New Health Care Reform and Impoverishment among Chronic Households in China: A Random-Intercept Approach

Int J Environ Res Public Health. 2019 Mar 26;16(6):1074. doi: 10.3390/ijerph16061074.

Abstract

High out-of-pocket (OOP) payments for chronic disease care often contribute directly to household poverty. Although previous studies have explored the determinants of impoverishment in China, few published studies have compared levels of impoverishment before and after the New Health Care Reform (NHCR) in households with members with chronic diseases (hereafter referred to as chronic households). Our study explored this using data from the fourth and fifth National Health Service Surveys conducted in Shaanxi Province. In total, 1938 households in 2008 and 7700 households in 2013 were included in the analysis. Rates of impoverishment were measured using a method proposed by the World Health Organization. Multilevel logistic modeling was used to explore the influence of the NHCR on household impoverishment. Our study found that the influence of NHCR on impoverishment varied by residential location. After the reform, in rural areas, there was a significant decline in impoverishment, although the impoverishment rate remained high. There was little change in urban areas. In addition, impoverishment in the poorest households did not decline after the NHCR. Our findings are important for policy makers in particular for evaluating reform effectiveness, informing directions for health policy improvement, and highlighting achievements in the efforts to alleviate the economic burden of households that have members with chronic diseases.

Keywords: China; chronic diseases; impoverishment; new health care reform; out-of-pocket expenditure.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Chronic Disease / economics*
  • Family Characteristics
  • Female
  • Health Care Reform / economics*
  • Health Expenditures / statistics & numerical data
  • Health Policy
  • Health Surveys
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • National Health Programs
  • Poverty / statistics & numerical data*
  • Rural Population / statistics & numerical data
  • Urban Population / statistics & numerical data