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Evaluating the efficiency of primary health care institutions in China: an improved three-stage data envelopment analysis approach
BACKGROUND: Primary health care (PHC) institutions are key to realizing the main functions of the health care system. Since the new health care reform in 2009, the Chinese government has invested heavily in PHC institutions and launched favorable initiatives to improve the efficiency of such institu...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503195/ https://www.ncbi.nlm.nih.gov/pubmed/37715162 http://dx.doi.org/10.1186/s12913-023-09979-3 |
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author | Su, Wanmin Hou, Yatian Huang, Mengge Xu, Jiamian Du, Qingfeng Wang, Peixi |
author_facet | Su, Wanmin Hou, Yatian Huang, Mengge Xu, Jiamian Du, Qingfeng Wang, Peixi |
author_sort | Su, Wanmin |
collection | PubMed |
description | BACKGROUND: Primary health care (PHC) institutions are key to realizing the main functions of the health care system. Since the new health care reform in 2009, the Chinese government has invested heavily in PHC institutions and launched favorable initiatives to improve the efficiency of such institutions. This study is designed to gauge the efficiency of PHC institutions by using 2012–2020 panel data covering 31 provinces in China. METHODS: This study applied an improved three-stage data envelopment analysis (DEA) model to evaluate the efficiency of PHC institutions in China. Unlike the traditional three-stage DEA model, the input-oriented global super-efficiency slack-based measurement (SBM) DEA model is used to calculate the efficiency in the first and third stages of the improved three-stage DEA model, which not only allows the effects of environmental factors and random noise to be taken into account but also deal with the problem of slack, super-efficiency and the comparability of interperiod efficiency values throughout the efficiency measurement. RESULTS: The results show that the efficiency of PHC institutions has been overestimated due to the impact of external environmental factors and random noise. From 2012 to 2020, the efficiency of PHC institutions displayed a downward trend. Moreover, there are significant differences in the efficiency of PHC institutions between regions, with the lowest efficiency being found in the northeast region. The efficiency of PHC institutions is significantly affected by residents’ annual average income, per capita GDP, population density, the percentage of the population aged 0–14, the percentage of the population aged 65 and older, the number of people with a college education and above per 100,000 residents, and the proportion of the urban population. CONCLUSIONS: Substantial investment in PHC institutions has not led to the expected efficiency gains. Therefore, more effective measures should be taken to improve the efficiency of PHC institutions in China based on local conditions. This study provides a new analytical approach to calculating the efficiency of PHC institutions, and this approach can be applied to efficiency evaluation either in other fields or in other countries. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-09979-3. |
format | Online Article Text |
id | pubmed-10503195 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-105031952023-09-16 Evaluating the efficiency of primary health care institutions in China: an improved three-stage data envelopment analysis approach Su, Wanmin Hou, Yatian Huang, Mengge Xu, Jiamian Du, Qingfeng Wang, Peixi BMC Health Serv Res Research BACKGROUND: Primary health care (PHC) institutions are key to realizing the main functions of the health care system. Since the new health care reform in 2009, the Chinese government has invested heavily in PHC institutions and launched favorable initiatives to improve the efficiency of such institutions. This study is designed to gauge the efficiency of PHC institutions by using 2012–2020 panel data covering 31 provinces in China. METHODS: This study applied an improved three-stage data envelopment analysis (DEA) model to evaluate the efficiency of PHC institutions in China. Unlike the traditional three-stage DEA model, the input-oriented global super-efficiency slack-based measurement (SBM) DEA model is used to calculate the efficiency in the first and third stages of the improved three-stage DEA model, which not only allows the effects of environmental factors and random noise to be taken into account but also deal with the problem of slack, super-efficiency and the comparability of interperiod efficiency values throughout the efficiency measurement. RESULTS: The results show that the efficiency of PHC institutions has been overestimated due to the impact of external environmental factors and random noise. From 2012 to 2020, the efficiency of PHC institutions displayed a downward trend. Moreover, there are significant differences in the efficiency of PHC institutions between regions, with the lowest efficiency being found in the northeast region. The efficiency of PHC institutions is significantly affected by residents’ annual average income, per capita GDP, population density, the percentage of the population aged 0–14, the percentage of the population aged 65 and older, the number of people with a college education and above per 100,000 residents, and the proportion of the urban population. CONCLUSIONS: Substantial investment in PHC institutions has not led to the expected efficiency gains. Therefore, more effective measures should be taken to improve the efficiency of PHC institutions in China based on local conditions. This study provides a new analytical approach to calculating the efficiency of PHC institutions, and this approach can be applied to efficiency evaluation either in other fields or in other countries. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12913-023-09979-3. BioMed Central 2023-09-15 /pmc/articles/PMC10503195/ /pubmed/37715162 http://dx.doi.org/10.1186/s12913-023-09979-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Su, Wanmin Hou, Yatian Huang, Mengge Xu, Jiamian Du, Qingfeng Wang, Peixi Evaluating the efficiency of primary health care institutions in China: an improved three-stage data envelopment analysis approach |
title | Evaluating the efficiency of primary health care institutions in China: an improved three-stage data envelopment analysis approach |
title_full | Evaluating the efficiency of primary health care institutions in China: an improved three-stage data envelopment analysis approach |
title_fullStr | Evaluating the efficiency of primary health care institutions in China: an improved three-stage data envelopment analysis approach |
title_full_unstemmed | Evaluating the efficiency of primary health care institutions in China: an improved three-stage data envelopment analysis approach |
title_short | Evaluating the efficiency of primary health care institutions in China: an improved three-stage data envelopment analysis approach |
title_sort | evaluating the efficiency of primary health care institutions in china: an improved three-stage data envelopment analysis approach |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10503195/ https://www.ncbi.nlm.nih.gov/pubmed/37715162 http://dx.doi.org/10.1186/s12913-023-09979-3 |
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