Evidence map›Paper›PMID 40648528›Full record

ArticleHealthcare (Basel, Switzerland)2025

Analysis of Geospatial Variations in Healthcare Across Rural Communities in the US Using Machine Learning.

Radion Svynarenko, Hyun Kim, Tracey Stansberry, Changwha Oh, Anujit Sarkar, Lisa Catherine Lindley

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 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

6 authors.

Radion SvynarenkoCollege of Nursing, University of Tennessee, 1412 Circle Dr., Knoxville, TN 37996, USA.ORCID 0000-0002-7568-529X
Hyun KimDepartment of Geography and Sustainability, University of Tennessee, 1000 Phillip Fulmer Way, Knoxville, TN 37996, USA.
Tracey StansberryCollege of Nursing, University of Tennessee, 1412 Circle Dr., Knoxville, TN 37996, USA.
Changwha OhDepartment of Geography and Sustainability, University of Tennessee, 1000 Phillip Fulmer Way, Knoxville, TN 37996, USA.ORCID 0000-0002-1682-1802
Anujit SarkarCollege of Nursing, University of Tennessee, 1412 Circle Dr., Knoxville, TN 37996, USA.
Lisa Catherine LindleyCollege of Nursing, University of Tennessee, 1412 Circle Dr., Knoxville, TN 37996, USA.ORCID 0000-0003-2960-7896

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesRural public health is significantly impacted by social drivers of health (SDOH), a set of community-level factors, with rural areas facing challenges such as a higher rate of aging population, fewer jobs, lower income, higher mortality, and poor healthcare access. While much research exists on rurality and SDOH, methodological issues remain, including a narrow definition of SDOH that often overlooks the critical location aspect of healthcare.

methodsThis study utilized county-level data from the 2020 Agency of Healthcare Research and Quality SDOH database to investigate geospatial variations in healthcare across the spectrum of rurality. This study employed a set of novel spatial-statistical methods: gradient boosting machines (GBM), Shapley additive explanations (SHAP), and multiscale geographically weighted regression (MGWR).

resultsThe analysis of 262 variables across 1976 counties identified 20 key variables related to rural healthcare. These variables were grouped into three categories: health insurance status, access to care, and the volume of standardized Medicare payments. The MGWR model further revealed both global and local effects of specific healthcare characteristics on rurality, demonstrating that geographically varying relationships were strongly associated with socio-geographical factors.

conclusionsTo improve the SDOH in vulnerable rural communities, particularly in Southern states without Medicaid expansion, policymakers must develop and implement equitable and innovative care models to address social determinants of health and access-to-care issues, especially given the potential cuts to public health programs.

Indexed as

healthcare accessmachine learningmultiscale geographically weighted regressionrural healthsocial drivers of health (SDOH)

Identifiers

PMID40648528
PMCPMC12248851

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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.