Literature DB >> 33507961

An integrated model for evaluation of maternal health care in China.

Qianlong Zhao1, Junyi Chen2, Fulun Li3, Aishu Li1, Qian Li1.   

Abstract

In recent years, in the context of China's continuous medical and health reforms, the health status of Chinese women and children has been significantly improved through the continuous efforts of staff at all levels of maternal and child health care institutions. Many indicators in maternal health care have improved significantly, but the speed and magnitude of changes have varied. The purpose of this study is to evaluate the dynamic changes in China's maternal health status from 2004 to 2018, in order to determine whether China's medical and health reform measures in recent years have improved maternal health. A total of 6 evaluation indicators from the data of China Health Statistics Yearbook 2019 were selected. Then, based on the multi-criteria decision-making (MCDA) methodology, the entropy weighted technique for order preference by similarity to an ideal solution (TOPSIS), entropy weighted rank-sum ratio (RSR) method and the fuzzy comprehensive evaluation were employed in this study. In addition, sensitivity analysis was engaged to validate the stability and accuracy of the achieved results. The study results shows the ranking values of various methods were not exactly the same, but the overall trend was consistent. Overall, the maternal health care in China improved from 2004 to 2018 year by year, of which the top four were ranked from 2015 to 2018, and relatively poor from 2004 to 2006. This means that the policies and measures implemented in China's medical and health reform in the past few decades have effectively promoted China's maternal health care, and this will also provide a theoretical basis for future decisions to promote maternal health care.

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Year:  2021        PMID: 33507961      PMCID: PMC7842919          DOI: 10.1371/journal.pone.0245300

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  33 in total

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  3 in total

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