Associations between nursing home performance and hospital 30‐day readmissions for acute myocardial infarction, heart failure and pneumonia at the healthcare community level in the United States

Pandolfi, Michelle M.; Wang, Yun; Spenard, Ann; Johnson, Florence; Bonner, Alice; Ng, Beng Koon; Elwell, Timothy; Bakullari, Anila; Galusha, Deron; Leifheit-Limson, Erica C; Lichtman, Judith H.; Krumholz, Harlan M.

doi:10.1111/opn.12154

Cited by 12 publications

(22 citation statements)

References 25 publications

(60 reference statements)

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“…However, individuals with worse physical function, hence possibly more frail, are generally more likely to be discharged to a nursing home, and living at a nursing home may alter the risk for readmission in both directions compared to living in ordinary home depending on nursing-home performance, as pointed out in previous studies [38]. Differences in skill and competence levels between nursing homes have also been shown to have an impact [43]. It is worth noting the competing risk due to death; the mortality rates in the more frail and less independent individuals living in nursing homes are higher [38].…”

Section: Plos Onementioning

confidence: 85%

Readmission within three months after inpatient geriatric care—Incidence, diagnosis and associated factors in a Swedish cohort

et al. 2021

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Introduction Readmissions are very costly, in monetary terms but also for the individual patient’s safety and health. Only by understanding the reasons and drivers of readmissions, it is possible to ensure quality of care and improve the situation. The aim of this study was to assess inpatient readmissions during the first three months after discharge from geriatric inpatient care regarding main diagnosis and frequency of readmission. Furthermore, the aim was to analyze association between readmission and patient characteristics including demography and socioeconomics, morbidity, physical function, risk screening and care process respectively. Methods The study includes all individuals admitted for inpatient care at three geriatric departments operated by the Stockholm region during 2016. Readmission after discharge was studied within three different time intervals; readmission within 10 days after discharge, within 11–30 days and within 31–90 days, respectively. Main diagnosis at readmission was assessed. Results One fourth of the individuals discharged from inpatient geriatric care was readmitted during the first three months after discharge. The most common main diagnoses for readmission were heart failure, chronic obstructive pulmonary disease and pneumonia. Statistically significant risk factors for readmission included age, sex, number of diagnoses at discharge, and to some extent polypharmacy and destination of discharge. Conclusions Several clinical risk factors relating to physical performance and vulnerability were associated with risk of readmission. Socioeconomic information did not add to the predictability. To enable reductions in readmission rates, proactive monitoring of frail individuals afflicted with chronic conditions is necessary, and an integrated perspective including all stakeholders involved is crucial.

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Section: Plos Onementioning

confidence: 85%

Readmission within three months after inpatient geriatric care—Incidence, diagnosis and associated factors in a Swedish cohort

et al. 2021

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“…It is consistent with data from the Behavioral Risk Factor Surveillance System (BRFSS) studies that showed higher prevalence of MI at ages younger than 65 in the lagging states ( 31 ) potentially associated with higher prevalence of MI risk factors in the lagging states among younger adults ( 24 – 27 , 32 ). Finally, observed lower survival rates after MI diagnosis and lower remaining LE at age 65 among MI patients may be explained by earlier MI onset ( 31 ), lower rate of cardiac rehabilitation ( 33 ), worse nursing home performance ( 34 ), lower adherence to medication intake for arterial hypertension and cholesterol-lowering ( 35 ), and longer pre-hospital time to the percutaneous coronary intervention (PCI) centers ( 36 ) in the lagging states.…”

Section: Discussionmentioning

confidence: 99%

Epidemiology of Geographic Disparities of Myocardial Infarction Among Older Adults in the United States: Analysis of 2000–2017 Medicare Data

Akushevich

Yashkin

et al. 2021

Front. Cardiovasc. Med.

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Background: There are substantial geographic disparities in the life expectancy (LE) across the U.S. with myocardial infarction (MI) contributing significantly to the differences between the states with highest (leading) and lowest (lagging) LE. This study aimed to systematically investigate the epidemiology of geographic disparities in MI among older adults.Methods: Data on MI outcomes among adults aged 65+ were derived from the Center for Disease Control and Prevention-sponsored Wide-Ranging Online Data for Epidemiologic Research database and a 5% sample of Medicare Beneficiaries for 2000–2017. Death certificate-based mortality from MI as underlying/multiple cause of death (CBM-UCD/CBM-MCD), incidence-based mortality (IBM), incidence, prevalence, prevalence at age 65, and 1-, 3-, and 5-year survival, and remaining LE at age 65 were estimated and compared between the leading and lagging states. Cox model was used to investigate the effect of residence in the lagging states on MI incidence and survival.Results: Between 2000 and 2017, MI mortality was higher in the lagging than in the leading states (per 100,000, CBM-UCD: 236.7–583.7 vs. 128.2–357.6, CBM-MCD: 322.7–707.7 vs. 182.4–437.7, IBM: 1330.5–1518.9 vs. 1003.3–1197.0). Compared to the leading states, lagging states had higher MI incidence (1.1–2.0% vs. 0.9–1.8%), prevalence (10.2–13.1% vs. 8.3–11.9%), pre-existing prevalence (2.5–5.1% vs. 1.4–3.6%), and lower survival (70.4 vs. 77.2% for 1-year, 63.2 vs. 67.2% for 3-year, and 52.1 vs. 58.7% for 5-year), and lower remaining LE at age 65 among MI patients (years, 8.8–10.9 vs. 9.9–12.8). Cox model results showed that the lagging states had greater risk of MI incidence [Adjusted hazards ratio, AHR (95% Confidence Interval, CI): 1.18 (1.16, 1.19)] and death after MI diagnosis [1.22 (1.21, 1.24)]. Study results also showed alarming declines in survival and remaining LE at age 65 among MI patients.Conclusion: There are substantial geographic disparities in MI outcomes, with lagging states having higher MI mortality, incidence, and prevalence, lower survival and remaining LE at age 65. Disparities in MI mortality in a great extent could be due to between-the-state differences in MI incidence, prevalence at age 65 and survival. Observed declines in survival and remaining LE require an urgent analysis of contributing factors that must be addressed.

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“…However, most of the research have separated the three entities, and examined them at each level of the healthcare service 20–23. For example, factors affecting hospital readmissions have been explored within the realm of primary healthcare services (eg, nurse turnover, nurse staffing and performance and care quality)24–26 or secondary healthcare services (eg, staff responsiveness, length of stay and medication-related events) 27–29…”

Section: Introductionmentioning

confidence: 99%

Hospital physicians’ views on discharge and readmission processes: a qualitative study from Norway

et al. 2019

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ObjectivesTo explore hospital physicians’ views on readmission and discharge processes in the interface between hospitals and municipalities.DesignQualitative case study.SettingThe Norwegian healthcare system.ParticipantsFifteen hospital physicians (residents and consultants) from one hospital, involved in the treatment and discharge of patients.ResultsThe results of this study showed that patients were being discharged earlier, with more complex medical conditions, than they had been previously, and that discharges sometimes were perceived as premature. Insufficient capacity at the hospital resulted in pressure to discharge patients, but the primary healthcare service of the area was not always able to assume care of these patients. Communication between levels of the healthcare service was limited. The hospital stay summary was the most important, and sometimes only, form of communication between levels. The discharge process was described as complicated and was affected by healthcare personnel, by patients themselves and by aspects of the primary healthcare service. Early hospital discharges, poor communication between healthcare services and inadequacies in the discharge process were perceived to affect hospital readmissions.ConclusionThe results of this study provide a better understanding of hospital physicians’ views on the discharge and hospital readmission processes in the interface between the hospital and the primary healthcare service. The study also identifies discrepancies in governmental requirements, reform regulations and current practices in municipalities and hospitals.

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Associations between nursing home performance and hospital 30‐day readmissions for acute myocardial infarction, heart failure and pneumonia at the healthcare community level in the United States

Cited by 12 publications

References 25 publications

Readmission within three months after inpatient geriatric care—Incidence, diagnosis and associated factors in a Swedish cohort

Readmission within three months after inpatient geriatric care—Incidence, diagnosis and associated factors in a Swedish cohort

Epidemiology of Geographic Disparities of Myocardial Infarction Among Older Adults in the United States: Analysis of 2000–2017 Medicare Data

Hospital physicians’ views on discharge and readmission processes: a qualitative study from Norway

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