What has affected the governance effect of the whole population coverage of medical insurance in China in the past decade? Lessons for other countries

Front Public Health. 2023 Mar 30:11:1079173. doi: 10.3389/fpubh.2023.1079173. eCollection 2023.

Abstract

Objective: This study aimed to explore the current state of governance of full population coverage of health insurance in China and its influencing factors to provide empirical references for countries with similar social backgrounds as China.

Methods: A cross-sectional quantitative study was conducted nationwide between 22 January 2020 and 26 January 2020, with descriptive statistics, analysis of variance, and logistic regression models via SPSS 25.0 to analyze the effectiveness and influencing factors of the governance of full population coverage of health insurance in China.

Results: The effectiveness of the governance relating to the total population coverage of health insurance was rated as good by 59% of the survey respondents. According to the statistical results, the governance of the public's ability to participate in insurance (OR = 1.516), the degree of information construction in the medical insurance sector (OR = 2.345), the government's governance capacity (OR = 4.284), and completeness of the government's governance tools (OR = 1.370) were all positively correlated (p < 0.05) on the governance effect of the whole population coverage of health insurance.

Conclusions: The governance of Chinese health insurance relating to the total population coverage is effective. To effectively improve the effectiveness of the governance relating to the total population coverage of health insurance, health insurance information construction, governance capacity, and governance tools should be the focus of governance to further improve the accurate expansion of and increase the coverage of health insurance.

Keywords: governance effect; influence factors; medical insurance; medical insurance governance; population coverage.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Cross-Sectional Studies
  • Insurance, Health*
  • Logistic Models
  • Surveys and Questionnaires

Grants and funding

This study was funded by the National Natural Science Foundation of China (72074064 and 71573068), China Postdoctoral Science Foundation (2019M650068), China Postdoctoral Fund Special Grant Program (2018T110319), and the National Social Science Fund of China (19AZD013). The funding body did not influence the study design, data collection, data analysis, data interpretation, or writing of the manuscript.