Exploring subjective quality-of-life indicators in long-term care facilities: a mixed-methods research protocol.

INTRODUCTION: Improving quality of life has become a priority in the long-term care (LTC) sector internationally. With development and implementation guidance, standardised quality-of-life monitoring tools based on valid, self-report surveys could be used more effectively to benefit LTC residents, families and organisations. This research will explore the potential for subjective quality-of-life indicators in the interRAI Self-Reported Quality of Life Survey for Long-Term Care Facilities (QoL-LTCF). METHODS AND ANALYSIS: Guided by the Medical Research Council Framework, this research will entail a (1) modified Delphi study, (2) feasibility study and (3) realist synthesis. In study 1, we will evaluate the importance of statements and scales in the QoL-LTCF by administering Delphi surveys and focus groups to purposively recruited resident and family advisors, researchers, and LTC clinicians, staff, and leadership from international quality improvement organisations. In study 2, we will critically examine the feasibility and implications of risk-adjusting subjective quality-of-life indicators. Specifically, we will collect expert stakeholder perspectives with interviews and apply a risk-adjustment methodology to QoL-LTCF data. In study 3, we will iteratively review and synthesise literature, and consult with expert stakeholders to explore the implementation of quality-of-life indicators. ETHICS AND DISSEMINATION: This study has received approval through a University of Waterloo Research Ethics Board and the Social and Societal Ethics Committee of KU Leuven. We will disseminate our findings in conferences, journal article publications and presentations for a variety of stakeholders.

Profiling the medical, functional, cognitive, and psychosocial care needs of adults assessed for home care in Ontario, Canada: The case for long-term 'life care' at home.

Calls to leverage routinely collected data to inform health system improvements have been made. Misalignment between home care services and client needs can result in poor client, caregiver, and system outcomes. To inform development of an integrated model of community-based home care, grounded in a holistic definition of health, comprehensive clinical profiles were created using Ontario, Canada home care assessment data. Retrospective, cross-sectional analyses of 2017-2018 Resident Assessment Instrument Home Care (RAI-HC) assessments (n = 162,523) were completed to group home care clients by service needs and generate comprehensive profiles of each group's dominant medical, functional, cognitive, and psychosocial care needs. Six unique groups were identified, with care profiles representing home care clients living with Geriatric Syndromes, Medical Complexity, Cognitive Impairment and Behaviours, Caregiver Distress and Social Frailty. Depending on group membership, between 51% and 81% of clients had identified care needs spanning four or more Positive Health dimensions, demonstrating both the heterogeneity and complexity of clients served by home care. Comprehensive clinical profiles, developed from routinely collected assessment data, support a future-focused, evidence-informed, and community-engaged approach to research and practice in integrated home-based health and social care.

Functional Decline in Long-Term Care Homes in the First Wave of the COVID-19 Pandemic: A Population-based Longitudinal Study in Five Canadian Provinces.

OBJECTIVE: We aimed to examine whether functional decline accelerated during the first wave of the COVID-19 pandemic (March to June 2020) for persons in long-term care facilities (LTCs) in Canada compared with the pre-pandemic period. DESIGN: We conducted a population-based longitudinal study of persons receiving care in LTC homes in 5 Canadian provinces before and during the COVID-19 pandemic. SETTING AND PARTICIPANTS: Residents in 1326 LTC homes within the Canadian provinces of Alberta, British Columbia, Manitoba, Newfoundland & Labrador, and Ontario between January 31, 2019, and June 30, 2020, with activities of daily living Hierarchy scale less than 6 and so, who still have potential for decline (6 being the worst of the 0-6 scale). METHODS: We fit a generalized estimating equation model with adjustment for repeated measures to obtain the adjusted odds of functional decline between COVID period exposed and unexposed pre-pandemic residents. RESULTS: LTC residents experienced slightly higher rates of functional decline during the first wave of the COVD-19 pandemic compared with the pre-pandemic period (23.3% vs 22.3%; P < .0001). The adjusted odds of functional decline were slightly greater during the pandemic (odds ratio [OR], 1.17; 95% CI, 1.15-1.20). Likewise, residents receiving care in large homes (OR, 1.20; 95% CI, 1.17-1.24) and urban-located LTC homes (OR, 1.20; 95% CI, 1.17-1.23), were more likely to experience functional decline during the COVID-19 pandemic. The odds of functional decline were also only significantly higher during the pandemic for LTC home residents in British Columbia (OR, 1.17; 95% CI, 1.11-1.23) and Ontario (OR, 1.25; 95% CI, 1.21-1.29). CONCLUSIONS AND IMPLICATIONS: This study provides evidence that the odds of experiencing functional decline were somewhat greater during the first wave of the COVID-19 pandemic. It highlights the need to maintain physical activity and improve nutrition among older adults during periods of stress. The information would be helpful to health administrators and decision-makers seeking to understand how the COVID-19 pandemic and associated public health measures affected LTC residents' health outcomes.

Rates of Hospital-Based Care among Older Adults in the Community and Residential Care Facilities: A Repeated Cross-Sectional Study.

OBJECTIVE: We examine annual rates of emergency department (ED) visits, hospital admissions, and alternate levels of care (ALC) days (ie, the number of days that an older adult remained in hospital when they could not be safely discharged to an appropriate setting in their community) among older adults. DESIGN: Repeated cross-sectional study. SETTING AND PARTICIPANTS: Linked, individual-level health system administrative data on community-dwelling persons, home care recipients, residents of assisted living facilities, and residents of nursing homes aged 65 years and older in Ontario, Canada, from January 1, 2013, to December 31, 2019. METHODS: We calculated rates of ED visits, hospital admissions, and ALC days per 1000 individuals per older adult population per year. We used a generalized linear model with a gaussian distribution, log link, and year fixed effects to obtain rate ratios. RESULTS: There were 1,655,656 older adults in the community, 237,574 home care recipients, 42,600 older adults in assisted living facilities, and 94,055 older adults in nursing homes in 2013; there were 2,129,690 older adults in the community, 281,028 home care recipients, 56,975 older adults in assisted living facilities, and 95,925 older adults in nursing homes in 2019. Residents of assisted living facilities had the highest rates of ED visits (1260.692019 vs 1174.912013), hospital admissions (482.632019 vs 480.192013), and ALC days (1905.572019 vs 1443.032013) per 1000 individuals. Residents of assisted living facilities also had significantly higher rates of ED visits [rate ratio (RR) 3.30, 95% CI 3.20, 3.41), hospital admissions (RR 6.24, 95% CI 6.01, 6.47), and ALC days (RR 25.68, 95% CI 23.27, 28.35) relative to community-dwelling older adults. CONCLUSIONS AND IMPLICATIONS: The disproportionate use of ED visits, hospital admissions, and ALC days among residents of assisted living facilities may be attributed to the characteristics of the population and fragmented licensing and regulation of the sector, including variable models of care. The implementation of interdisciplinary, after-hours, team-based approaches to home and primary care in assisted living facilities may reduce the potentially avoidable use of ED visits, hospital admissions, and ALC days among this population and optimize resource allocation in health care systems.