Poster 362: Identifying Racial Disparity in Utilization and Outcomes of Hip Arthroscopy using Machine Learning

Objectives: Background: Arthroscopic diagnosis and treatment of femoroacetabular pathology has been increasingly used in the past thirty years with interventions resulting in improved hip function and ultimate delay of hip arthroplasty in a minimally invasive manner. Unfortunately, previous investig...

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Veröffentlicht in:Orthopaedic journal of sports medicine 2023-07, Vol.11 (7_suppl3)
Hauptverfasser: Lu, Yining, Marigi, Erick, Alder, Kareme, Mickley, John, Camp, Christopher, Levy, Bruce, Krych, Aaron, Okoroha, Kelechi
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Sprache:eng
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Zusammenfassung:Objectives: Background: Arthroscopic diagnosis and treatment of femoroacetabular pathology has been increasingly used in the past thirty years with interventions resulting in improved hip function and ultimate delay of hip arthroplasty in a minimally invasive manner. Unfortunately, previous investigations have observed decreased rates of access, utilization of, and outcomes following orthopedic interventions such as hip arthroplasty in underrepresented patients. The purpose of this study is to examine racial differences in procedural rates, outcomes, and complications in patients undergoing hip arthroscopy. Methods: The State Ambulatory Surgery and Services Database (SASD) and State Emergency Department Database (SEDD) of New York were queried for patients undergoing hip arthroscopy from 2011 to 2017. The primary outcomes investigated were utilization over time, total charges billed per encounter, 90-day emergency department visits, and revision hip arthroscopy. Patients were stratified into White and non-White race, and intergroup differences were evaluated with descriptive statistics. Subgroup analysis was performed with linear mixed-effects models to identify significant interactions between race and individual variables that contributed to any differences in the outcomes of interest. Temporal trends in utilization of hip arthroscopy and concomitant procedures between the two groups were analyzed with Poisson regression modeling. Finally, targeted maximum likelihood estimation (TMLE) was performed to provide nonparametric estimates of the specific differences in the outcomes studied using machine learning ensembles while controlling for patient risk factors. Results: A total of 9,745 patients underwent hip arthroscopy during the study period, with 1,081 patients of non-White race (11.9%). Results of Poisson regression demonstrated an annual increase of 1.11 in the incidence rate of hip arthroscopy among White patients, compared to 1.03 for non-White patients (p
ISSN:2325-9671
2325-9671
DOI:10.1177/2325967123S00325