Evidence map›Paper›PMID 36915124›Full record

ArticleBMC health services research2023

A study of primary health care service efficiency and its spatial correlation in China.

Kangni Mei, Ruxin Kou, Yuqing Bi, Yuzhuo Liu, Jingwen Huang, Wei Li

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Article in BMC health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
–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

27 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  9. [Regional distribution differences and influencing factors of primary healthcare institutions in China].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025
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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

6 authors.

Kangni Mei *School of Public Health, Weifang Medical University, Weifang, 261053, Shandong, China.
Ruxin Kou *School of Public Health, Weifang Medical University, Weifang, 261053, Shandong, China.
Yuqing BiSchool of Public Health, Weifang Medical University, Weifang, 261053, Shandong, China.
Yuzhuo LiuSchool of Management, Weifang Medical University, Weifang, 261053, Shandong, China.
Jingwen HuangSchool of Public Health, Weifang Medical University, Weifang, 261053, Shandong, China.
Wei LiSchool of Public Health, Weifang Medical University, Weifang, 261053, Shandong, China. imliwei@163.com.

Funding

national nature science foundation of China No.71774119
6 · The paper itself

Abstract

backgroundChina's primary health care system has undergone major changes since the new round of medical reform in 2009, but the current status of primary health care institution service efficiency is still unsatisfactory. The purpose of this study is to compare and evaluate the China's primary health care institution service efficiency and provide a reference for improving the efficiency and promoting the development of primary health care institution.

methodsBased on panel data of 31 provinces (municipalities directly under the central government and autonomous regions) in mainland China from 2011 to 2020, using the super efficiency slack-based measure-data envelopment analysis model, to analyze the data from a static perspective, and the changes in the efficiency of primary health care services were analyzed from a dynamic perspective by using the Malmquist index method. Spatial autocorrelation analysis method was used to verify the spatial correlation of primary health care service efficiency among various regions.

resultsThe number of Primary health care institutions increased from 918,000 in 2011 to 970,000 in 2020. The average primary health care institution service efficiency in the northeastern region including Jilin (0.324), Heilongjiang (0.460), Liaoning (0.453) and northern regions such as Shaanxi (0.344) and Neimenggu (0.403) was at a low level, while the eastern coastal regions such as Guangdong (1.116), Zhejiang (1.211), Shanghai (1.402) have higher average service efficiency levels. The global Moran's I showed the existence of spatial autocorrelation, and the local Moran's I index suggested that the problem of uneven regional development was prominent, showing a contiguous regional distribution pattern. Among them, H-H (high-efficiency regions) were mainly concentrated in Jiangsu, Anhui and Shanghai, and L-L regions (low-efficiency regions) were mostly in northern and northeastern China.

conclusionThe service efficiency of primary health care institution in China showed a rising trend in general, but the overall average efficiency was still at a low level, and there were significant geographical differences, which showed a spatial distribution of "high in the east and low in the west, high in the south and low in the north". The northwestern region, after receiving relevant support, has seen a rapid development of primary health care, and its efficiency was steadily improving and gradually reaching a high level. The average primary health care institution service efficiency in the northeastern region including the northern region of China was at a low level, while the average efficiency in the eastern coastal region and some economically developed regions was high, which also verifies the dependence and high symbiosis of primary health care institution service efficiency on regional economy.

Indexed as

Delivery of Health CareEfficiencyChinaCitiesHumansPrimary Health CareData envelopment analysisExploratory spatial data analysisMoran’s IPrimary health care institutionService efficiencySpatial autocorrelation

Identifiers

PMID36915124
PMCPMC10012696

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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.