Evidence map›Paper›PMID 33306702›Full record

ArticlePloS one2020

Productivity change and its driving forces in Chinese healthcare sector.

Zhensheng Chen, Xueli Chen, Tomas Baležentis, Xiaoqing Gan, Vivian Valdmanis

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

Zhensheng ChenSchool of Management, Nanchang University, Nanchang, China.
Xueli ChenAnhui University of Finance and Economics, Bengbu, China.ORCID 0000-0003-0758-5243
Tomas BaležentisLithuanian Institute of Agrarian Economics, Vilnius, Lithuania.
Xiaoqing GanSchool of Management, Nanchang University, Nanchang, China.
Vivian ValdmanisWestern Michigan University, Kalamazoo, MI, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the last medical reform in 2009, China's public hospitals have been facing the changes in the institutional environment. However, the effects of reforms have not been received enough attention to deliver evidence-based implications. In this paper, we first assess the efficiency of regional public hospitals from 2011 to 2018, employing a proposed method based on an additive indicator and an aggregate directional distance function (DDF). The method applied allows for decomposing total factor productivity (TFP) indicator into three components, including technical efficiency change (TEC), total productivity (TP) and scale efficiency change (SEC). Second, following the efficiency assessment, we carry post-efficiency analysis to identify the determinants of efficiency of the public hospitals. The results show that annual average TFP growth rate is 1.38%, which is driven mainly by TEC. Regional disparities of public hospitals' performance are expanding. Almost 75% of the regions considered show a positive TFP growth. The regression results show that the significant determinants of efficiency of regional public hospitals include the price of and demand for health services.

Indexed as

Efficiency, OrganizationalChinaDatabases, FactualHealth Care ReformHealth Care SectorHospitals, Public

Identifiers

PMID33306702
PMCPMC7732348

What OpenQuestion holds

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Registered trials

None linked

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.