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Background: China has since the beginning of this millennium engaged in substantial Universal Health Coverage (UHC) reforms. This paper adds evidence on how equity in level of health service utilization changed after UHC reforms. Methods: Our study was based on household survey data from 30 counties in Sichuan province in 2004 and 2011. We introduce an unusual outcome variable, namely level of healthcare utilization. Concentration index (CI) was used to measure income based inequality in level of healthcare utilization. Horizontal index (HI) was used to assess whether inequalities are inequitable. We decomposed the concentration index to measure the factors contributing to inequality in level of utilization. Oaxaca type decomposition was applied to control whether identified changes were attributable to changed inequality or to other factors. Results: Pro-rich inequity in level of healthcare utilization increased after UHC reforms. Overall, a higher proportion of users sought services at county hospitals or higher in 2011 compared with 2004. Richer users were considerably more likely than the poor to seek care at hospitals rather than at clinics or health centers, and the pro-rich inequality in level of healthcare utilization was highly inequitable. Insurance enrollment became the main driver of pro-rich inequity in level of healthcare utilization after reforms, while health needs became less important for determining level of care, all disfavoring low income groups. Conclusions: Assessments of equity should pay attention to inequalities in level of healthcare utilization. Our results indicate that in China, wide insurance coverage is insufficient to ensure equity in level of healthcare utilization. On the contrary, type of insurance enrollment has become a main driver of inequity in level of utilization. Hence, equalizing health insurance schemes would be of crucial importance in order to improve health equity in China. Moreover, UHC reforms should strengthen the primary sector and limit non-needs based use of high-level hospitals in order to promote equitable use of healthcare services. [ABSTRACT FROM AUTHOR]

Objective: By analyzing the gap of hospitalization service among floating population covered by different medical insurance in Jiangsu Province, this paper aimed to understand the current situation of hospitalized health service utilization (HHSU) among floating population, and to provide policy suggestions for improving HHSU of floating population with different health insurance. Methods: The data of this study were obtained from "the National Dynamic Monitoring Survey of Floating Population in 2014". A total of 12,000 samples of floating population in Jiangsu Province were selected. 57.15% for men and 42.85% for women; 46.95% for those under 30 years old, 39.67% for 30 to 45 years old, 13.38% for over the age of forty-five. Using descriptive statistical analysis, chi-square test, exploratory factor analysis, logistic regression and stepwise multiple linear regression, the paper analyzed the difference of HHSU of floating population with different medical insurance in 2014. This study divided basic medical insurance into 3 categories: MIUE (Medical Insurance of Urban Employee), other medical insurances (including new rural cooperative medical system and the medical insurance for urban residents) and no medical insurance. Results: The hospitalization rate of floating population with MIUE (89.95%) was higher than the rate of floating population with other medical insurances (74.76%) and the gap is 15.19%. It was also higher than the rate of floating population with no medical insurance (67.57%) and the gap is 22.38%. (chi-square = 24.958, p = 0.000). 15.34% of floating population with MIUE spent more than 1600 dollars during hospitalization. It was lower than floating population with other medical insurances (16.19%) and no medical insurance (21.62%). The gaps respectively were 0.85 and 6.28% (chi-square = 10.000, p = 0.040). There existed significant differences among hospitalization medical expenses that floating population with different basic medical insurances spent. (chi-square = 225.206, p = 0.000) The type of basic medical insurance had statistical significance on whether the patients were hospitalized (p = 0.003) and whether they were hospitalized (p = 0.014). Logistic regression analysis results showed that "Social structure" (Education, Hukou, Insurance status and Work status) were significantly associated with Should be hospitalized but not and "Education" were significantly associated with Inpatient facilities selection. The stepwise multiple linear regression results presented that "Demography" and "Floating area" influenced In-hospital medical cost and "Social structure" and "Gender" influenced Reimbursement of in-hospital medical cost. Conclusion: Medical insurance type affects the hospitalization health service utilization of floating population, including Should be hospitalized but not and Reimbursement of in-hospital medical cost. [ABSTRACT FROM AUTHOR]