The Metrics Matter: Improving Comparisons of COVID-19 Outbreaks in Nursing Homes.

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2021-05

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Abstract

Objectives

In the United States, nursing facility residents comprise fewer than 1% of the population but more than 40% of deaths due to Coronavirus Disease 2019 (COVID-19). Mitigating the enormous risk of COVID-19 to nursing home residents requires adequate data. The widely used Centers for Medicare & Medicaid Services (CMS) COVID-19 Nursing Home Dataset contains 2 derived statistics: Total Resident Confirmed COVID-19 Cases per 1000 Residents and Total Resident COVID-19 Deaths per 1000 Residents. These metrics provide a misleading picture, as facilities report cumulative counts of cases and deaths over different time periods but use a point-in-time measure as proxy for number of residents (number of occupied beds in a week), resulting in inflated statistics. We propose an alternative statistic to better illustrate the burden of COVID-19 cases and deaths across nursing facilities.

Design

Retrospective cohort study.

Setting and participants

Using the CMS Nursing Home Compare and COVID-19 Nursing Home Datasets, we examined facilities with star ratings and COVID-19 data passing quality assurance checks for each reporting period from May 31 to August 16, 2020 (n = 11,115).

Methods

We derived an alternative measure of the number of COVID-19 cases per 1000 residents using the net change in weekly census. For each measure, we compared predicted number of cases/deaths by overall star rating using negative binomial regression with constant dispersion, controlling for county-level cases per capita and nursing home characteristics.

Results

The average number of cases per 1000 estimated residents using our method is lower compared with the metric using occupied beds as proxy for number of residents (44.8 compared with 66.6). We find similar results when examining number of COVID-19 deaths per 1000 residents.

Conclusions and implications

Future research should estimate the number of residents served in nursing facilities when comparing COVID-19 cases/deaths in nursing facilities. Identifying appropriate metrics for facility-level comparisons is critical to protecting nursing home residents as the pandemic continues.

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Published Version (Please cite this version)

10.1016/j.jamda.2021.03.001

Publication Info

Miller, Katherine EM, Rebecca J Gorges, R Tamara Konetzka and Courtney H Van Houtven (2021). The Metrics Matter: Improving Comparisons of COVID-19 Outbreaks in Nursing Homes. Journal of the American Medical Directors Association, 22(5). pp. 955–959.e3. 10.1016/j.jamda.2021.03.001 Retrieved from https://hdl.handle.net/10161/26133.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Van Houtven

Courtney Harold Van Houtven

Professor in Population Health Sciences

Dr. Courtney Van Houtven is a Professor in The Department of Population Health Science, Duke University School of Medicine and Duke-Margolis Center for Health Policy. She is also a Research Career Scientist in The Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT), Durham Veterans Affairs Health Care System. Dr. Van Houtven’s aging and economics research interests encompass long-term care financing, intra-household decision-making, unpaid family and friend care, and home- and community-based services. She examines how family caregiving affects health care utilization, expenditures, health and work outcomes of care recipients and caregivers. She is also interested in understanding how best to support family caregivers to optimize caregiver and care recipient outcomes.

Dr. Van Houtven  is co-PI on the QUERI Program Project, “Optimizing Function and Independence”, in which her caregiver skills training program developed as an RCT in VA, now called Caregivers FIRST, has been implemented at 125 VA sites nationally. The team will evaluate how intensification of an implementation strategy changes adoption. She directs the VA-CARES Evaluation Center, which evaluates the VA’s Caregiver Support Program. She leads a mixed methods R01 study as PI from the National Institute on Aging that will assess the value of "home time" for persons living with dementia and their caregivers (RF1 AG072364).


Areas of expertise: Health Services Research and Health Economics


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