We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Racial and Ethnic Differences in Insurer Classification of Nonemergent Pediatric Emergency Department Visits.
- Authors
Pomerantz, Alexander; De Souza, Heidi G.; Hall, Matthew; Neuman, Mark I.; Goyal, Monika K.; Samuels-Kalow, Margaret E.; Aronson, Paul L.; Alpern, Elizabeth R.; Simon, Harold K.; Hoffmann, Jennifer A.; Wells, Jordee M.; Shanahan, Kristen H.; Gutman, Colleen K.; Peltz, Alon
- Abstract
Key Points: Question: Do insurance policies that retrospectively reduce payments for nonemergent pediatric emergency department (ED) visits by using claims algorithms introduce potential racial and ethnic differences in reimbursement? Findings: This cohort study of MarketScan Medicaid data included 8 471 386 ED visits and simulated the potential impact of 1 state Medicaid policy. Visits to the ED by Black (50%) and Hispanic (49%) children had a higher likelihood of being algorithmically identified as nonemergent and subject to professional reimbursement reductions compared with visits by White children (45%). Meaning: This study found that bias contained in the output of claims algorithms that retrospectively identify nonemergent pediatric ED visits may introduce inequity in health care financing. This cohort study simulates the outcomes of an algorithm identifying nonemergent emergency department (ED) visits to model racial and ethnic differences in classification of visits by pediatric patients. 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.
- Subjects
INSURANCE companies; HEALTH policy; HOSPITAL emergency services; HEALTH services accessibility; RACE; PEDIATRICS; RETROSPECTIVE studies; HEALTH insurance reimbursement; DESCRIPTIVE statistics; MEDICAL appointments; MEDICAID; HEALTH equity; DATA analysis software; ALGORITHMS
- Publication
JAMA Network Open, 2023, Vol 6, Issue 5, pe2311752
- ISSN
2574-3805
- Publication type
Article
- DOI
10.1001/jamanetworkopen.2023.11752