HSRA2011 The Impacts of Health Insurance on Health Care Utilization Among the Elderly in China

Transcription

1 The Impacts of Health Insurance on Health Care Utilization Among the Elderly in China Xin Li, PhD Shanghai Jiao Tong University, China

2 Outline Background Literature Objectives Methods Results Conclusions

3 Background China s economic reforms have changed its health care system dramatically. Dramatic drop in the health insurance coverage

4 Health insurance system in China Urban employee basic medical insurance (UEBMI) Urban resident basic medical insurance (URBMI) New cooperative medical scheme (NCMS)

5 Health insurance system (cont d) Urban employee basic medical insurance (UEBMI) Launched in 1998 Employees in the state owned enterprises, the governme t and State institutions, all private and smaller public enterprises funding Two accounts Benefits structure Employer 6% of wage Employee 2% SRP 4.2% MSA 3.8% Inpatient Outpatient (MSA 3.8%)

6 Health insurance system (cont d) Urban resident basic medical insurance (URBMI) Launched in 2007 Primary and secondary school students, young children, and other unemployed urban residents funding Individual (majority) Government (no less than 40RMB) Benefits structure inpatient Outpatient services for chronic or fatal diseases

7 Health insurance system (cont d) New cooperative medical scheme (NCMS) Launched in 2003 Rural population funding Individual (up to 20RMB in 2008) Government (no less than 80RMB in 2008) two accounts MSA SRP Benefits structure Outpatient services for chronic or fatal diseases Inpatient

8 Literature Description of the system Liu. Health Policy 2002 You and Kobayashi. Evaluation of the system Wagstaff and Lindelow Lei and Lin Health Policy 2009 Henderson et al. Social Science & Medicine 1998 Liu et al. International Journal of Economic Development 1999 Gao et al. Health Policy 2007 Health Economics 2009 J of Health Economics 2008

9 Motivation Few have focused on the elderly China is on the fast track of aging Main users of health care services Less financial support

10 Objectives To examine how different types of health insurance programs (UEBMI, URBMI, NCMS and no insurance) affect the health care utilization among the elderly in China: the number of outpatient visits individual out-of-pocket (OOP) expenditure for the most recent doctor visit the length of stay (LOS) individual OOP expenditure for the last hospitalizatio

11 Data The survey of the China Health and Retirement Longitudinal Study (CHARLS Pilot) A broad-purposed social science and health survey of the elderly in China Data collected from July to September 2008 People aged 45 or older from two provinces of China: Zhejiang and Gansu Seven sections: Demographic Background; Family; Health Status and Functioning; Health Care and Insurance; Work, Retirement and Pension; Income, Expenditure and Assets; Interviewer Observation.

12 Survey design Within each province 16 county level units were randomly selected, stratified by regions and urban/rural Within each county 3 village level units were randomly selected as PSU Within each PSU dwelling units were randomly selected

13 Study sample CHARLS data includes 2685 respondents We have excluded: Respondents who had more than one insurance type Respondents who were younger than 45 years old Our sample includes 2377 respondents

14 Dependent variables The number of outpatient visits The individual outpatient OOP expenditure The number of nights spent (LOS) The individual inpatient OOP expenditure

15 Independent variables Key variables of interest: Insurance type (UEBMI, URBMI, NCMS, no insurance) Other variables Predisposing: age, gender, marital status, education and family size Enabling: region of country, household per-month living expenditure, health insurance Need: self-reported health status, disability, chronic diseases Life-style variables: physical activity, smoking behavior

16 Methods We employed two-part model to estimate the impacts of insurance For the number of outpatient visits and the LOS In the first part, we used a logistic model In the second part, we used zero-truncated Poisson model For the outpatient and inpatient OOP expenditures The first part was a logistic model The second part was generalized linear model (GLM) with a gamma distribution and a log link

17 Methods (cont d) We reported marginal effects of having UEBMI, URBMI, or no insurance vs. NCMS on the health care utilization We considered the design characteristics of survey data in the analysis Individual sample weights were used Regressions were run with weights Standard errors were estimated by bootstrapping

18 Respondents characteristics UEBMI URBMI NCMS No insurance Total Sample size (n) Population (n) 2,587, ,980 19,192,746 2,063,748 24,656,822 Proportion Age (y) 59.5 (10.0) 60.2 (10.3) 60.2 (10.1) 62.5 (13.1) 60.3 (10.4) Age Age Age Age= Male Province Zhejiang Gansu Education Illiterate Can read/writing Finish elementary school Junior high and above Married Monthly household expense ( ) 4,333.8 (1,423.61) 2,196.7 (237.65) 1,775.2 (92.60) 1,571.5 (215.09) 2,037.6 (186.28)

19 Health information UEBMI URBMI NCMS No insurance Total Sample size (n) Population (n) 2,587, ,980 19,192,746 2,063,748 24,656,822 Proportion Poor health status Having chronic diseases Having disabilities Physical activity Smoker

20 Health care utilization UEBMI URBMI NCMS No insurance Total Outpatient visit % of outpatient visit No. of visit (among those 2.4 (0.32) 1.8 (0.19) 2.3 (0.17) 2.1 (0.34) 2.3 (0.13) who had outpatient visit) OOP expenditure for the most recent visit ( ) Inpatient visit % of being hospitalized LOS for the last 15.3 (2.84) 14.4 (2.83) 12.9 (1.57) 6.7 (1.29) 13.2 (0.00) hospitalization OOP expenditure for the last hospitalization ( ) ( ) (564.33) ( ) (938.33)

21 Two-part economic model No. of outpatient visit last month UEBMI URBMI Part one: P(Y>0) Part two: Y Y>0 Overall ( )** ( )** ( ) ( )* ( )** ( ) No insurance ( ) ( ) ( ) Outpatient OOP for the recent visit UEBMI ( )** ( )** ( ) URBMI ( )** ( ) ( ) No insurance ( ) ( ) ( )*

22 Two-part economic model (cont d) LOS for the recent stay UEBMI URBMI Part one: P(Y>0) Part two: Y Y>0 Overall ( )* ( ) ( ) ( ) ( ) ( ) No insurance ( ) ( )** ( ) Inpatient OOP for the recent stay UEBMI ( )* -4, (-7, ,542.23) ( ) URBMI ( ) -4, (-6, ,818.37) ( ) No insurance ( ) (-5, ,615.04) ( )

23 Summary For the outpatient service People with UEBMI and URBMI are more likely to have outpatient visits compared with people with NCMS Among those who had at least one outpatient visit, people with UEBMI had significantly less OOP expenditure than people with NCMS The overall number of outpatient visits was significantly higher for people with UEBMI than for people with NCMS

24 Summary (cont d) For the inpatient care People with UEBMI are more likely to be hospitalized compared with people with NCMS Among those who had at least one inpatient visit, people without insurance had significant less LOS than people with NCMS There was no significant difference in inpatient spending for the four groups.

25 Thank You! 25