Evidence map›Paper›PMID 38351077›Full record

ArticleBMC health services research2024

A spatial feature analysis of primary health care utilization in a large city in China and its implications for family doctor contract service policy.

Xin Rao, Li Luo, Xingyue Wang

Abstract read
In one paragraph

Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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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3 · Its place in the literature

Who cites it

6 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

3 authors.

Xin RaoDepartment of General Practice office of General Practice Medical Center, West China HospitalSCU, Chengdu, China.
Li LuoInstitute of Service ManagementSchool of business, SCU, Chengdu, China.
Xingyue WangDepartment of Graduate Medical Education, West China Hospital/School of Medicine, SCU, Chengdu, China. 7120639@qq.com.

Funding

National Steering Committee for Medical Professional Degree Education/Chinese Medical Doctor Association 2021 National General Practice Education and Teaching Research Project B-YXGP20210402-01Sichuan Province Science and Technology Support Program 2022JDR0194
6 · The paper itself

Abstract

backgroundFamily doctor contract policy is now run by the State Council as an important move to promote the hierarchical medical system. Whether the family doctor contract policy achieves the initial government's goal should be measured further from the perspective of patient visits between hospitals and community health centers, which are regarded as grass medical agencies.

methodsThe spatial feature measurement method is applied with ArcGIS 10.2 software to analyze the spatial aggregation effect of patient visits to hospitals or community health centers among 20 districts of one large city in China and analyze the family doctor contract policy published in those areas to compare the influence of visit tendencies.

resultsFrom year 2016-2020, visits to hospitals were in the high-high cluster, and the density was spatially overflow, while there was no such tendency in visits to community health centers. The analysis of different family doctor contract policy implementation times in 20 districts reflects that the family doctor contract policy has a very limited effect on the promotion of the hierarchical medical system, and the innovation of the family doctor contract policy needs to be considered.

conclusionsA brief summary and potential implications. A multi-integrated medical system along with family doctor contract policy needs to be established, especially integrated in leadership and governance, financing, workforce, and service delivery between hospitals and community health centers, to promote the hierarchical medical system.

Indexed as

Delivery of Health CarePhysicians, FamilyChinaContract ServicesHealth PolicyHumansPatient Acceptance of Health CareFamily doctor contract serviceHealth utilizationPrimary health careSpatial feature analysis

Identifiers

PMID38351077
PMCPMC10863294

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LicenceCC BY
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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.