The cream-skimming behaviors of tertiary hospitals under medical alliances: evidence from China.

IF 4.1 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Zixuan Peng, Xu Chen, Peter C Coyte
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引用次数: 0

Abstract

Background: While previous studies have delved into the formation and development of medical alliances in China, there has been limited focus on investigating inequity in the referral rates and the quality of care received provided to patients with experience of referral and those without under the introduction of medical alliances. This study explored: (1) inequity in the odds of being referred to healthcare institutions within medical alliances; and (2) inequity in the quality of care received between the referred and non-referred patients.

Methods: This study employed a dataset comprising 440,950 individuals who had at least one outpatient visit at healthcare facilities in Hangzhou city, Zhejiang province, China from January 1, 2020 to September 24, 2021. Quality of outpatient care was measured by the odds of having seven-day all-cause follow-up encounters to any healthcare institution. Binary regression models combined with random effects were constructed to examine inequity in the referral rates and the quality of care received. A set of sensitivity analyses were conducted to check the robustness of study findings.

Results: This study has three key findings. First, outpatients' insurance status, rather than their specific diseases and health conditions, was identified the most significant determinant driving healthcare institutions' referral decisions. Compared with outpatients covered by public health insurance programs, those without such coverage were more likely to be referred by tertiary hospitals to primary care facilities (coefficient = 1.33; 95% CI: 0.56-2.11) while being less likely to be referred by primary care facilities to tertiary hospitals (coefficient = -2.00; 95% CI: -3.08 - -0.92). Second, the referred outpatients received poorer quality of care, as indicated by higher odds of having all-cause follow-up encounters within seven days at any healthcare institution, compared to those non-referred outpatients. Third, outpatients with chronic diseases and public health insurance coverage not only experienced higher referral rates but poorer quality of outpatient care after being referred from tertiary hospitals to primary care facilities, compared to their counterparts.

Conclusion: This study demonstrated that tertiary hospitals "siphoned-off" outpatients with public health insurance coverage from primary care facilities. Outpatients who were older, were male, with chronic diseases, and with public health insurance coverage were more likely to experience not only higher referral rates but poorer quality of outpatient care after being referred from tertiary hospitals to primary care facilities. Tailored policies are required to protect and compensate the most vulnerable population groups.

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医疗联盟下三级医院的撇脂行为:来自中国的证据。
背景:虽然以前的研究已经深入探讨了中国医疗联盟的形成和发展,但对于在引入医疗联盟的情况下,有转诊经验的患者和没有转诊经验的患者的转诊率和获得的护理质量的不公平调查的关注有限。本研究探讨:(1)医疗联盟内转诊到医疗机构的机率不平等;(2)转诊患者和非转诊患者接受的护理质量不平等。方法:本研究使用了一个包含440,950人的数据集,这些人在2020年1月1日至2021年9月24日期间在中国浙江省杭州市的医疗机构至少进行过一次门诊。门诊护理的质量是通过对任何医疗机构进行7天全因随访的几率来衡量的。二元回归模型结合随机效应,以检验在转诊率和护理质量的不公平。进行了一组敏感性分析以检查研究结果的稳健性。结果:本研究有三个主要发现。首先,门诊病人的保险状况,而不是他们的具体疾病和健康状况,被确定为驱动医疗机构转诊决策的最重要决定因素。与公共健康保险项目覆盖的门诊患者相比,没有公共健康保险项目覆盖的门诊患者更有可能由三级医院转到初级保健机构(系数= 1.33;95% CI: 0.56-2.11),而由初级保健机构转到三级医院的可能性较小(系数= -2.00;95% CI: -3.08 - -0.92)。第二,与未转诊的门诊患者相比,转诊的门诊患者接受的护理质量较差,这表明在任何医疗机构7天内进行全因随访的几率较高。第三,与同类患者相比,患有慢性病和公共健康保险的门诊患者从三级医院转到初级保健机构后,不仅转诊率更高,而且门诊服务质量更差。结论:本研究证明三级医院从基层医疗机构“吸走”了享有公共医疗保险的门诊病人。年龄较大、患有慢性病、有公共健康保险的男性门诊病人,从三级医院转到初级保健设施后,不仅转诊率更高,而且门诊护理质量更差。需要有针对性的政策来保护和补偿最脆弱的人口群体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.80
自引率
4.20%
发文量
162
审稿时长
28 weeks
期刊介绍: International Journal for Equity in Health is an Open Access, peer-reviewed, online journal presenting evidence relevant to the search for, and attainment of, equity in health across and within countries. International Journal for Equity in Health aims to improve the understanding of issues that influence the health of populations. This includes the discussion of political, policy-related, economic, social and health services-related influences, particularly with regard to systematic differences in distributions of one or more aspects of health in population groups defined demographically, geographically, or socially.
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