Influence of population aging on balance of medical insurance funds in China

Int J Health Plann Manage. 2020 Jan;35(1):152-161. doi: 10.1002/hpm.2844. Epub 2019 Jul 3.

Abstract

Purpose: The increasing intensification of population aging can affect the balance of social medical insurance funds, an issue that has aroused much research attention. Against this background, this paper studies the impact of population aging on the balance of medical insurance funds in China.

Findings: With the introduction of six intermediate variables, ie, economic level, dependency ratio of the elderly population, physical condition, medical demand, medical expenses, and medical resources, a structural equation model is constructed. Then, the relations among these variables are analyzed to explore how population aging affects the medical insurance fund balance. The direct impact of aging is found not to be significant. Physical condition, medical resources, and medical demand are intermediate variables that can affect the relationship.

Conclusion: The results show that population aging does not have a significant impact on the balance of the medical insurance fund. However, China's aging trend suggests that the population aging level is very likely to continue to intensify in the future. Moreover, the proportion of revenue in the medical insurance fund is progressively declining, and population aging may threaten the balance between revenue and expenditure. Finally, based on the above analysis, several corresponding recommendations and future studies are proposed.

Keywords: Chinese balance of medical insurance fund; population aging; structural equation model.

MeSH terms

  • Aged
  • China
  • Forecasting
  • Health Expenditures / statistics & numerical data
  • Health Expenditures / trends
  • Health Services Needs and Demand / economics
  • Health Services Needs and Demand / statistics & numerical data
  • Health Services Needs and Demand / trends
  • Healthcare Financing*
  • Humans
  • Insurance, Health / economics*
  • Insurance, Health / statistics & numerical data
  • Insurance, Health / trends
  • Population Dynamics / statistics & numerical data*
  • Population Dynamics / trends