilled Nursing Facilities Selected to Participate in Preferred Provider Networks Have Higher Quality and Lower Costs? Health Serv Res 2018; 53:4886-4905. [PMID: 30112827 PMCID: PMC6232398 DOI: 10.1111/1475-6773.13027] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVE To determine whether skilled nursing facilities (SNFs) chosen by health systems to participate in preferred provider networks exhibited differences in quality, costs, and patient outcomes relative to other SNFs after accounting for differences in case mix. DATA SOURCES Medicare provider and claims data, 2012 and 2013. STUDY DESIGN We compared SNFs included in preferred networks relative to other SNFs in the same market, prior to the establishment of preferred provider networks. DATA EXTRACTION METHODS We linked the SNFs in our sample to facility characteristics and quality data. We identified SNF admissions and hospitalizations in claims data and limited the analysis to patients discharged from the hospitals in our sample. We obtained patient characteristics from Medicare summary files and the preceding hospital stay. PRINCIPAL FINDINGS Preferred SNFs exhibited better performance across publicly reported quality measures. Patients admitted to preferred SNFs exhibited shorter stays, lower Medicare payments, and lower probability of SNF readmission relative to nonpreferred SNFs. CONCLUSIONS Our results imply that health systems selected SNFs with lower resource use and better performance on quality measures. Thus, the trend toward preferred provider networks could have implications for Medicare spending and patient health.
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Affiliation(s)
- Peter J. Huckfeldt
- Division of Health Policy and ManagementUniversity of Minnesota School of Public HealthMinneapolisMN
| | - Lianna Weissblum
- Division of Health Policy and ManagementUniversity of Minnesota School of Public HealthMinneapolisMN
| | - José J. Escarce
- Department of MedicineDavid Geffen School of Medicine at UCLALos AngelesCA
| | - Pinar Karaca‐Mandic
- Department of FinanceCarlson School of ManagementUniversity of MinnesotaMinneapolisMN
| | - Neeraj Sood
- Sol Price School of Public PolicySchaeffer Center for Health Policy and EconomicsUniversity of Southern CaliforniaLos AngelesCA
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Agarwal D, Werner RM. Effect of Hospital and Post-Acute Care Provider Participation in Accountable Care Organizations on Patient Outcomes and Medicare Spending. Health Serv Res 2018; 53:5035-5056. [PMID: 30066420 PMCID: PMC6232507 DOI: 10.1111/1475-6773.13023] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
OBJECTIVE To test for differences in patient outcomes when hospital and post-acute care (PAC) providers participate in accountable care organizations (ACOs). DATA/SETTING Using Medicare claims, we examined changes in readmission, Medicare spending, and length of stay among patients admitted to ACO-participating hospitals and PAC providers. DESIGN We compared changes in outcomes among patients discharged from ACO-participating hospitals/PACs before and after participation to changes among patients discharged from non-participating hospitals/PACs over the same time period. RESULTS Patients discharged from an ACO-participating hospitals and skilled nursing facilities (SNF) had lower readmission rates (-1.7 percentage points, p-value = .03) than before ACO participation and non-participants; and lower per-discharge Medicare spending (-$940, p-value = .001), and length of stay (-3.1 days, p-value <.001) in SNF. Effects among ACO-participating hospitals without a co-participating SNF were smaller. Patients discharged from an ACO-participating hospital and home health agency had lower Medicare per-discharge spending (-$209; p-value = .06) and length of stay (-1.6 days, p-value <.001) for home health compared to before ACO participation and non-participants. Discharge from an ACO-participating hospital and inpatient rehabilitation facility did not impact patient outcomes or spending. CONCLUSIONS Hospital and SNF participation in an ACO was associated with lower readmission rates, Medicare spending on SNF, and SNF length of stay. These results lend support to the ACO payment model.
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Affiliation(s)
- Divyansh Agarwal
- Medical Scientist Training Program (MSTP)Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA
- Department of StatisticsThe Wharton SchoolUniversity of PennsylvaniaPhiladelphiaPA
| | - Rachel M. Werner
- Division of General Internal MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPA
- Center for Health Equity Research and PromotionCrescenz VA Medical CenterPhiladelphiaPA
- Leonard Davis Institute of Health EconomicsUniversity of PennsylvaniaPhiladelphiaPA
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Malik AT, Kim J, Yu E, Khan SN. Discharge to Inpatient Care Facility After Anterior Lumbar Interbody Fusion: Incidence, Predictors, and Postdischarge Outcomes. World Neurosurg 2018; 122:e584-e590. [PMID: 31108074 DOI: 10.1016/j.wneu.2018.10.108] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 10/15/2018] [Accepted: 10/17/2018] [Indexed: 11/19/2022]
Abstract
BACKGROUND Despite a significant number of patients being discharged to inpatient care facilities after anterior lumbar interbody fusion (ALIF), the current literature remains limited regarding the predictors associated with a nonhome discharge and the impact of continued inpatient care in a facility on postdischarge outcomes. METHODS The 2013-2016 American College of Surgeons National Surgical Quality Improvement Program was queried using Current Procedural Terminology (CPT) codes for ALIF (CPT-22558) and additional level fusions (CPT-22585). Discharge to inpatient care facilities included discharge to skilled care facilities and/or inpatient rehabilitation units. RESULTS Independent predictors of an inpatient care facility discharge were age older than 45 years (P < 0.001), female sex (P < 0.001), more than 10% body weight loss in the last 6 months prior to surgery (P=0.012), American Society of Anesthesiologists grade greater than II (P=0.005), undergoing a 2-level (P < 0.001) or more than 2-level fusion (P=0.017), a length of stay greater than 3 days (P < 0.001), and the occurrence of any predischarge complication (P < 0.001). After adjustment for differences in clinical and baseline characteristics between the 2 groups, discharge to an inpatient care facility after ALIF was independently associated with higher odds of any postdischarge complication (P=0.010), postdischarge wound complication (P=0.005), and postdischarge septic complications (P=0.011). No significant impact was seen on 30-day readmissions (P=0.943), 30-day reoperations (P=0.228), and 30-day mortality (P=0.913). CONCLUSIONS With an increasing focus toward minimizing costs associated with postacute care, providers should understand the need of appropriate preoperative risk stratification and construction of care pathways aimed at a home discharge to reduce the occurrence and/or risk of experiencing postdischarge complications.
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Affiliation(s)
- Azeem Tariq Malik
- The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Jeffery Kim
- The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Elizabeth Yu
- The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Safdar N Khan
- The Ohio State University Wexner Medical Center, Columbus, Ohio, USA.
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Abstract
OBJECTIVES To determine how the risk of subsequent long-term care (LTC) placement varies between skilled nursing facilities (SNFs) and the SNF characteristics associated with this risk. DESIGN Population-based national cohort study with participants nested in SNFs and hospitals in a cross-classified multilevel model. SETTING SNFs (N=6,680). PARTICIPANTS Fee-for-service Medicare beneficiaries (N=552,414) discharged from a hospital to a SNF in 2013. MEASUREMENTS Participant characteristics from Medicare data and the Minimum Data Set. SNF characteristics from Medicare and Nursing Home Compare. Outcome was a stay of 90 days or longer in a LTC nursing home within 6 months of SNF admission. RESULTS Within 6 months of SNF admission, 10.4% of participants resided in LTC. After adjustments for participant characteristics, the SNF where a participant received care explained 7.9% of the variance in risk of LTC, whereas the prior hospital explained 1.0%. Individuals in SNFs with excellent quality ratings had 22% lower odds of transitioning to LTC than those in SNFs with poor ratings (odds ratio=0.78, 95% confidence interval=0.74-0.84). Variation between SNFs and associations with quality markers were greater in sensitivity analyses limited to individuals least likely to require LTC. Results were essentially the same in a number of other sensitivity analyses designed to reduce potential confounding. CONCLUSION Risk of subsequent LTC placement, an important and negatively viewed outcome for older adults, varies substantially between SNFs. Individuals in higher-quality SNFs are at lower risk.
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Affiliation(s)
- James S. Goodwin
- Sealy Center on AgingUniversity of Texas Medical BranchGalvestonTexas
- Department of Internal MedicineUniversity of Texas Medical BranchGalvestonTexas
- Division of Rehabilitation SciencesUniversity of Texas Medical BranchGalvestonTexas
- Department of Preventive Medicine and Community HealthUniversity of Texas Medical BranchGalvestonTexas
| | - Shuang Li
- Sealy Center on AgingUniversity of Texas Medical BranchGalvestonTexas
| | - Addie Middleton
- Division of Physical TherapyMedical University of South CarolinaCharlestonSouth Carolina
| | - Kenneth Ottenbacher
- Sealy Center on AgingUniversity of Texas Medical BranchGalvestonTexas
- Division of Rehabilitation SciencesUniversity of Texas Medical BranchGalvestonTexas
| | - Yong‐Fang Kuo
- Sealy Center on AgingUniversity of Texas Medical BranchGalvestonTexas
- Department of Internal MedicineUniversity of Texas Medical BranchGalvestonTexas
- Department of Preventive Medicine and Community HealthUniversity of Texas Medical BranchGalvestonTexas
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