Determinants of access to health care in nine provinces of China: The impact of socioeconomic variables and the role of urban health insurance. Ysaline PADIEU July, 2010 Abstract This work focuses on the determinants of access to care when ill in Chinese urban areas. Access to care is interpreted here as utilization of health care services, outpatient as well as inpatient services. Using two waves of the China Nutrition and Health Survey, i.e. the 2000 and 2006 waves, probit estimations are used on cross-section individual datasets in order to determine the effects of socioeconomic variables and the role of insurance on access to health care. Key words: Health insurance, Access to care, Equity, China.
Introduction As President Hu Jin Tao declared in 2009 unveiling the new health reforms, ensuring equal and affordable access to health care as well as enhancing equity are among the major health issues China has to tackle by 2012 (Chen, 2009; Yip and Hsiao, 2009). Mooney and Legrand proposed several definitions of equity in health care provisions, four of them were studied by Wagstaff and Culyer (1993): equality of expenditure per capita, distribution according to need, equality of health and equality of access. I analyze in this work this last definition of equity and focus on the measure of horizontal equity, a concept defined by Wagstaff, van Doorslaer and Paci (1993) and explained in their article by the following sentence persons in equal need of medical care should receive the same treatment, irrespective of whether they happen to be poor or rich, old or young, black and white, and so on. In this study, access is interpreted as utilization of health care services when ill according to need. Need is measured here as the severity of illness affecting the individual. The objective of this article is to assess the impacts of socioeconomic variables and the role insurance on seeking care when ill using the most recent available datasets of the Chinese Health Nutrition Survey from 2000 and 2006. Two probit cross-section equations will be estimated in order to define the effects of the different types of insurance in urban areas on the likelihood of ill people to seek care. We assess the impacts of the Workers Compensation Insurance for the 2000 wave and the effects of three models of Urban Insurance (Urban Passway Model, Urban Block Model, Urban Catastrophic Model) in 2006. Brief History of Chinese health care system These insurances differ in several key characteristics such as the place of implementation, the coverage, the funding and the package of services and drugs that are offered. The Health program in China is based on the division between rural and urban areas. The New Cooperative medical insurance (NCMS) replaced the old scheme that covered agricultural workers under the pre-reform planned economy. After the collapse of the rural economy, the government implemented a new cooperative fund system, the NCMS, based on voluntary enrollment and financed by central and local government as well as by participants. The financing and the package of services vary across provinces.
In urban areas, the Urban Basic Insurance scheme was implemented in 1998 to replace the Labor Insurance Scheme (LIS), which covered state-owned enterprise workers. This new insurance covered urban employees but did not cover dependents and migrants for most cities. Both employers and employees finance this insurance and the funds are divided into a medical saving account and a social pooling fund. In 2007, the basic medical insurance system for urban residents was implemented in order to cover the majority of urban population without insurance. The urban scheme was then declined in three main models that are studied in this work: the Urban Passway model, the Block model and the Catastrophic Disease Model. New reforms were announced in April 2009 whose aim is to increase coverage in order to enroll all rural populations in the New Cooperative Medical Scheme and all urban residents in the Basic Medical Insurance scheme for urban residents. Using data from two years 2000 and 2006, this work will focus on the effect of the Urban Basic Medical Care for the 2000 wave, but also on the impacts of the three types of urbanimplemented schemes (the Passway Model, the Block Model and the Catastrophic Disease Model) for the 2006 wave. Literature Review If the effect of health care insurance has been studied on both health care consumption and health expenses, the conclusions of the literature review on these effects remain mitigated. Henderson et al. (1999) study the determinants of health care utilization using data from the first three waves of the Chinese Nutrition and Health Survey conducted in 1989, 1991 and 1993 for both urban and rural areas. They use probit estimations and control for the health insurance endogeneity. They find no impact of health care insurance, namely Government Insurance and Labor Insurance, on seeking care when ill in 1989 and 1991, whereas for 1993 people with Labor Insurance seem less likely to consume health care when ill than people without insurance. Liu and Zhao (2002) focus on the impact of insurance reform on Health care access at different settings in Zhenjiang from 1994 through 1996. They observe a significant rise in outpatient care utilization by the lower socio-economic groups. As regards to rural areas, Zhou et al. (2009) study the problem of unaffordable and difficult access to health care ( Kan Bing nan, Kan bing gui ) in Chinese Rural areas from 2004 to
2006 after the implementation of Harvard research insurance project called Rural Mutual Health care. Using panel data, they conclude that coverage of outpatient services has a positive effect on outpatient care consumption. However using the CHNS data, Lei and Lin (2009) find that the New Cooperative Medical System increases the consumption of preventive care but does not have any effect on formal medical services. Data The China Health and Nutrition Survey was conducted by the Carolina Population Center at the University of North Carolina at Chapel Hill and the National Institute of Nutrition and Food Safety at the Chinese Center for Disease Control and Prevention. The China Health and nutrition Survey uses a multistage, random cluster process to draw a sample of households and individuals. This dataset gathers data from nine Chinese provinces (Liaoning, Heilongjiang, Jiangsu, Shandong, Henan, Hubei, Hunan, Guangxi and Guizhou), which are mostly located in Eastern and Central China from 1989 to 2006. These provinces present different economic and geographic key characteristics and represent a relatively representative sample of China. The China Health Nutrition Survey provides household and individual data on their social and geographical characteristics, health care consumption, payments as well as their insurance coverage modalities. Moreover, CHNS includes both urban and rural data and provides information only about the month preceding the date of interview. Method and Model In this work, I use a probit estimation on cross-section urban individual datasets in order to define the determinants of access to health care and to highlight the role of urban insurance among these causal variables. The aim of this study was mostly influenced by the previous article of Henderson, Akin, Hutchinson, Jin, Wang, Dietrich and Mao (1998). However, this study will focus on two cross-section datasets from 2000 and 2006. Henderson and al. questioned in their work the endogeneity of insurances. They use the method of instrumental variables in order to assess whether if the variables of insurance are not correlated with the error term of the equation of access to care. The problem of endogeneity is important in case of voluntary enrollment: for example in the case of Cooperative Medical Insurance for rural areas or Commercial insurances. However, in urban
areas, individuals are insured as soon as they work, thus I do not question the endogeneity of urban health insurances. Variables In this study I use two waves of the China Health and Nutrition Survey (2004 and 2006). The studied population will only include people that declared to be ill during the 4 last weeks preceding the survey. The dependent variable is a dichotomous variable indicating if the ill individual chose whether to seek care or not (respectively 1 and 0 for each situation) during the last four weeks preceding the interviews. This variable measures access to care when ill. It includes all levels of care (outpatient and inpatient care) for all care facilities (different types of clinic, hospitals and planning services). The variables of interest are the variables of insurance. In 2000, the variable of interest is the Workers Compensation Insurance. In 2006, the Workers Compensation Insurance is declined in 3 different models of workers Insurance: the Urban Passway Insurance, the Block Model Insurance and the Catastrophic Disease Insurance. Control variables include demographic and geographic variables variables (age, gender, place of residence), socio economic variables (wealth, jobs, years of education completed), illness characteristics (severity of illness, time to go to the nearest care institution, by bike) and household specificities (household size). These variables are all defined in the Table 1 and descriptive statistics are available in Tables 2.1 and 2.2. The China Health Nutrition Survey provides a measure of self-reported income but as this variable is likely to be misreported, I use a multiple components analysis to construct an asset-based index. To measure this MCA-based index, I select several variables provided information on asset ownership (Bicycle, Motorcycle, Radio, Color TV, Washing Machine, Fridge, Air Conditioner, Sewing Machine, Electric fan, Camera, Electric Rice Cooker, Pressure Cooker, Telephone, VCD-DVD, but also cellphone and satellite dish when information was available), sources of water supply and sanitation facilities. From this constructed index, categorical variables identifying quintiles were computed.
Table 1: Definition of Variables Variables Access to care Age Wealth Education Definition of Variables Independant Variable: dummy variable = '0' if the ill individual does not seek care during the past month ='1'if the ill individual seeks care during the past month Age groups: 16-24/25-34/35-54/55 and above Number of assets owned by the individual's household Type of assets: Radio tape recorder/ Video Cassette Recording/ Black/White television/ Color Television/ Washing Machine/ Refrigerator/ Air Conditioner/ Sewing Machine/ Electric Fan/ Computer/ Camera/ Microwave oven/ Electric Rice/ DVD/ Satellite Dish Years of education Insurance Cooperative Insurance (2004 & 2006) Workers Conpensation Insurance (2004) Urban Passway Model (2006) Urban Block Model (2006) Urban Catastrophinc Disease Model (2006) Severity of illness Travel Time Travel Cost Average Wait Self assessed severity of the illness occured in the past month Not severe/ Moderatly severe/ Quite severe Time of travel by bike to go to the nearest care institution Transport Cost to go to the nearest institution (RMB) Average wait to be seek by the practionnal at the nearest institution Place of residence Urban: City and Suburbs Rural: Towns and villages Source: China Health and Nutrition Survey
Table 2.1: Proportion of population having the following characteristics who sought care during the last four weeks 2000 2006 N % N % Age 18-25 33 73,33 51 66,23 25-35 9 52,94 23 56,10 35-55 68 64,15 106 51,71 Above 102 64,56 208 49,48 Gender Female 122 67,03 230 53,36 Male 90 62,03 158 51,13 Education No school 47 61,04 87 61,27 Primary 80 62,50 147 58,57 Lower Middle school 54 64,29 108 48,87 Upper Middle 212 65,03 388 52,43 College University 31 83,78 46 36,51 Occupation Administrator/executive/manager 54 55,8 8 44,84 Marital Status Married 134 61,65 258 48,22 Province Liaoning 12 92,31 29 22,14 Heilongjiang 11 64,61 22 44 Jiangsu 19 26,03 30 46,15 Shandong 20 80 45 69,23 Henan 34 85 68 85,71 Hubei 31 72,09 73 77,27 Hunan 25 73,53 47 48,96 Guangxi 24 63,16 32 51,61 Guizhou 36 83,72 42 56,96 Source : China Health and Nutrition Survey
Table 2.2: Proportion of population having the following characteristics who sought care during the last four weeks 2000 2006 N % N % Health Insurance Uninsured 122 69,71 208 56,68 Insured 89 60,96 180 48,26 Type of Insurance Commercial insurance 53 63,7 20 62,5 Workers compensation Insurance 29 42,65 - Urban EMI: Passway Model 36 47,37 Urban EMI: Block Model 38 30,89 Urban EMI: Catastrophic Disease 19 45,24 Free Medical Insurance 36 73,47 28 50,91 Severity of illness Not severe 101 67,33 109 38,93 Moderatly severe 75 74,26 193 54,52 Quite severe 18 69,23 65 76,47 Access to facilities Travel Time>20 minutes 82 62,60 270 52,84 Travel Time<20 minutes 130 66,67 503 60,63 Source : China Health and Nutrition Survey Probit Estimations Table 3 reports the main results of cross-sections probit estimations. Control variables In 2000 age is not significantly related to heath care utilization, while in 2006 age has no significant impact on health care utilization. A disaggregation of this variable shows that 18-35 year-old people are more likely to use health care services than the oldest (55 year-old and above). Findings on gender show than being a woman is positively related to seeking care in 2000, while it is not significantly related to the dependent variable in 2006.
As regards the variable of wealth, we observe that the richest three quintiles are more willing to seek care than the poorest quintile in 2000. This trend increases according to the wealth of the quintile. However, this effect is not significant for the wave of 2006. As regards education, the variable indicated the number of completed years is significantly and positively related to health care consumption in 2000, while in it is negatively related in 2006. People employed as an administrator, an executive or a manager (a working proprietor, a government official, a section chief, a department or a bureau director, an administrative cadre, a village leader) do not seem to have a greater tendency to seek care than other people. In terms of place of residence, results suggest that people from cities are not significantly more likely to seek care than people from suburbs. As regards the variable of need, we observe that in 2006 people suffering from a more severe disease are more likely to seek care than others, however in 2000 people affected by moderately severe disease are more willing to consume health care services than the others. Interest variables In 2004 people with workers insurance are less likely to seek care than people without insurance. In addition to this conclusion, we observe that individuals with the Urban Block Model have significantly lower tendencies to seek care than people with no insurance. We do not find any significant impact of the Urban Passway Model and the Urban Catastrophic Disease model. Discussion This work focuses on the role of insurance on access to care when ill. Access to care is interpreted here as utilization of health care services, outpatient as well as inpatient services. Using the last two waves of the China Nutrition and Health Survey, i.e. the 2004 and 2006 waves, probit estimations are used on cross-section individual datasets. In terms of equity, results of the probit estimations on control variables are mixed. For both waves, severity of illness has a significant impact on the probability of seeking care for both years. As regards gender, women are more likely to consume health care services than men. The variable of access to health care when ill does not include preventive health care and so gynecological, prenatal and postnatal examinations, which could have an influence on the preceding results. Findings for the 2006 wave on age show that the younger individuals are, the more likely they will seek care.
In terms of wealth, measured here by an MCA-based index, the three richest quintiles seem to consume more health services when ill than the poorest quintile in 2000, which means that for this period and these individuals, poor and rich do not have the same access to health care. However, in 2006, we do not observe any significant impact of wealth on access to health care when ill, suggesting that this inequality has been reduced. As regards education findings are opposite for the two waves, we observe a positive impact on access to health care in 2000 and a negative impact in 2006 which suggests an education inequality in access to health consumption favoring high educated individuals in 2000 and low educated individuals in 2006. In terms of job status, working as administrator executive or manager, and so benefiting from additional government insurance is not likely to increase the consumption of health care. Henderson et al. found the same results for the 1989, 1991 and 1993 waves, but for both urban and rural areas. In conclusion, people with higher income and high education were more likely to seek care than others in urban areas in 2000. In 2006 people with lower socioeconomic status seem to be less disadvantaged. Less educated individuals have a better access to health care for this last wave and people with poorer wealth index were as likely to seek care as others. Socioeconomic inequity of access to health care seems to have decreased over the studied period even if younger people have a greater access to health care in 2006. As regards urban health insurances, individuals with a Workers Compensation Insurance experienced a decline of access to care in 2000. Moreover, individuals with a Urban Block model are less likely to seek care than other individuals, while Catastrophic Disease model and the Passway model are not significantly related to seeking care. However these negative results could be toned down as we observe at the same time a reduction of socioeconomic inequality of health care access. Acknowledgements This research uses data from China Health and Nutrition Survey (CHNS). We thank the National Institute of Nutrition and Food Safety, China Center for Disease Control and Prevention, Carolina Population Center, the University of North Carolina at Chapel Hill, the NIH (R01-HD30880, DK056350, and R01-HD38700) and the Fogarty International Center,
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