Evidence map›Paper›PMID 39977667›Full record

ArticleJournal of global health2025

The efficiency and productivity-changing trend of PHCIs since the 2009 health reform in China based on a three-stage DEA and Malmquist Productivity Index.

Ling Liu, Jia Peng, Sumit Kane, Chenkai Wu, Yumei Liu, Jiayan Huang

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Article in Journal of global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ling Liu *NHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai, China.
Jia Peng *NHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai, China.
Sumit KaneNossal Institute for Global Health, Melbourne School of Population and Global Health, University of Melbourne, Australia.
Chenkai WuGlobal Health Research Center, Duke Kunshan University, Kunshan, China.
Yumei LiuInternational School of Public Health and One Health, Hainan Medical University, Haikou, Hainan Province, China.
Jiayan HuangNHC Key Laboratory of Health Technology Assessment, School of Public Health, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In China, most primary health care institutes (PHCIs) support ground-level medical services which are essential to residents' health levels. The Chinese government implemented a health reform in 2009 to strengthen PHCIs through increased fiscal inputs. However, how efficiently these inputs were converted into PHCIs' services remains unclear. We aimed to examine the efficiency of PHCIs' medical services and investigate if any changes occurred following the implementation of the health reform. Methods: We aggregated data from PHCIs from Hainan's 18 districts (2011-21), treating those from the same district as one decision-making unit (DMU). We used three-stage data envelopment analysis (DEA) to assess the efficiencies of these PHCIs, adjusting the approach for environmental factors, managerial ineffectiveness, and statistical errors potentially arising from the background variability of measured data that deviates from the input and output values, allowing all DMUs to be compared in a homogeneous environment. We used the adjusted efficiency scores to evaluate the efficiency of PHCIs in Hainan each year and the Malmquist Productivity Index (MPI) to explore the productivity change of PHCIs over time. Results: After adjusting for environmental factors between 2011-21, technical efficiency (TE) decreased from 0.825 to 0.745, pure technical efficiency (PTE) increased from 0.936 to 0.954, and scale efficiency (SE) decreased from 0.883 to 0.783. Seven districts had full PTE (1.0) and two districts had full TE (1.0) after adjustment. The mean MPI from 2011 to 2021 was 0.9430, indicating a 5.7% decrease in PHCIs' efficiency. After excluding the low productivity index possibly influenced by COVID-19 (2019 to 2021), PHCIs' efficiency decreased by 0.49%, with a mean MPI of 0.9951. Conclusions: The efficiency of PHCIs in Hainan has declined slightly since the health reform. Low level of scale efficiency posed a significant impact on the overall efficiency of the medical services in PHCIs. Among potential inefficient technological performances, future policy formulation might focus more on the imbalanced allocation of resources in less-developed regions and PHCIs' lack of attractiveness to local patients.

Indexed as

Efficiency, OrganizationalHealth Care ReformPrimary Health CareChinaHumans

Identifiers

PMID39977667
PMCPMC11893142

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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.