Evidence map›Paper›PMID 41432298›Full record

ArticleJMIR formative research2025

Mapping the Availability of Rehabilitation Providers Using Public Licensure and Population Data for a Geographic Information System-Based Approach to Workforce Planning: Cross-Sectional Feasibility Study.

Madeline Ratoza, Rupal M Patel, Julia Chevan, Wayne Brewer, Katy Mitchell

Abstract read
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Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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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

5 authors.

Madeline RatozaUniversity of St. Augustine for Health Sciences, Austin, TX, United States.ORCID 0009-0007-1993-5171
Rupal M PatelTexas Woman's University, Houston, TX, United States.ORCID 0000-0001-5966-7983
Julia ChevanSpringfield College, Springfield, MA, United States.ORCID 0000-0002-3044-4070
Wayne BrewerTexas Woman's University, Houston, TX, United States.ORCID 0000-0002-4841-5454
Katy MitchellTexas Woman's University, Denton, TX, United States.ORCID 0000-0001-5182-5406

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccess to rehabilitation services is a critical yet under-studied dimension of health equity. Among the 6 domains of access, health care provider availability, defined as the presence of sufficient health care providers to meet population needs, is particularly underexplored in rehabilitation professions such as physical and occupational therapy. Current data reporting often lacks the geographic granularity required for effective workforce planning.

objectiveThe purpose of this study was to demonstrate the feasibility of mapping rehabilitation provider availability at the census tract level using geographic information systems and integrating public licensure and population data to inform equitable workforce planning.

methodsA descriptive, cross-sectional study was conducted using publicly available state licensure data for physical and occupational therapists and demographic data from the American Community Survey. Residential addresses of rehabilitation providers were geocoded and matched to 2020 census tracts. Population-to-provider ratios were calculated and mapped using choropleth and bivariate mapping techniques. Population-to-provider ratios were calculated per tract and summarized overall and by rurality using 2020 Rural-Urban Commuting Area (RUCA) codes (urban: RUCA of 1-3; rural: RUCA of ≥4). The spatial dependence of ratios was tested using a spatial autocorrelation statistic, the global Moran I, in ArcGIS Pro using edge contiguity neighbors and row standardization.

resultsAcross 6896 tracts, ratios ranged from 4.5 to 11,147 persons per provider (median 1131, IQR 537-2501). By rurality, urban tracts (n=5734, 83.1%) had a median ratio of 1141 (IQR 2054), and rural tracts (n=1162, 16.9%) had a median ratio of 1093 (IQR 1690), indicating a broadly similar central tendency with somewhat greater variability in urban areas. The population-to-provider ratio exhibited significant positive spatial autocorrelation (global Moran I=0.305; Z=40.28; P<.001), consistent with clustered pockets of high and low availability rather than random dispersion.

conclusionsA replicable geographic information system protocol can integrate licensure and demographic data to produce interpretable population-to-provider metrics and spatial diagnostics at the census-tract level. In Texas, rehabilitation workforce availability is spatially clustered and not explained solely by an urban-rural divide, underscoring the value of small-area mapping for equitable workforce planning and policy decisions.

Indexed as

Geographic Information SystemsHealth Services AccessibilityHealth WorkforceLicensureCross-Sectional StudiesFeasibility StudiesFemaleHumansMaleRural PopulationUnited Statesgeographic information systemshealth service accessrehabilitation workforcespatial analysisworkforce planning

Identifiers

PMID41432298
PMCPMC12775756

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