Abstract
IMPORTANCE: Government and commercial health insurers have recently enacted policies to discourage nonemergent emergency department (ED) visits by reducing or denying claims for such visits using retrospective claims algorithms. Low-income Black and Hispanic pediatric patients often experience worse access to primary care services necessary for preventing some ED visits, raising concerns about the uneven impact of these policies. OBJECTIVE: To estimate potential racial and ethnic disparities in outcomes of Medicaid policies for reducing ED professional reimbursement based on a retrospective diagnosis-based claims algorithm. DESIGN, SETTING, AND PARTICIPANTS: This simulation study used a retrospective cohort of pediatric ED visits (aged 0-18 years) for Medicaid-insured children and adolescents appearing in the Market Scan Medicaid database between January 1, 2016, and December 31, 2019. Visits missing date of birth, race and ethnicity, professional claims data, and Current Procedural Terminology codes of billing level of complexity were excluded, as were visits that result in admission. Data were analyzed from October 2021 to June 2022. MAIN OUTCOMES AND MEASURES: Proportion of ED visits algorithmically classified as nonemergent and simulated per-visit professional reimbursement after applying a current reimbursement reduction policy for potentially nonemergent ED visits. Rates were calculated overall and compared by race and ethnicity. RESULTS: The sample included 8 471 386 unique ED visits (43.0% by patients aged 4-12 years; 39.6% Black, 7.7% Hispanic, and 48.7% White), of which 47.7% were algorithmically identified as potentially nonemergent and subject to reimbursement reduction, resulting in a 37% reduction in ED professional reimbursement across the study cohort. More visits by Black (50.3%) and Hispanic (49.0%) children were algorithmically identified as nonemergent when compared with visits by White children (45.3%; P < .001). Modeling the impact of the reimbursement reductions across the cohort resulted in expected per-visit reimbursement that was 6% lower for visits by Black children and 3% lower for visits by Hispanic children relative to visits by White children. CONCLUSIONS AND RELEVANCE: In this simulation study of over 8 million unique ED visits, algorithmic approaches for classifying pediatric ED visits that used diagnosis codes identified proportionately more visits by Black and Hispanic children as nonemergent. Insurers applying financial adjustments based on these algorithmic outputs risk creating uneven reimbursement policies across racial and ethnic groups.