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

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.

Keywords: Attribution; Medicaid; health plans; readmission; sickle cell disease.