Meyers Primary Care Institute, (a joint endeavor of the University of Massachusetts Medical School, Reliant Medical Group, and Fallon Health), Worcester, Massachusetts, USA.
Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
Health Serv Res. 2022 Jun;57(3):579-586. doi: 10.1111/1475-6773.13677. Epub 2021 Jun 1.
To describe the characteristics of high-frequency hospital users (four or more hospitalizations in a year) and the consequences of including or excluding their data from a readmission-based measure.
2015 and 2016 Massachusetts Medicaid data.
We compare demographics, morbidity burden, and social risk factors for high- and low-frequency hospital users, and membership in 17 accountable care organizations. We evaluate how excluding hospitalizations of high-frequency users from a 30-day readmission measure (with or without risk adjustment) changes its rate and variability and affects performance rankings of accountable care organizations. The outcome is readmission within 30 days; each live discharge from a hospital contributes one observation.
DATA COLLECTION/EXTRACTION METHODS: We studied 74 706 hospitalizations of 42 794 MassHealth members, 18-64 years old, managed-care-eligible, and ever hospitalized in 2016.
Among adult managed-care-eligible MassHealth members with at least one acute hospitalization, 8.7% were high-frequency hospital users; they contributed 30.2% of hospitalizations and 69.4% of readmissions. High-frequency users were more often male (77.1% vs. 50.0%; P < 0.001) and sicker (mean medical morbidity score was 3.3 vs. 1.9; P < 0.001) than others. They also had significant social risks: 33.1% with housing problems, 44.1% disabled, 83.2% with serious mental illness, and 77.1% with substance abuse disorder (vs. 22.0%, 27.3%, 60.2%, and 50.0%, respectively, for other hospital users [all P values <0.001]). Fully 50.7% of hospitalizations for high-frequency users led to 30-day readmissions (vs. 9.7%), contributing 72.0% of the variance in 30-day readmission, and substantially affecting judgments about the relative performance of accountable care organizations.
A small group of high-frequency hospital users have a disproportionate effect on 30-day readmission rates. This negatively affects some Medicaid ACOs, and more broadly is likely to adversely affect safety net hospitals. How these metrics are used should be reconsidered in this context.
描述高频住院患者（一年内住院 4 次或以上）的特征，以及将其数据纳入或排除在基于再入院的指标之外所产生的后果。
2015 年和 2016 年马萨诸塞州医疗补助数据。
我们比较了高频和低频住院患者的人口统计学特征、疾病负担和社会风险因素，以及 17 个问责制医疗组织的成员资格。我们评估了将高频住院患者的住院数据排除在 30 天再入院指标之外（是否进行风险调整）如何改变其比率和变异性，并影响问责制医疗组织的绩效排名。结果是 30 天内再入院；每位从医院出院的患者贡献一次观察。
资料收集/提取方法：我们研究了 74706 例马萨诸塞州医疗补助计划（MassHealth）42794 名符合管理式医疗资格、年龄在 18-64 岁之间、2016 年曾住院的患者的住院情况。
在至少有一次急性住院治疗的成年管理式医疗合格的 MassHealth 成员中，8.7%为高频住院患者；他们贡献了 30.2%的住院治疗和 69.4%的再入院。高频住院患者中男性（77.1%比 50.0%；P<0.001）和病情更严重（平均医疗发病率评分 3.3 比 1.9；P<0.001）的比例更高。他们还存在显著的社会风险：33.1%存在住房问题，44.1%残疾，83.2%患有严重精神疾病，77.1%患有药物滥用障碍（相比之下，其他住院患者的比例分别为 22.0%、27.3%、60.2%和 50.0%[所有 P 值均<0.001]）。高频住院患者中有 50.7%的住院治疗导致 30 天内再入院（9.7%），对 30 天内再入院率的变异性贡献了 72.0%，这对问责制医疗组织的相对绩效评估产生了实质性影响。
一小部分高频住院患者对 30 天再入院率有不成比例的影响。这对一些医疗补助 ACO 产生了负面影响，更广泛地说，可能对医疗保障网络医院产生不利影响。在这种情况下，应该重新考虑这些指标的使用方式。
