Evidence map›Paper›PMID 41709434›Full record

ArticleInquiry : a journal of medical care organization, provision and financing

Higher Nursing Staff Wages Are Associated With Lower Operating Margins in Nursing Homes: An Instrumental Variable Analysis.

Akbar Ghiasi, Rohit Pradhan, Gregory Orewa, Robert Weech-Maldonado

Abstract read
In one paragraph

Article in Inquiry : a journal of medical care organization, provision and financing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Akbar GhiasiUniversity of the Incarnate Word, San Antonio, TX, USA.
Rohit PradhanTexas State University, San Antonio, TX, USA.ORCID 0009-0006-3762-7212
Gregory OrewaUniversity of Texas at San Antonio, TX, USA.ORCID 0000-0002-3519-7902
Robert Weech-MaldonadoUniversity of Alabama at Birmingham, AL, USA.ORCID 0000-0002-5005-0909

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nursing staff including registered nurses (RNs), licensed practical nurses (LPNs), and certified nursing assistants (CNAs) are critical to nursing home (NH) operations but account for approximately 27% of net revenues. Understanding how nursing staff wages affect financial performance is particularly important as policy efforts seek to expand NH minimum staffing hours. Drawing from efficiency wage theory, which posits that employers may pay above-market wages to enhance worker productivity and retention, this study examined the relationship between nursing staff wages and NH financial performance. We used secondary datasets, including Payroll-Based Journal data and Medicare cost reports (N = 37 933 facility-year observations, 2020-2022). The dependent variable was operating margin, while the independent variables were facility-level RN, LPN, and CNA wages. An instrumental variable (IV) approach was used to address potential endogeneity in RN wages, with county-level average wages (excluding the index facility) serving as the instrument. The first stage modeled RN wages as a function of the instrument, and the second stage estimated the effect of predicted wages on operating margin. Ordinary least squares models were used for LPN and CNA wages, for which endogeneity was not detected. A $1 increase in RN wages was associated with a 0.70 percentage-point decrease in operating margin (

Indexed as

Nursing HomesNursing StaffSalaries and Fringe BenefitsHumansMedicareUnited Statesefficiency wage theoryfinancial performanceinstrumental variable analysisnursing homesnursing staff wages

Identifiers

PMID41709434
PMCPMC12921171

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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.