The Comparison of Various Types of Health Insurance in the Healthcare Utilization, Costs and Catastrophic Health Expenditures among Middle-Aged and Older Chinese Adults

Int J Environ Res Public Health. 2022 May 13;19(10):5956. doi: 10.3390/ijerph19105956.

Abstract

Rapid aging in China is increasing the number of older people who tend to require health services for their poor perceived health. Drawing on the China Health and Retirement Longitudinal Study (CHARLS) 2018 data, we used two-part model and binary logistic regression to compare various types of health insurance in the healthcare utilization, costs and catastrophic health expenditures (CHE) among the middle-aged and older adults in China. Compared with uninsured, all types of health insurance promoted hospital utilization rate (ranged from 8.6% to 12.2%) and reduced out-of-pocket (OOP) costs (ranged from 64.9% to 123.6%), but had no significant association with total costs. In contrast, the association of health insurance and outpatient care was less significant. When Urban Employee Medical Insurance (UEMI) as reference, other types of insurance did not show a significant difference. Health insurance could not reduce the risk of CHE. The equity in healthcare utilization improved and healthcare costs had been effectively controlled among the elderly, but health insurance did not protect against CHE risks. Policy efforts should further focus on optimizing healthcare resource allocation and inclining toward the lower socio-economic and poor-health groups.

Keywords: China; catastrophic health expenditures; health insurance; health utilization; older adults.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • China
  • Delivery of Health Care
  • Health Expenditures*
  • Humans
  • Insurance, Health*
  • Longitudinal Studies
  • Middle Aged
  • Patient Acceptance of Health Care

Grants and funding

This study was supported by the National Natural Science Foundation of China (grant number #71974212) and Guangdong Basic and Applied Basic Research Foundation (grant number # 2020A1515010737).