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Background: The accessibility and fairness of the floating population's access to basic public health services have an important impact on improving the health level of the whole population. Existing studies have shown that medical insurance and social integration have an impact on basic public health services, but there are few studies on the specific influence path between the three. Therefore, the research purpose of this paper is to explore the effects of medical insurance for urban and rural residents and basic medical insurance for urban employees on the utilization of basic public health services, and to analyze the mediating effect of social integration. Methods: The data in this paper are derived from the 2017 China Mobile Population Dynamic Monitoring Survey data, which collects information on 31 provinces (regions, cities) and Xinjiang Production and Construction Corps mobile population 169,989 people, all of whom come from China's relatively concentrated mobile population inflow areas (NHC FPSCo. 2021. Floating Population Service Center of NHC). After deleting part of the missing data and replacing the mean value, 154,586 people were finally included in the analysis. The proportion is 90.9%. Based on the data of China's floating population dynamic survey in 2017,we used Logistic regression method to analyze the effects of basic medical insurance for urban and rural residents, basic medical insurance for urban employees and social integration on the utilization of basic public health services. Then we used the Bootstrap method of structural equation model to analyze the mediating effect of social integration. Results: Medical insurance for urban and rural residents (β = 0.236;95%CI:1.195 ~ 1.342) has positive impact on health education, it (β = 0,190;95%CI:1.150 ~ 1.272) also has positive impact on the establishment of residents' health records. Social integration (including political participation (β = 0.312;95%CI:1.324 ~ 1.410),activity participation (β = 0.724;95%CI:2.009 ~ 2.119), identity (β = 0.421; 95%CI:1.387 ~ 1.675))has positive impact on health education, it ((β = 0.312;95%CI:1.324 ~ 1.410), (β = 0.404;95%CI:1.463 ~ 1.534), (β = 0.282;95%CI:1.191 ~ 1.477)) also has positive impact on the establishment of residents' health records. In addition, BMIUE (β = 0.169;95%CI:1.150 ~ 1.219) has an impact on the establishment of residents' health records. The direct effect of medical insurance on the utilization of public health services was 0.092 (95%CI: 0.093 ~ 0.103), social integration was a partial mediator, the mediating effect was 0.127 (95%CI: 0.108 ~ 0.127), and the mediating effect size was 57.73%. Conclusions: Medical insurance can directly promote the floating population to use basic public health services, and can indirectly promote the improvement of public health service utilization level through social integration. [ABSTRACT FROM AUTHOR]

Background: The inequity of healthcare utilization in rural China is serious, and the urban-rural segmentation of the medical insurance system intensifies this problem. To guarantee that the rural population enjoys the same medical insurance benefits, China began to establish Urban and Rural Resident Basic Medical Insurance (URRBMI) nationwide in 2016. Against this backdrop, this paper aims to compare the healthcare utilization inequity between URRBMI and New Cooperative Medical Schemes (NCMS) and to analyze whether the inequity is reduced under URRBMI in rural China. Methods: Using the data from a national representative survey, the China Health and Retirement Longitudinal Study (CHARLS), which was conducted in 2015, a binary logistic regression model was applied to analyze the influence of income on healthcare utilization, and the decomposition of the concentration index was adopted to compare the Horizontal inequity index (HI index) of healthcare utilization among the individuals insured by URRBMI and NCMS. Results: There is no statistically significant difference in healthcare utilization between URRBMI and NCMS, but in outpatient utilization, there are significant differences among different income groups in NCMS; high-income groups utilize more outpatient care. The Horizontal inequity indexes (HI indexes) in outpatient utilization for individuals insured by URRBMI and NCMS are 0.024 and 0.012, respectively, indicating a pro-rich inequity. Meanwhile, the HI indexes in inpatient utilization under the two groups are − 0.043 and − 0.028, respectively, meaning a pro-poor inequity. For both the outpatient and inpatient care, the inequity degree of URRBMI is larger than that of NCMS. Conclusions: This paper shows that inequity still exists in rural areas after the integration of urban-rural medical insurance schemes, and there is still a certain gap between the actual and the expected goal of URRBMI. Specifically, compared to NCMS, the pro-rich inequity in outpatient care and the pro-poor inequity in inpatient care are more serious in URRBMI. More chronic diseases should be covered and moral hazard should be avoided in URRBMI. For the vulnerable groups, special policies such as reducing the deductible and covering these groups with catastrophic medical insurance could be considered. [ABSTRACT FROM AUTHOR]

Objective: We describe awareness about the modified "public charge" rule among Oregon's Mexican-origin Latino/a population and whether concerns about the rule influenced disenrollment from state-funded programs, which do not fall under the public charge. Methods: We conducted a cross-sectional survey of adults (ages 18–59) recruited at the Mexican consulate and living in the state of Oregon. Our outcomes were awareness (of the public charge, source of knowledge, and confidence in knowledge of the public charge) and disenrolling self or family members from state-funded public healthcare programs due to concerns about the rule. We described outcomes and used logistic regression and calculated adjusted probabilities to identify factors associated with awareness of the public charge. Results: Of 498 Latino/a respondents, 48% reported awareness of the public charge. Among those who knew about the public charge, 14.6% had disenrolled themselves or family members from public healthcare programs and 12.1% were hesitant to seek care due to concerns about the public charge. Younger respondents had a lower adjusted probability of awareness of the public charge (18–24 years: 15.6% (95% CI 3.1–28.2); 30–39 years 54.9% (95% CI 47.7–62.0). Higher education was associated with a higher adjusted probability of awareness of the public charge; ability to speak English was not associated with awareness of the public charge. Conclusion: Our study reveals limited awareness about the public charge among Mexican-origin Oregon Latino/as. Outreach and advocacy are essential to ensure Latino/as know their rights to access available state-funded healthcare programs. [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]