社区高血压患者门诊服务利用的公平性分析

目的：分析3种社会医疗保险(以下简称医保)覆盖下高血压患者门诊服务利用的公平性，并探讨其影响因 素。方法：选取14个省(市、自治区)28个分中心社区的8 670名15岁及以上的高血压患者作为研究对象，采用间接标 化法和集中指数分析高血压患者门诊服务利用的公平性，并采用集中指数分解法分别探讨整个样本人群以及城镇职 工医保、城镇居民医保和新型农村合作医疗(以下简称为新农合)医保样本人群门诊就诊不公平的影响因素。结果： 整个样本人群的门诊服务利用的集中指数为0.2378。标化“需要”变量后，门诊就诊水平不公平指数为0.2360。整个 样本人群集中指数分解法显示：门诊服务利用集中指数贡献率较大且为正向贡献的因素为人均GDP水平、离退休、 城镇居民医保、城镇职工医保；贡献率较大且为负向贡献的因素为新农合医保。城镇职工医保、城镇居民医保、新 农合医保样本人群门诊服务利用的集中指数分别为0.2017，0.1208和0.0288；控制“需要”变量的影响后，其水平不 公平指数分别为0.1889，0.1215和0.0219，均存在不同程度的亲富不公平，以城镇职工医保不公平程度最高，其次是 城镇居民医保和新农合医保。经济水平是造成3种社会医保样本人群门诊服务利用不公平的主要因素。除经济水平 外，城镇职工和城镇居民的共同正向贡献因素为居住地。年龄是城镇职工医保样本人群的正向贡献因素。结论：3 种社会医保覆盖下高血压患者均存在不同程度的亲富不公平，且以城镇职工医保样本人群门诊就诊的不公平程度最 高。经济水平是影响3种社会医保覆盖下高血压患者门诊就诊公平性的主要因素。

Equity of outpatient service utilization for hypertensive patients in community

Objective: 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.