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Background The relative contributions of long-term care (LTC) resident frailty and home-level characteristics on COVID-19 mortality has not been well studied. We examined the association between resident frailty and home-level characteristics with 30-day COVID-19 mortality before and after the availability of SARS-CoV-2 vaccination in LTC. Methods We conducted a population-based retrospective cohort study of LTC residents with confirmed SARS-CoV-2 infection in Ontario, Canada. We used multi-level multivariable logistic regression to examine associations between 30-day COVID-19 mortality, the Hubbard Frailty Index (FI), and resident and home-level characteristics. We compared explanatory models before and after vaccine availability. Results There were 11,179 and 3,655 COVID-19 cases in the pre- and post-vaccine period, respectively. The 30-day COVID-19 mortality was 25.9 and 20.0% during the same periods. The median odds ratios for 30-day COVID-19 mortality between LTC homes were 1.50 (95% credible interval [CrI]: 1.41–1.65) and 1.62 (95% CrI: 1.46–1.96), respectively. In the pre-vaccine period, 30-day COVID-19 mortality was higher for males and those of greater age. For every 0.1 increase in the Hubbard FI, the odds of death were 1.49 (95% CI: 1.42–1.56) times higher. The association between frailty and mortality remained consistent in the post-vaccine period, but sex and age were partly attenuated. Despite the substantial home-level variation, no home-level characteristic examined was significantly associated with 30-day COVID-19 mortality during either period. Interpretation Frailty is consistently associated with COVID-19 mortality before and after the availability of SARS-CoV-2 vaccination. Home-level characteristics previously attributed to COVID-19 outcomes do not explain significant home-to-home variation in COVID-19 mortality. [ABSTRACT FROM AUTHOR]

Background: While assisted living (AL) and nursing home (NHs) residents in share vulnerabilities, AL provides fewer staffing resources and services. Research has largely neglected AL, especially during the COVID‐19 pandemic. Our study compared trends of practice‐sensitive, risk‐adjusted quality indicators between AL and NHs, and changes in these trends after the start of the pandemic. Methods: This repeated cross‐sectional study used population‐based resident data in Alberta, Canada. Using Resident Assessment Instrument data (01/2017–12/2021), we created quarterly cohorts, using each resident's latest assessment in each quarter. We applied validated inclusion/exclusion criteria and risk‐adjustments to create nine quality indicators and their 95% confidence intervals (CIs): potentially inappropriate antipsychotic use, pain, depressive symptoms, total dependency in late‐loss activities of daily living, physical restraint use, pressure ulcers, delirium, weight loss, urinary tract infections. Run charts compared quality indicators between AL and NHs over time and segmented regressions assessed whether these trends changed after the start of the pandemic. Results: Quarterly samples included 2015–2710 AL residents and 12,881–13,807 NH residents. Antipsychotic use (21%–26%), pain (20%–24%), and depressive symptoms (17%–25%) were most common in AL. In NHs, they were physical dependency (33%–36%), depressive symptoms (26%–32%), and antipsychotic use (17%–22%). Antipsychotic use and pain were consistently higher in AL. Depressive symptoms, physical dependency, physical restraint use, delirium, weight loss were consistently lower in AL. The most notable segmented regression findings were an increase in antipsychotic use during the pandemic in both settings (AL: change in slope = 0.6% [95% CI: 0.1%–1.0%], p = 0.0140; NHs: change in slope = 0.4% [95% CI: 0.3%–0.5%], p < 0.0001), and an increase in physical dependency in AL only (change in slope = 0.5% [95% CI: 0.1%–0.8%], p = 0.0222). Conclusions: QIs differed significantly between AL and NHs before and during the pandemic. Any changes implemented to address deficiencies in either setting need to account for these differences and require monitoring to assess their impact. [ABSTRACT FROM AUTHOR]

Background: Because there are no standardized reporting systems specific to residents of retirement homes in North America, little is known about the health of this distinct population of older adults. We evaluated rates of health services use by residents of retirement homes relative to those of residents of long-term care homes and other populations of older adults. Methods: We conducted a retrospective cohort study using population health administrative data from 2018 on adults 65 years or older in Ontario. We matched the postal codes of individuals to those of licensed retirement homes to identify residents of retirement homes. Outcomes included rates of hospital-based care and physician visits. Results: We identified 54 733 residents of 757 retirement homes (mean age 86.7 years, 69.0% female) and 2 354 385 residents of other settings. Compared to residents of long-term care homes, residents of retirement homes had significantly higher rates per 1000 person months of emergency department visits (10.62 v. 4.48, adjusted relative rate [RR] 2.61, 95% confidence interval [CI] 2.55 to 2.67), hospital admissions (5.42 v. 2.08, adjusted RR 2.77, 95% CI 2.71 to 2.82), alternate level of care (ALC) days (6.01 v. 2.96, adjusted RR 1.51, 95% CI 1.48 to 1.54), and specialist physician visits (6.27 v. 3.21, adjusted RR 1.64, 95% CI 1.61 to 1.68), but a significantly lower rate of primary care visits (16.71 v. 108.47, adjusted RR 0.13, 95% CI 0.13 to 0.14). Interpretation: Residents of retirement homes are a distinct population with higher rates of hospital-based care. Our findings can help to inform policy debates about the need for more coordinated primary and supportive health care in privately operated congregate care homes. [ABSTRACT FROM AUTHOR]

Objective: The main objective was to develop a decision-support tool to assess the risk of caregiver burden, the Caregiver Risk Evaluation (CaRE) algorithm. Methods: Home care clients were assessed using the Resident Assessment Instrument for Home Care (RAI-HC). Their caregiver completed the 12-item Zarit Burden Interview (ZBI), the main dependent measure, which was linked to the RAI-HC. Results: In the sample (n = 344), 48% were aged 85+ years and 61.6% were female. The algorithm can be collapsed into four categories (low, moderate, high, and very high risk). Relative to the low-risk group, clients in the very high-risk group had an odds ratio of 5.16 (95% confidence interval: [2.05, 12.9]) for long-term care admission, after adjusting for client age, sex, and regional health authority. Discussion: The CaRE algorithm represents a new tool to be used by home care clinicians as they proactively plan for the needs of clients and their caregivers. [ABSTRACT FROM AUTHOR]

Abstract Background Acute hospital discharge delays are a pressing concern for many health care administrators. In Canada, a delayed discharge is defined by the alternate level of care (ALC) construct and has been the target of many provincial health care strategies. Little is known on the patient characteristics that influence acute ALC length of stay. This study examines which characteristics drive acute ALC length of stay for those awaiting nursing home admission. Methods Population-level administrative and assessment data were used to examine 17,111 acute hospital admissions designated as alternate level of care (ALC) from a large Canadian health region. Case level hospital records were linked to home care administrative and assessment records to identify and characterize those ALC patients that account for the greatest proportion of acute hospital ALC days. Results ALC patients waiting for nursing home admission accounted for 41.5% of acute hospital ALC bed days while only accounting for 8.8% of acute hospital ALC patients. Characteristics that were significantly associated with greater ALC lengths of stay were morbid obesity (27 day mean deviation, 99% CI = ±14.6), psychiatric diagnosis (13 day mean deviation, 99% CI = ±6.2), abusive behaviours (12 day mean deviation, 99% CI = ±10.7), and stroke (7 day mean deviation, 99% CI = ±5.0). Overall, persons with morbid obesity, a psychiatric diagnosis, abusive behaviours, or stroke accounted for 4.3% of all ALC patients and 23% of all acute hospital ALC days between April 1st 2009 and April 1st, 2011. ALC patients with the identified characteristics had unique clinical profiles. Conclusions A small number of patients with non-medical days waiting for nursing home admission contribute to a substantial proportion of total non-medical days in acute hospitals. Increases in nursing home capacity or changes to existing funding arrangements should target the sub-populations identified in this investigation to maximize effectiveness. Specifically, incentives should be introduced to encourage nursing homes to accept acute patients with the least prospect for community-based living, while acute patients with the greatest prospect for community-based living are discharged to transitional care or directly to community-based care.

Abstract Background Although numerous risk factors for adverse outcomes for older persons after an acute hospital stay have been identified, a decision making tool combining all available information in a clinically meaningful way would be helpful for daily hospital practice. The purpose of this study was to evaluate the ability of the Method for Assigning Priority Levels for Acute Care (MAPLe-AC) to predict adverse outcomes in acute care for older people and to assess its usability as a decision making tool for discharge planning. Methods Data from a prospective multicenter study in five Nordic acute care hospitals with information from admission to a one year follow-up of older acute care patients were compared with a prospective study of acute care patients from admission to discharge in eight hospitals in Canada. The interRAI Acute Care assessment instrument (v1.1) was used for data collection. Data were collected during the first 24 hours in hospital, including pre-morbid and admission information, and at day 7 or at discharge, whichever came first. Based on this information a crosswalk was developed from the original MAPLe algorithm for home care settings to acute care (MAPLe-AC). The sample included persons 75 years or older who were admitted to acute internal medical services in one hospital in each of the five Nordic countries (n = 763) or to acute hospital care either internal medical or combined medical-surgical services in eight hospitals in Ontario, Canada (n = 393). The outcome measures considered were discharge to home, discharge to institution or death. Outcomes in a 1-year follow-up in the Nordic hospitals were: living at home, living in an institution or death, and survival. Logistic regression with ROC curves and Cox regression analyses were used in the analyses. Results Low and mild priority levels of MAPLe-AC predicted discharge home and high and very high priority levels predicted adverse outcome at discharge both in the Nordic and Canadian data sets, and one-year outcomes in the Nordic data set. The predictive accuracy (AUC's) of MAPLe-AC's was higher for discharge outcome than one year outcome, and for discharge home in Canadian hospitals but for adverse outcome in Nordic hospitals. High and very high priority levels in MAPLe-AC were also predictive of days to death adjusted for diagnoses in survival models. Conclusion MAPLe-AC is a valid algorithm based on risk factors that predict outcomes of acute hospital care. It could be a helpful tool for early discharge planning although further testing for active use in clinical practice is still needed.

Abstract Background This manuscript describes a method for adjustment of nursing home quality indicators (QIs) defined using the Center for Medicaid & Medicare Services (CMS) nursing home resident assessment system, the Minimum Data Set (MDS). QIs are intended to characterize quality of care delivered in a facility. Threats to the validity of the measurement of presumed quality of care include baseline resident health and functional status, pattern of comorbidities, and facility case mix. The goal of obtaining a valid facility-level estimate of true quality of care should include adjustment for resident- and facility-level sources of variability. Methods We present a practical and efficient method to achieve risk adjustment using restriction and indirect and direct standardization. We present information on validity by comparing QIs estimated with the new algorithm to one currently used by CMS. Results More than half of the new QIs achieved a "Moderate" validation level. Conclusions Given the comprehensive approach and the positive findings to date, research using the new quality indicators is warranted to provide further evidence of their validity and utility and to encourage their use in quality improvement activities.