Evidence map›Paper›PMID 40823006›Full record

ArticleHealth affairs scholar2025

State variation in staffing and characteristics of nursing homes most impacted by new federal standards.

Robert J Skinner, Jiani Yu, Mark A Unruh, Robert Tyler Braun, Hye-Young Jung, Phyllis Johnson, Rahul Fernandez, David G Stevenson

Abstract read
In one paragraph

Article in Health affairs scholar, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

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.

Robert J SkinnerDepartment of Health Policy, Vanderbilt University Medical Center, Nashville, TN 37203, United States.ORCID https://orcid.org/0000-0002-0195-2121
Jiani YuDepartment of Population Health Sciences, Weill Cornell Medical College, New York, NY 10065, United States.ORCID https://orcid.org/0000-0002-7518-6220
Mark A UnruhDepartment of Population Health Sciences, Weill Cornell Medical College, New York, NY 10065, United States.ORCID https://orcid.org/0000-0002-9662-5659
Robert Tyler BraunDepartment of Population Health Sciences, Weill Cornell Medical College, New York, NY 10065, United States.ORCID https://orcid.org/0000-0001-6408-2656
Hye-Young JungDepartment of Population Health Sciences, Weill Cornell Medical College, New York, NY 10065, United States.
Phyllis JohnsonDepartment of Population Health Sciences, Weill Cornell Medical College, New York, NY 10065, United States.ORCID https://orcid.org/0000-0002-8594-9041
Rahul FernandezDepartment of Population Health Sciences, Weill Cornell Medical College, New York, NY 10065, United States.
David G StevensonDepartment of Health Policy, Vanderbilt University Medical Center, Nashville, TN 37203, United States.ORCID https://orcid.org/0000-0002-3370-3277

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: New federal minimum staffing standards aim to increase staffing in nursing homes. As the future of the new rule remains uncertain, this study compares the new standard to existing state staffing standards and examines the characteristics of nursing homes who may meet the new requirement. Methods: We utilized the 2023 CMS Payroll-Based Journal Data to calculate staffing ratios and nurse turnover. We summarized staffing levels by nursing home size, ownership type, chain affiliation, and rurality. We compared state staffing policies using data from the Medicaid and Children's Health Insurance Program (CHIP) Payment and Access Commission (MACPAC). Statistical analyses included Student's Results: Nursing homes in 11 states had staffing levels below the new federal minimum. Across states, compliance with the new federal requirements ranged from 31% in states with the lowest staffing requirements to 65% in states with the highest. Higher state staffing standards were associated with better quality ratings and lower turnover. Conclusion: Our paper explores state efforts toward reaching staffing goals. While higher state staffing standards correlate with better nursing home quality ratings, many homes may struggle to meet the new federal requirements.

Indexed as

elder carelong-term services and supportsnursing homeregulationstaffing

Identifiers

PMID40823006
PMCPMC12352297

What OpenQuestion holds

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Registered trials

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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.