Evidence map›Paper›PMID 39666469›Full record

ArticleNursing research

Poorer Nurse Staffing in Black-Serving Hospitals.

Eileen T Lake, Christin Iroegbu, Jessica G Smith, Douglas O Staiger, Kimi Li, Hal Chen, Nehemiah Weldeab, Jeannette A Rogowski

Abstract read
In one paragraph

Article in Nursing research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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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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

2 citing papers in PubMed.

  1. Article
  2. Including Nursing System Factors to Address Health Disparities: A Conceptual Framework.Inquiry : a journal of medical care organization, provision and financing
    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.

Funding

ADVANCED TRAINING IN NURSING OUTCOMES RESEARCHT32NR007104 · NINR · UNIVERSITY OF PENNSYLVANIA · PI JACQUELINE MARGO BROOKS CARTHON, EILEEN T LAKE · 1999 to 2026
$11.6M
NINR NIH HHS T32 NR007104
6 · The paper itself

Abstract

backgroundPatients in hospitals that serve disproportionately patients of Black race have worse outcomes than patients in other hospitals, but the modifiable nursing factors that may contribute to such disparities have not been explored.

objectiveThe study objective was to examine whether nurse staffing differs in hospitals that serve predominantly patients of Black race (Black-serving hospitals) as compared to other hospitals.

methodsA cross-sectional correlational design using a nurse survey in a national hospital sample was used to fulfill the study objective. Nurse staffing was measured as the maximum number of patients cared for on the last shift from the 2015 annual registered nurse survey conducted in National Database of Nursing Quality Indicators hospitals. Hospitals were classified into subgroups of low, medium, and high percentages of patients of Black race using the 2019 Medicare Provider Analysis and Review database.

resultsIn survey data from 179,336 registered nurses in 574 hospitals, nurse staffing was significantly worse in high-Black-serving hospitals as compared to medium- and low-Black-serving hospitals. In Poisson regression models that adjusted for nursing unit type and hospital characteristics, nurses in high-Black-serving hospitals and medium-Black-serving hospitals had more patients-per-nurse than did nurses in low-Black-serving hospitals. DISCUSSION: Small, statistically significant differences in nurse staffing that are worse in hospitals where Black patients disproportionately access their care were found using nurse survey data accounting for nursing unit type. The poorer nurse staffing in Black-serving hospitals may compromise the care and outcomes of the seven in 10 hospitalized Black older adults who receive care in Black-serving hospitals. The consequences for patient outcome disparities of poorer nurse staffing in Black-serving hospitals deserve investigation. Policies to increase nurse staffing in hospitals serving a higher proportion of patients of Black race are needed to contribute to efforts to reduce health disparities.

Indexed as

Black or African AmericanNursing Staff, HospitalPersonnel Staffing and SchedulingCross-Sectional StudiesFemaleHealthcare DisparitiesHospitalsHumansMaleSurveys and QuestionnairesUnited States

Identifiers

PMID39666469
PMCPMC11643354

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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.