Evidence map›Paper›PMID 41941870›Full record

ArticleThe Gerontologist2026

Heterogeneous effects of nursing staff wages on turnover: evidence from U.S. nursing homes using an instrumental variable approach.

Rohit Pradhan, Akbar Ghiasi, Ganisher Davlyatov, Robert Weech-Maldonado

Abstract read
In one paragraph

Article in The Gerontologist, 2026. 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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0citing papers 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

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Rohit PradhanSchool of Health Administration, College of Health Professions, Texas State University, San Marcos, Texas, United States.ORCID 0009-0006-3762-7212
Akbar GhiasiDepartment of Healthcare Administration, H-E-B School of Business and Administration, University of the Incarnate Word, San Antonio, Texas, United States.ORCID 0000-0002-1477-4985
Ganisher DavlyatovDepartment of Health Administration and Policy, Hudson College of Public Health, University of Oklahoma Health Campus, Oklahoma City, Oklahoma, United States.ORCID 0000-0001-9410-9696
Robert Weech-MaldonadoDepartment of Health Services Administration, School of Health Professions, University of Alabama at Birmingham, Birmingham, Alabama, United States.ORCID 0000-0002-5005-0909

Funding

Tracking and Evaluation CoreU54GM104938 · NIGMS · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI Robert Hal Scofield · 2013 to 2026
$68.2M
NIGMS NIH HHS U54 GM104938NIGMS NIH HHS U5GM104938Research Enhancement Program grant at Texas State UniversityUniversity of Oklahoma Health Sciences
6 · The paper itself

Abstract

BACKGROUND AND

objectivesTurnover among nursing staff (registered nurses, licensed practical nurses, and certified nursing assistants [CNAs]) is a long-standing challenge in nursing homes with significant implications for quality of care. This study aimed to examine the relationship between nursing staff wages and turnover. RESEARCH DESIGN AND

methodsWe used national data from 2021 to 2023, linking multiple datasets including the Payroll-Based Journal and Medicare Cost Reports (n = 37,254). Turnover was modeled separately for each nursing staff type as a fractional outcome bounded between 0 and 1. The primary predictor variable was facility-level average hourly wage for each staff type. To address potential endogeneity and reverse causality, we used a two-stage residual inclusion instrumental variables approach with county-level average wages (excluding the index facility) as the instrument. Models controlled for facility-level organizational and county-level market characteristics, with fixed effects for county and year and cluster-robust standard errors at the facility level.

resultsHigher CNA wages were significantly associated with lower turnover (β = -0.35, 95% CI [-0.59, -0.11], p = .005), indicating a 0.35 percentage point reduction in turnover per $1 increase in hourly wage. Wages were not significantly associated with turnover among licensed nurses. DISCUSSION AND IMPLICATIONS: Findings suggest that wage increases may be most effective for CNAs, while retaining licensed nurses likely requires complementary organizational and nonmonetary strategies. While nursing homes should strive to offer competitive wages to their staff, targeted reimbursement reforms may be necessary to overcome financial constraints.

Indexed as

Nursing HomesNursing StaffPersonnel TurnoverSalaries and Fringe BenefitsHumansUnited StatesNursing homesNursing staffTurnover

Identifiers

PMID41941870
PMCPMC13131959

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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.