Short-stay admissions and lower staffing associated with larger COVID-19 outbreaks in Maryland nursing homes

  1. T. Joseph Mattingly
  2. Alison Trinkoff
  3. Alison D Lydecker
  4. Justin J. Kim
  5. Jung Min Yoon
  6. Mary-Claire Roghmann

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Abstract

Objectives

Identify facility factors associated with a larger COVID-19 outbreak among residents in Maryland nursing homes (NHs).

Design

Observational

Setting and Participants

All Maryland NHs.

Methods

Resident COVID-19 cases were collected for each Maryland NH from January 1, 2020 through July 1, 2020. Cumulative COVID-19 incidence through July 1, 2020 was collected for each county and Baltimore City. Facility characteristics for each Maryland NH were collected from time periods prior to January 1, 2020. NH outbreaks were defined as larger when total resident COVID-19 cases exceeded 10% of licensed beds. Descriptive and multivariable analyses were conducted to assess the strongest predictors for the primary outcome of larger COVID-19 outbreak.

Results

NHs located in counties with high cumulative incidence of COVID-19 were more likely to have larger outbreaks (OR 4.5, 95% CI 2.3-8.7, p<0.01). NHs with at least 100 beds were more likely to have larger outbreaks, especially among facilities with >140 licensed beds (100-140 beds vs <100 beds: OR 1.9, 95% CI 0.9-4.1, p=0.09; >140 beds vs <100 beds: OR 2.9, 95% CI 1.3-6.1, p<0.01). NHs with more short-stay residents (OR 2.2, 95% CI 1.1-4.8, p=0.04) or fewer Certified Nursing Assistant hours daily (OR 2.6, 95% CI 1.3-5.3, p<0.01) also were more likely to have larger outbreaks. Resident race and gender were not significant predictors of larger outbreaks after adjustment for other factors.

Conclusions

Large NHs with lower staffing levels and many short-stay residents in counties with high COVID-19 incidence were at increased risk for COVID-19 outbreaks. Understanding the characteristics of nursing homes associated with larger outbreaks can help us prepare for the next pandemic.

Brief summary

Maryland nursing homes in counties with a high COVID-19 incidence, more licensed beds, a higher proportion of short-stay residents, or lower CNA staffing hours were more likely to have a larger outbreak early in the pandemic.

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  1. ScreenIT

    SciScore for 10.1101/2021.03.03.21252846: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    16 Then a quarterly average HPRD was calculated for certified nurse assistants (CNAs): nurse aides and certified medication aides.
    HPRD
    suggested: None
    All analyses were performed with Stata 15.1 (Stata Corp., College Station, TX) and SAS 9.4 (SAS Institute, Inc. Cary, NC).
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.03.03.21252846v1 on medRxiv