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考虑在医疗保健系统各层级汇总数据以衡量绩效时的注意事项。

Considerations When Aggregating Data to Measure Performance Across Levels of the Health Care System.

机构信息

Department of Pediatrics, Susan B Meister Child Health Evaluation and Research (CHEAR) Center, University of Michigan (SL Reeves, KJ Dombkowski, and B Madden), Ann Arbor, Mich; Department of Epidemiology, University of Michigan (SL Reeves), Ann Arbor, Mich.

Department of Pediatrics, Susan B Meister Child Health Evaluation and Research (CHEAR) Center, University of Michigan (SL Reeves, KJ Dombkowski, and B Madden), Ann Arbor, Mich.

出版信息

Acad Pediatr. 2022 Apr;22(3S):S119-S124. doi: 10.1016/j.acap.2021.11.013.

Abstract

BACKGROUND

Measuring quality at varying levels of the health care system requires attribution, a process of determining the patients and services for which each level is responsible. However, it is important to ensure that attribution approaches are equitable; otherwise, individuals may be assigned differentially based upon social determinants of health.

METHODS

First, we used Medicaid claims (2010-2018) from Michigan to assess the proportion of children with sickle cell anemia who had less than 12 months enrollment within a single Medicaid health plan and could therefore not be attributed to a specific health plan. Second, we used the Medicaid Analytic eXtract data (2008-2009) from 26 states to simulate adapting the 30-Day Pediatric All-Condition Readmission measure to the Accountable Care Organization (ACO) level and examined the proportion of readmissions that could not be attributed.

RESULTS

For the sickle cell measure, an average of 300 children with sickle cell anemia were enrolled in Michigan Medicaid each year. The proportion of children that could not be attributed to a Medicaid health plan ranged from 12.2% to 89.0% across years. For the readmissions measure, of the 1,051,365 index admissions, 22% were excluded in the ACO-level analysis because of being unable to attribute the patient to a health plan for the 30 days post discharge.

CONCLUSIONS

When applying attribution models, it is essential to consider the potential to induce health disparities. Differential attribution may have unintentional consequences that deepen health disparities, particularly when considering incentive programs for health plans to improve the quality of care.

摘要

背景

在医疗保健系统的不同层面衡量质量需要归因,即确定每个层面负责的患者和服务的过程。然而,确保归因方法公平是很重要的;否则,个体可能会因健康的社会决定因素而受到不同的分配。

方法

首先,我们使用密歇根州的医疗补助(Medicaid)索赔数据(2010-2018 年)来评估患有镰状细胞贫血的儿童中,有多少人在单一医疗补助健康计划中的参保时间少于 12 个月,因此无法归属于特定的健康计划。其次,我们使用来自 26 个州的 Medicaid Analytic eXtract 数据(2008-2009 年)模拟将 30 天儿科全病种再入院措施适应于责任医疗组织(Accountable Care Organization,ACO)层面,并检查了无法归因的再入院比例。

结果

对于镰状细胞贫血的衡量标准,密歇根州的医疗补助计划每年平均有 300 名镰状细胞贫血患儿参保。无法归属于医疗补助计划的儿童比例在各年份间从 12.2%到 89.0%不等。对于再入院的衡量标准,在 1051365 次入院中,22%的病例在 ACO 层面的分析中被排除在外,因为在出院后 30 天内无法将患者归属于健康计划。

结论

在应用归因模型时,必须考虑到可能引发健康差异的问题。差异化归因可能会产生意想不到的后果,加深健康差异,尤其是在考虑激励医疗计划改善医疗质量的计划时。

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