Equity of outpatient service utilization for hypertensive patients in community.
10.11817/j.issn.1672-7347.2018.06.015
- Author:
Min XU
1
;
Xiaowan WANG
1
;
Zengwu WANG
2
,
3
;
Jian LI
1
;
Ruihua FENG
1
;
Yueying CUI
1
Author Information
1. Department of Health Economics, Institute of Medical Information, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, China.
2. Fuwai Hospital, Chinese Academy of Medical Sciences
3. Division of Community Prevention, National Center for Cardiovascular Diseases, Beijing 102308, China.
- Publication Type:Journal Article
- MeSH:
Adolescent;
Ambulatory Care;
economics;
statistics & numerical data;
China;
Healthcare Disparities;
economics;
statistics & numerical data;
Humans;
Hypertension;
therapy;
Insurance, Health;
economics;
statistics & numerical data;
Outpatients;
statistics & numerical data;
Rural Health Services;
economics;
statistics & numerical data;
Socioeconomic Factors;
Urban Health Services;
economics;
statistics & numerical data
- From:
Journal of Central South University(Medical Sciences)
2018;43(6):668-678
- CountryChina
- Language:Chinese
-
Abstract:
To analyze the equity of outpatient service utilization for hypertensive patients (HPs) under 3 kinds of social medical insurance, and to explore its influential factors.
Methods: A total of 8 670 HPs (aged at 15 years old from 28 sub-centers) in 14 provinces were selected. Indirectly standardized method and concentration index were used to analyze the equity of outpatient utilization in HPs, and decomposition analysis was used to explore the impact factors of outpatient treatment among the whole sample population, population with urban employees' basic medical insurance (UEBMI), and population with urban residents' basic medical insurance (URBMI) and new rural cooperative medical systems (NCMS).
Results: The overall concentration index (CI) for the whole sample population was 0.2378. After the standardizing "need" variable, horizontal inequity (HI) was 0.2360, indicating that the outpatient service of HPs was inequity and that the higher economic level, the more outpatient services received. The decomposition of overall CI results showed that the positive factors for contribution were gross domestic product (GDP) level, retired, UEBMI and URBMI, and the negative factors for contribution were NCMS. The CI of UEBMI, URBMI and NCMS was 0.2017, 0.1208 and 0.0288, respectively; the HI was 0.1889, 0.1215 and 0.0219, respectively. The inequity in UEBMI is the most serious, followed by NRCMS and URBMI. The economic level was the main factor that caused inequity in the outpatient services utilization in three social medical insurance. In addition to the economic level, a common positive factor for the contribution to UEBMI and URBMI was district of residence, and the age was the positive factor to UEBMI as well.
Conclusion: There are different levels of inequity in the HPs covered by 3 kinds of social medical insurance, and the inequity of UEBMI is the highest one among 3 kinds social medical insurance. The economic level is the main factor that affects the equity of outpatient in the HPs under 3 kinds of social medical insurance.
