Risk Stratification of Nursing Homes to Plan COVID-19 Responses: A Case Study of Victoria, Australia.

OBJECTIVE: Emergency management responses to coronavirus disease 2019 (COVID-19) in nursing homes lacked preparation and nuance; moving forward, responses must recognize nursing homes are not generic organizations or services, and individually appreciate each's unique nature, strengths, and limitations. The objective of this study was to describe an approach to stratifying nursing homes according to risk for COVID-19 outbreak. METHODS: Population-based cross-sectional study of all accredited nursing homes in Victoria (n = 766), accommodating 48,824 permanent residents. We examined each home's facility structure, governance history, socio-economic status, proximity to high-risk industry, and proximity and size of local acute public hospital, stratified by location, size, and organizational structure. RESULTS: Privately owned nursing homes tend to be larger and metropolitan-based, and publicly owned homes regionally based and smaller in size. The details reveal additional nuance, eg, privately owned metropolitan-based medium- to large-sized facilities tended to have more regulatory noncompliance, no board of governance, and fewer Chief Executive Officers with clinical background. In contrast, the smaller, publicly owned, remote facilities perform better on those same metrics. CONCLUSIONS: Nursing homes should not be regarded as generic entities, and there is significant underlying heterogeneity. Stratification of nursing homes according to risk level is a viable approach to informing more nuanced policy direction and resource allocation for emergency management responses.

A Proactive Nursing Home Risk Stratification Model for Disaster Response: Lessons Learned from COVID-19 to Optimize Resource Allocation.

A coordinated emergency management response to disaster management in nursing homes is desperately needed globally. During the most recent COVID-19 pandemic, aside from a few exemplary countries, most countries have struggled to protect their nursing home populations. Timely and appropriate allocation of resources to nursing homes during disaster response is a challenging yet crucial task to prevent morbidity and mortality of residents. The responsibility for the management of nursing homes during the pandemic was multifaceted, and responsibilities lay at the national, jurisdictional, and regional levels. Success in managing COVID-19 in nursing homes required all these levels to be aligned and supportive, ideally through management by an emergency response leadership team. However, globally there is a paucity of effective management strategies. This article uses the example of the COVID-19 pandemic to propose a risk stratification system to ensure timely and appropriate allocation of resources to nursing homes during disaster preparation and management. Nursing homes should be risk-stratified according to 4 domains: risk of intrusion, capability for outbreak containment, failure in organizational capability, and failure in the availability of community and health care supports. Risk stratification should also consider factors such as current levels of community transmission, if applicable, and geographic location of nursing homes and services. Early identification of nursing homes at risk for infectious disease, or disasters, and targeted allocation of resources might help reduce the number of outbreaks, lower the mortality, and preserve community supports such as acute hospital services. The next step is to debate this concept to validate the selected variables and then develop and pilot test a risk stratification tool for use.

Characteristics of nursing homes associated with COVID-19 outbreaks and mortality among residents in Victoria, Australia.

OBJECTIVE: To determine nursing home characteristics associated with COVID-19 outbreak, outbreak size and mortality, during the second wave in Victoria, Australia. METHOD: Population-based cross-sectional study of all nursing homes in Victoria between 7 July and 13 November 2020. RESULTS: There were one or more resident cases of COVID-19 in 9.7% of nursing homes (74/766). COVID-19 intrusion was more likely in larger metropolitan facilities, privately owned by large chains, with a past history of regulatory non-compliance, located close to high-risk industry. Larger outbreaks were associated with homes in metropolitan areas, accommodating 91 or more residents, with shared rooms, owned by private providers operating many (11 or more) facilities. The highest case-fatality rates were observed in homes owned by not-for-profit providers operating many facilities, located close to high-risk industry. CONCLUSION: Stratifying nursing homes according to characteristics associated with morbidity and mortality can inform risk management, prioritising emergency responses and optimising future nursing home operations.

Developing a clinical screening tool for identifying COVID-19 infection in older people dwelling in residential aged care services.

OBJECTIVE: To develop and conduct preliminary feasibility testing of a clinical screening instrument for early identification of COVID-19 infection in older people residing in residential aged care services (RACS). METHODS: A qualitative study was conducted using a multi-modal approach involving examination of existing literature and national guidelines for COVID-19 clinical screening, formulation of a discussion document with peer review and feasibility testing of a prototype screening tool. RESULTS: Existing COVID-19 clinical screening tools do not consider age-related impacts on clinical presentation. The qualitative analysis identified the important clinical elements to include were a lower threshold for temperature, occurrence of a recent fall and change in functional status. The new elements also had to be simple and feasible to implement. Overall feedback was positive with all participants recommending the use of the new tool. CONCLUSION: A new screening tool for RACS residents was developed addressing the pathophysiological changes with ageing and atypical features of COVID-19 infection.