Evidence map›Paper›PMID 36299745›Full record

ArticleFrontiers in public health2022

Intended and unintended impacts of the comprehensive reform of urban public hospitals: A mixed-method study in Hangzhou, China.

Tao Zhang, Jing Liu, Beiyin Lu, Zhongheng Yan, Xiaojun Huang, Wei Lu

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 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

6 authors.

Tao ZhangDepartment of Health Policy and Management, School of Public Health, Hangzhou Normal University, Hangzhou, China.
Jing LiuAdministrative Office, Yuebei People's Hospital, Shaoguan, China.
Beiyin LuDepartment of Health Policy and Management, School of Public Health, Hangzhou Normal University, Hangzhou, China.
Zhongheng YanOffice of the Vice President, Central Hospital of Hainan Province Western, Haikou, China.
Xiaojun HuangDepartment of Health Management, School of Management, Hainan Medical University, Haikou, China.
Wei LuDepartment of Health Management, School of Management, Hainan Medical University, Haikou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Public hospital reform is a key area in the Chinese healthcare system reform with the aim of controlling excessive growth of medical expenditures. This study aims to evaluate the impacts of two rounds of urban public hospital reforms respectively starting in 2018 and 2019. Method: A mixed-method method was conducted in Hangzhou. In the quantitative phase, monthly data covering 7 provincial, 12 municipal, and 35 district hospitals from March 2017 to June 2020 was analyzed using a panel-interrupted time-series. Thematic content analysis was conducted using qualitative data collected from 32 in-depth interviews. Results: Quantitative data showed a considerable reduction in the proportion of drug revenue (provincial hospitals: -4.937%; municipal hospitals: -2.765%; district hospitals: -2.189%) and an increase in the proportion of consumable (provincial hospitals: Conclusions: Overall, the urban public hospital reforms in China created positive effects in adjusting hospital revenue structure and constraining soaring medical expenditures. Unintended consequences remind policymakers to establish rational and dynamic compensation mechanisms for public hospitals.

Indexed as

Health Care ReformHospitals, PublicChinaHealth ExpendituresInterrupted Time Series AnalysisChinahealth care expenditurehospital revenue structurepanel-interrupted time-seriespublic hospital reform

Identifiers

PMID36299745
PMCPMC9589150

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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.