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Nursing Home Staff Networks and COVID-19

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  • M. Keith Chen
  • Judith A. Chevalier
  • Elisa F. Long

Abstract

Nursing homes and other long-term care facilities account for a disproportionate share of COVID-19 cases and fatalities worldwide. Outbreaks in U.S. nursing homes have persisted despite nationwide visitor restrictions beginning in mid-March. An early report issued by the Centers for Disease Control and Prevention identified staff members working in multiple nursing homes as a likely source of spread from the Life Care Center in Kirkland, Washington to other skilled nursing facilities. The full extent of staff connections between nursing homes—and the role these connections serve in spreading a highly contagious respiratory infection—is currently unknown given the lack of centralized data on cross-facility employment. We perform the first large-scale analysis of nursing home connections via shared staff and contractors using device-level geolocation data from 50 million smartphones, and find that 5.1 percent of smartphone users who visit a nursing home for at least one hour also visit another facility during our 11-week study period—even after visitor restrictions were imposed. We construct network measures of connectedness and estimate that nursing homes, on average, share connections with 7 other facilities. Controlling for demographic and other factors, a home’s staff-network connections and its centrality within the greater network strongly predict COVID-19 cases. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, consistent with recent research. Multivariate regressions comparing demographically and geographically similar nursing homes suggest that 49 percent of COVID cases among nursing home residents are attributable to staff movement between facilities.

Suggested Citation

  • M. Keith Chen & Judith A. Chevalier & Elisa F. Long, 2020. "Nursing Home Staff Networks and COVID-19," NBER Working Papers 27608, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:27608
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    References listed on IDEAS

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    1. Susan Feng Lu & Lauren Xiaoyuan Lu, 2017. "Do Mandatory Overtime Laws Improve Quality? Staffing Decisions and Operational Flexibility of Nursing Homes," Management Science, INFORMS, vol. 63(11), pages 3566-3585, November.
    2. Vincent W. Slaugh & Alan A. Scheller‐Wolf & Sridhar R. Tayur, 2018. "Consistent Staffing for Long‐Term Care through On‐Call Pools," Production and Operations Management, Production and Operations Management Society, vol. 27(12), pages 2144-2161, December.
    3. M. Keith Chen & Ryne Rohla, 2017. "The Effect of Partisanship and Political Advertising on Close Family Ties," Papers 1711.10602, arXiv.org, revised Jun 2018.
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    1. Abe Dunn & Joshua D Gottlieb & Adam Hale Shapiro & Daniel J Sonnenstuhl & Pietro Tebaldi, 2024. "A Denial a Day Keeps the Doctor Away," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 139(1), pages 187-233.
    2. Antoci, Angelo & Sabatini, Fabio & Sacco, Pier Luigi & Sodini, Mauro, 2022. "Experts vs. policymakers in the COVID-19 policy response," Journal of Economic Behavior & Organization, Elsevier, vol. 201(C), pages 22-39.
    3. Cronin, Christopher J. & Evans, William N., 2022. "Nursing home quality, COVID-19 deaths, and excess mortality," Journal of Health Economics, Elsevier, vol. 82(C).
    4. Xavier Flawinne & Mathieu Lefebvre & Sergio Perelman & Pierre Pestieau & Jérôme Schoenmaeckers, 2023. "Nursing homes and mortality in Europe: Uncertain causality," Health Economics, John Wiley & Sons, Ltd., vol. 32(1), pages 134-154, January.
    5. Pongou, Roland & Sidie, Ghislain Junior & Tchuente, Guy & Tondji, Jean-Baptiste, 2022. "Profits, Pandemics, and Lockdown Effectiveness in Nursing Home Networks," National Institute of Economic and Social Research (NIESR) Discussion Papers 540, National Institute of Economic and Social Research.
    6. Drost, Alyssa & Alam, M Injamam & Boamah, Sheila & Kralj, Boris & Costa, Andrew & Sweetman, Arthur, 2023. "Multiple jobholding and part-time work among nurses in long-term care homes compared to other healthcare sectors: Evidence from Ontario," Health Policy, Elsevier, vol. 130(C).
    7. Casey B. Mulligan, 2021. "The Backward Art of Slowing the Spread? Congregation Efficiencies during COVID-19," NBER Working Papers 28737, National Bureau of Economic Research, Inc.
    8. Coven, Joshua & Gupta, Arpit & Yao, Iris, 2023. "JUE Insight: Urban flight seeded the COVID-19 pandemic across the United States," Journal of Urban Economics, Elsevier, vol. 133(C).
    9. Nathan M. Stall & Kevin A. Brown & Antonina Maltsev & Aaron Jones & Andrew P. Costa & Vanessa Allen & Adalsteinn D. Brown & Gerald A. Evans & David N. Fisman & Jennie Johnstone & Peter Jüni & Kamil Ma, 2021. "COVID‐19 and Ontario's Long‐Term Care Homes," Journal of Elder Policy, John Wiley & Sons, vol. 1(3), pages 65-110, September.
    10. Matthew Spiegel & Heather Tookes, 2021. "Business Restrictions and COVID-19 Fatalities [The immediate effect of COVID-19 policies on social distancing behavior in the United States]," The Review of Financial Studies, Society for Financial Studies, vol. 34(11), pages 5266-5308.
    11. Gallo, Edoardo & Barak, Darija & Langtry, Alastair, 2023. "Social distancing in networks: A web-based interactive experiment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 107(C).
    12. Paul L. Joskow, 2022. "From Scarcity to Abundance: Government and Private Initiatives to Manage the Allocation of N95 Masks in the U.S. During the COVID-19 Pandemic," NBER Working Papers 29876, National Bureau of Economic Research, Inc.
    13. Theresa Kuchler & Johannes Stroebel, 2022. "Social Interactions, Resilience, and Access to Economic Opportunity: A Research Agenda for the Field of Computational Social Science," CESifo Working Paper Series 9606, CESifo.
    14. Almagro, Milena & Coven, Joshua & Gupta, Arpit & Orane-Hutchinson, Angelo, 2023. "Disparities in COVID-19 risk exposure: Evidence from geolocation data," Regional Science and Urban Economics, Elsevier, vol. 102(C).
    15. Christopher Avery & William Bossert & Adam Clark & Glenn Ellison & Sara Fisher Ellison, 2020. "An Economist's Guide to Epidemiology Models of Infectious Disease," Journal of Economic Perspectives, American Economic Association, vol. 34(4), pages 79-104, Fall.
    16. Pongou, Roland & Tchuente, Guy & Tondji, Jean-Baptiste, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," GLO Discussion Paper Series 957, Global Labor Organization (GLO).
    17. A. James O'Malley & Thomas A. Bubolz & Jonathan S. Skinner, 2021. "The Diffusion of Health Care Fraud: A Network Analysis," NBER Working Papers 28560, National Bureau of Economic Research, Inc.
    18. Taylor A Begley & Daniel Weagley, 2023. "Firm Finances and the Spread of COVID-19: Evidence from Nursing Homes," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 12(1), pages 1-35.
    19. Eric Budish, 2020. "Maximize Utility subject to R≤1: A Simple Price-Theory Approach to Covid-19 Lockdown and Reopening Policy," NBER Working Papers 28093, National Bureau of Economic Research, Inc.
    20. Roland Pongou & Guy Tchuente & Jean-Baptiste Tondji, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," Papers 2110.10230, arXiv.org.

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    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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