Evidence map›Paper›PMID 40938301›Full record

ArticleJournal of the American Geriatrics Society2025

Comparing Disaster-Related Surge Staffing Practices Across Rural and Non-Rural Nursing Homes.

Natalia Festa, Kelsey Alexovitz, Kendra Davis-Plourde, Richard Marottoli, Andrew B Cohen, David Dosa, Terry Fulmer, Thomas M Gill

Abstract readComparative Study
In one paragraph

Article in Journal of the American Geriatrics Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Natalia FestaDepartment of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.ORCID 0000-0003-4487-6832
Kelsey AlexovitzDepartment of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Kendra Davis-PlourdeDepartment of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA.ORCID 0000-0001-6654-0710
Richard MarottoliDepartment of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Andrew B CohenDepartment of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.ORCID 0000-0001-9161-8436
David DosaUniversity of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.
Terry FulmerThe John A. Hartford Foundation, New York, New York, USA.
Thomas M GillDepartment of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA.ORCID 0000-0002-6450-0368

Funding

Yale Study Support Suite (YES3): Dashboard and Web Portal Software Supporting Research Workflow through integrated, customizable REDCap External ModulesP30AG021342 · NIA · YALE UNIVERSITY · PI Albert C Shaw · 2002 to 2026
$37.9M
Yale Training Program in Geriatric Clinical Epidemiology and Aging-Related ResearchT32AG019134 · NIA · YALE UNIVERSITY · PI Terri R. Fried · 2001 to 2026
$7.5M
Investigating Nursing Home Emergency Preparedness for Environmental and Climatological Determinants of Resident HealthR03AG088893 · NIA · YALE UNIVERSITY · PI FESTA, NATALIA · 2024 to 2024
$335k
Claude D. Pepper Older Adults Independence Center P30AG021342HRSA HHS U1QHP28745NIA NIH HHS L70 AG089284NIA NIH HHS P30 AG021342NIA NIH HHS R03 AG088893NIA NIH HHS R03AG088893NIA NIH HHS T32 AG019134Patrick and Catherine Weldon Donaghue Medical Research Foundation
6 · The paper itself

Abstract

backgroundClarifying whether rural and non-rural nursing homes implement different disaster-related staffing approaches is vital to developing targeted preparedness strategies.

methodsIn this retrospective cohort study of 361 nursing homes exposed to Hurricane Michael (2018), we used a comparative interrupted time series design to assess changes in staffing intensity and composition from 30 days before landfall to 7 days after. We examined three outcomes using the Centers for Medicare & Medicaid Services (CMS) Payroll Based Journal: total staffing intensity (hours per resident per day), licensure composition (percentage of registered nurses (RN) and licensed practical nurses (LPN)), and employment composition (percentage of routine staff who are not independent contractors). We evaluated staffing intensity with linear mixed-effects models and licensure and employment composition using linear probability models. We report point estimates and 95% confidence intervals (CI).

resultsOf 361 nursing homes, 39.9% were rural. At baseline, rural facilities had 8% (0.92; 95% CI 0.87-0.96) lower total staffing intensity compared to non-rural facilities. In the post-event period, rural facilities increased total staffing by an additional 4% (95% CI 1.02 to 1.06) in the post-event period compared to non-rural facilities. Rural facilities increased their routine staff representation (0.46% points; 95% CI 0.14 to 0.78) but decreased licensed staff representation (-1.00% points; 95% CI -1.39 to 0.61) compared to the post-disaster staffing changes in non-rural facilities.

conclusionsDistinct disaster-related staffing approaches may heighten baseline staffing differences between rural and non-rural nursing homes. Disaster-related staffing intensity increased in rural facilities, with rural facilities starting from a lower baseline. Although rural facilities may have benefited from greater reliance on routine staff, they were unable to augment licensed nurse staffing. These findings offer foundational evidence regarding the influence of baseline staffing practices and local healthcare workforce conditions on disaster-related staffing strategies.

Indexed as

Cyclonic StormsDisaster PlanningNursing HomesPersonnel Staffing and SchedulingRural Health ServicesHumansRetrospective StudiesRural PopulationUnited Statesdisaster responsenursing homesolder adultsruralstaffing

Identifiers

PMID40938301
PMCPMC12670253

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.