Evidence map›Paper›PMID 41059173›Full record

ArticleFrontiers in public health2025

Policy practice for narrowing urban-rural healthcare gaps: determinants and implementation path of the urban doctors servicing rural areas policy in Beijing, China.

Yao Liu, Chen Lu, Jiale Sheng, Yurou Zou

Abstract read
In one paragraph

Article in Frontiers in public health, 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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yao LiuBeijing Xicheng District Zhanlanlu Hospital (Beijing First Rehabilitation Hospital), Beijing, China.
Chen LuSchool of Public Policy and Management, University of Chinese Academy of Sciences, Beijing, China.
Jiale ShengSino-Danish College, University of Chinese Academy of Sciences, Beijing, China.
Yurou ZouSchool of Public Policy and Management, University of Chinese Academy of Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The urban-rural disparities in healthcare resources and service quality remain a critical challenge for equitable public health development in China. To address this, Beijing has implemented the "Urban Doctors Serving Rural Areas (UDSR)" policy-a key counterpart support initiative. Its core goal is to bridge urban-rural healthcare gaps by mobilizing urban medical professionals to serve rural institutions. Methods: Grounded in Van Meter and Van Horn's policy implementation framework, this study employs fuzzy-set Qualitative Comparative Analysis (fsQCA). It examines 39 annual observations from 13 paired urban-rural hospitals in Beijing over 2017-2019. To capture temporal changes, the study applies time-series QCA techniques. It analyzes conditions including support project quantity, subsidy source diversification, prescription rights, professional matching, communication channels, and policy cognition, with rural medical technology improvement as the outcome variable. Results: Three critical determinants of UDSR policy effectiveness are identified: the number of support projects, diversified subsidy sources, and prescription rights for urban doctors in rural institutions. Four implementation pathways are uncovered: (1) goal-and-cognition-driven, (2) professional-matching-driven, (3) external-funding-driven, and (4) comprehensive-factor-driven. Temporal analysis reveals two evolutionary paths: a dominant path achieved via integrating multiple factors, and a transitional path shifting from external funding reliance to professional alignment and goal cognition-reflecting adaptive maturation of the UDSR policy. Conclusion: This study advances understanding of counterpart support policy implementation by revealing synergistic combinations of influencing factors and dynamic evolutionary paths. The findings make two key contributions. Theoretically, they provide insights for policy implementation research in non-western contexts; practically, they offer guidance for optimizing urban-rural healthcare resource allocation and provide a framework for refining targeted support mechanisms in China and similar developing countries.

Indexed as

Healthcare DisparitiesHealth PolicyPhysiciansRural Health ServicesUrban Health ServicesBeijingHumansRural Populationcounterpart support policyfuzzy-set qualitative comparative analysisimplementation pathpolicy implementationurban doctors servicing in rural hospitals (UDSR) policyVan Meter-Van Horn policy implementation framework

Identifiers

PMID41059173
PMCPMC12497779

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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.