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2008 年至 2018 年期间中国医疗保险间和医疗保险内医疗利用差距的变化趋势:一项重复的横断面研究。

Trends in disparities in healthcare utilisation between and within health insurances in China between 2008 and 2018: a repeated cross-sectional study.

机构信息

School of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.

Institute of Medical Information, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100020, China.

出版信息

Int J Equity Health. 2022 Feb 24;21(1):30. doi: 10.1186/s12939-022-01633-4.

DOI:10.1186/s12939-022-01633-4
PMID:35209916
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8876177/
Abstract

BACKGROUND

Fragmentation in China's social health insurance schemes and income gap have been recognised as important factors for the inequitable use of healthcare. This study assessed trends in disparities in healthcare utilisation between and within health insurances in China between 2008 and 2018.

METHODS

We used data from the 2008, 2013, and 2018 China National Health Services Survey. Outpatient visit, inpatient admission and foregone inpatient care were chosen to measure healthcare utilisation and underutilisation by health insurances. Absolute differences and rate ratios were generated to examine disparities between and within health insurances, and changes in disparities were analysed descriptively. Pearson χ2 tests were used to test for statistical significance of differences.

RESULTS

The outpatient visit rate for respondents covered by the urban resident-based basic medical insurance scheme (URBMI) more than doubled between 2008 and 2018, increasing from 10.5% (9.7-11.2) to 23.5% (23.1-23.8). Inpatient admission rates for respondents covered by URBMI and the new rural cooperative medical scheme (NRCMS) more than doubled between 2008 and 2018, increasing by 7.2 (p < 0.0001) and 7.4 (p < 0.0001) percentage points, respectively. Gaps in outpatient visits and inpatient admissions narrowed across the urban employee-based basic medical insurance scheme (UEBMI), URBMI, and NRCMS through 2008 to 2018, and by 2018 the gaps were small. The rate ratios of foregone inpatient care between NRCMS and UEBMI fell from 0.9 (p > 0.1) in 2008 to 0.8 (p < 0.0001) in 2018. Faster increases in outpatient and inpatient utilisation and greater reductions in foregone inpatient care were observed in poor groups than in wealthy groups within URBMI and NRCMS. However, the poor groups within UEBMI, URBMI, and NRCMS were always more likely to forego inpatient care in comparison with their wealthy counterparts.

CONCLUSIONS

Remarkable increases in healthcare utilisation of URBMI and NRCMS, especially among the poorest groups, were accompanied by improvements in inequality in healthcare utilisation across UEBMI, URBMI, and NRCMS, and in income-based inequality in healthcare utilisation within URBMI and NRCMS. However, the poor groups were always more likely to forego admission to hospital, as recommended by doctors. We suggest further focus on the foregoing admission care of the poor groups.

摘要

背景

中国社会医疗保险计划的碎片化和收入差距已被认为是医疗保健不公平利用的重要因素。本研究评估了 2008 年至 2018 年期间中国医疗保险之间和内部医疗保健利用不平等的趋势。

方法

我们使用了 2008 年、2013 年和 2018 年中国国家卫生服务调查的数据。选择门诊就诊、住院和放弃住院治疗来衡量医疗保险的医疗利用和利用不足。生成绝对差异和比率比来检查医疗保险之间和内部的差异,并描述性地分析差异的变化。使用 Pearson χ2 检验测试差异的统计学意义。

结果

参加城镇居民基本医疗保险(URBMI)的受访者的门诊就诊率在 2008 年至 2018 年间翻了一番多,从 10.5%(9.7-11.2)增加到 23.5%(23.1-23.8)。参加 URBMI 和新型农村合作医疗(NRCMS)的受访者的住院率在 2008 年至 2018 年间也翻了一番多,分别增加了 7.2(p<0.0001)和 7.4(p<0.0001)个百分点。通过 2008 年至 2018 年,URBMI 和 NRCMS 的门诊就诊和住院治疗差距缩小,到 2018 年差距较小。NRCMS 和 UEBMI 之间放弃住院治疗的比率比从 2008 年的 0.9(p>0.1)下降到 2018 年的 0.8(p<0.0001)。URBMI 和 NRCMS 中的贫困人群的门诊和住院利用率增长较快,放弃住院治疗的比例较低。然而,在 UEBMI、URBMI 和 NRCMS 中,贫困人群住院的可能性总是低于富裕人群。

结论

URBMI 和 NRCMS 的医疗利用率显著增加,尤其是最贫困人群,同时医疗保险之间以及 URBMI 和 NRCMS 内部的医疗利用率不平等和收入基础上的医疗利用率不平等也有所改善。然而,贫困人群总是更有可能放弃医生建议的住院治疗。我们建议进一步关注贫困人群的上述入院护理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6665/8876177/c0dff9c3431b/12939_2022_1633_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6665/8876177/95923fd5db04/12939_2022_1633_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6665/8876177/5b660b1a9e92/12939_2022_1633_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6665/8876177/c0dff9c3431b/12939_2022_1633_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6665/8876177/95923fd5db04/12939_2022_1633_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6665/8876177/5b660b1a9e92/12939_2022_1633_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6665/8876177/c0dff9c3431b/12939_2022_1633_Fig3_HTML.jpg

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