Evidence map›Paper›PMID 42517380›Full record

ArticleThe International journal of health planning and management2026

The Effect of Pairing Assistance Under Medical Alliance Policy on Healthcare Utilization for Patients With Chronic Diseases in Rural China.

Mingyue Li, He Zhu, Haoqing Tang, Xiaoran Cheng, Xiaoyun Liu

Abstract read
In one paragraph

Article in The International journal of health planning and management, 2026. 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

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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

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

5 authors.

Mingyue LiDepartment of Health Policy and Management, School of Public Health, Peking University, Beijing, China.
He ZhuChina Center for Health Development Studies, Peking University, Beijing, China.
Haoqing TangDepartment of Health Policy and Management, School of Public Health, Peking University, Beijing, China.ORCID https://orcid.org/0000-0002-5805-2116
Xiaoran ChengDepartment of Health Policy and Management, School of Public Health, Peking University, Beijing, China.
Xiaoyun LiuChina Center for Health Development Studies, Peking University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pairing assistance (PA) of health professionals between county hospitals and township health centres is one of the key components of the reform of medical alliances in China to strengthen the development of health workforce in primary health care (PHC). This study aims to examine the effect of PA on healthcare utilization for patients with chronic diseases in rural areas. Two waves of National Health Services Survey (2013 and 2018) were used. A total of 13,893 and 22,725 rural residents with chronic diseases were included in the 2013 and 2018 waves, respectively. Multiple logistic regressions were used to examine the associations between PA and outpatient and inpatient service utilization in PHC. Chow test was used to examine the difference between PA in two models. Among rural patients with chronic diseases, 2-week outpatient visits increased from 22.69% to 27.54%, and annual hospitalisation admission increased from 20.72% in 2013 to 25.44%. PA was associated with a significant decrease in outpatient visits (p < 0.001) in 2018 after controlling for individual and county characteristics. Patients in PA counties were 1.45 times (95% CI 1.10-1.90) more likely to use PHC outpatient care in 2013, but the difference disappeared in 2018 (OR = 0.85, 95% CI 0.71-1.01). PA did not reverse the downward trend in the share of PHC outpatient visits. The potential monopoly of county hospitals should be prevented in the future.

Indexed as

Health PolicyPatient Acceptance of Health CareRural Health ServicesAdolescentAdultAgedChinaChronic DiseaseFemaleHumansMaleMiddle AgedPrimary Health CareRural PopulationYoung Adultchronic diseasehealth care utilizationmedical alliancepairing assistance

Identifiers

PMID42517380
PMCPMC13551518

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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.