Evidence map›Paper›PMID 40050554›Full record

Observational studyJournal of general internal medicine2025

Impact of Primary Care Team Configuration on Access and Quality of Care.

Sylvia J Hysong, Kelley Arredondo, Houston F Lester, Richard SoRelle, Trang Pham, Frederick L Oswald, LeChauncy Woodard, Laura A Petersen, Joshua Hamer, Ashley M Hughes

Abstract readObservational Study
In one paragraph

Observational study in Journal of general internal medicine, 2025. 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

10 authors.

Sylvia J HysongSection of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA. hysong@bcm.edu.ORCID 0000-0002-9063-5207
Kelley ArredondoSection of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Houston F LesterSection of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Richard SoRelleSection of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Trang PhamDepartment of Biomedical & Health Information Sciences, University of Illinois at Chicago, Chicago, IL, USA.
Frederick L OswaldDepartment of Psychological Sciences, Rice University, Houston, TX, USA.
LeChauncy WoodardSection of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Laura A PetersenSection of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Joshua HamerSection of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
Ashley M HughesCenter of Innovations in Chronic Complex Healthcare, Edward Hines Jr VA Medical Center Hines, Hines, IL, USA.

Funding

Clinical and Translational Science Collaborative of Northern Ohio, Catalyzing Linkages to Equity in Health (CLE Health)UM1TR004528 · NCATS · CASE WESTERN RESERVE UNIVERSITY · PI GRACE A MCCOMSEY · 2023 to 2026
$32.1M
NCATS NIH HHS UM1 TR004528
6 · The paper itself

Abstract

backgroundTeam-based primary care has become the norm within many large healthcare systems; however, limited guidance exists on how to optimally staff primary care teams in relationship to healthcare.

objectiveThis paper examines the associations between variations in team staffing configurations on primary care access and clinical quality.

designObservational study linking national Veterans Health Administration (VHA) data from February 2020 on primary care team staffing configurations to data on access to and quality of care the teams delivered.

participantsWe examined data from 22,390 primary care personnel assigned to 7050 teams from 1050 VA Medical Centers and Community-Based Outpatient Clinics across the USA. MAIN MEASURES: We used data from VHA's Corporate Data Warehouse. We assessed team-based measures of overall adherence to VHA's national guidelines for front-line clinical team staffing based on achievement of recommended staffing configurations in terms of quantity of staff and diversity of professional roles. To measure staffing sufficiency, we integrated total number of team members (team size) with their full-time equivalents (FTEs). To measure role diversity, we assessed deviation from guidelines using network analysis of staffing data. As outcomes, we used three measures of patient access to primary care and four measures of clinical quality that were prioritized by a prior expert panel. We analyzed associations between predictors and outcomes using random intercept multilevel models, with teams nested within healthcare facility. KEY

resultsVariation in team size and FTE reflected lack of adherence to VHA guidelines rather than normal variation. Overall adherence to VHA guidelines was unrelated to access or quality of care delivered. In most cases, teams with higher FTEs exhibited better outcomes. Increased role diversity was associated with decreased secure messaging communication ratios. Teams with more members exhibited improved 2-day post-hospital discharge contact, but reduced access through third next available appointments.

conclusionsPrimary care teams require a minimum amount of FTE staff capacity to deliver high quality and access to healthcare. Future work should examine how these associations vary by specific job role to further optimize staffing configurations.

Indexed as

Health Services AccessibilityPatient Care TeamPrimary Health CareQuality of Health CareHumansUnited StatesUnited States Department of Veterans Affairs

Identifiers

PMID40050554
PMCPMC12686220

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.