Evidence map›Paper›PMID 39436649›Full record

ArticleJAMA network open2024

Clinician Staffing and Quality of Care in US Health Centers.

Q Wilton Sun, Howard P Forman, Logan Stern, Benjamin J Oldfield

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. 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.

Q Wilton SunYale School of Medicine, New Haven, Connecticut.
Howard P FormanDepartment of Radiology and Biological Imaging, Yale School of Medicine, New Haven, Connecticut.
Logan SternFair Haven Community Health Care, New Haven, Connecticut.
Benjamin J OldfieldFair Haven Community Health Care, New Haven, Connecticut.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

Importance: Health centers are vital primary care safety nets for underserved populations, but optimal clinician staffing associated with quality care is unclear. Understanding the association of clinician staffing patterns with quality of care may inform care delivery, scope-of-practice policy, and resource allocation. Objective: To describe the association of clinician staffing models and ratios with quality-of-care metrics in health centers. Design, Setting, and Participants: This cross-sectional study of US health centers used data from the 2022 Health Resources and Services Administration Uniform Data System (UDS). Exposure: Clinician staffing ratios, expressed as the fraction of full-time equivalents (FTEs) per 1000 visits of physicians, advanced practice registered nurses (APRNs), and physician associates (PAs) to total clinician FTEs at each health center. Main outcomes and measures: Percentage of eligible patients receiving the corresponding service or outcome for 14 individual clinical quality metrics collected by the UDS, including infant immunizations; screening for cancer, depression, tobacco use, hypertension, HIV, and glycated hemoglobin levels; weight and body mass index (BMI) assessment; and appropriate statin, aspirin, and/or antiplatelet therapy. Results: This analysis of 791 health centers serving 16 114 842 patients (56.6% female) identified 5 clinician staffing models: balanced (similar FTEs of physicians, APRNs, and PAs; 152 [19.2%] of health centers), higher FTEs of APRNs than physicians (174 [22.0%]), higher FTEs of physicians than APRNs (160 [20.2%]), approximately equal FTEs of physicians and APRNs (263 [33.2%]), and large scale (42 [5.3%]). Adjusted linear models showed positive associations between physician FTEs per 1000 visits and cervical (β, 14.9; 95% CI, 3.1-26.7), breast (β, 15.7; 95% CI, 3.2-28.1), and colorectal (β, 18.3; 95% CI, 6.0-30.6) cancer screening. Generalized additive models showed nonlinear positive associations beginning at a physician FTE ratio of 0.45 (95% CI, 0.02-6.22) for infant vaccinations, 0.39 (95% CI, 0.05-2.21) for cervical cancer screening, 0.39 (95% CI, 0.02-1.67) for breast cancer screening, 0.47 (95% CI, 0.00-5.76) for HIV testing, and 0.70 (95% CI, 0.18-19.96) for depression in remission; APRN FTE ratio of 0.45 (95% CI, 0.17-7.46) for adult BMI assessment; and PA FTE ratio of 0.16 (95% CI, 0.11-3.88) for infant vaccinations. Staffing models were not associated with 7 of the 14 metrics analyzed. Conclusions and Relevance: In this cross-sectional study of health centers, physician FTE ratio was associated with higher performance in cancer screening, infant vaccinations, and HIV testing; APRN FTE ratio was associated with higher performance in preventative health assessments; and PA FTE ratio was associated with higher performance in infant vaccination. These findings suggest that targeted staffing strategies may be associated with quality of care in certain domains and that tailored approaches to health center staffing based on community-specific needs are warranted.

Indexed as

Personnel Staffing and SchedulingQuality of Health CareCross-Sectional StudiesFemaleHumansMalePrimary Health CareUnited StatesWorkforce

Identifiers

PMID39436649
PMCPMC11581487

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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.