aceReal-World Identification of Obesity: Development and Internal Validation of a Machine Learning Algorithm
To develop and internally validate machine learning (ML) models to retrospectively identify people with obesity (PwO) (body mass index [BMI] ≥ 30 kg/m2) using administrative claims and electronic health record (EHR) data. This study used US commercial and Medicare Advantage claims and EHR data from the Healthcare Integrated Research Database (HIRD) enriched with clinical, laboratory and social drivers of health data from the American Community Survey and Food Access Research Atlas between 1 January 2022 and 30 S…
A machine learning model identified people with obesity in claims and health record data more accurately (F1 0.797) than relying on BMI diagnosis codes alone (F1 0.716).
Evidence
- Peer-reviewedDiabetes, Obesity and Metabolism2026-10-25
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Truvace Impact Record TRV-2026-2273, v1: “Real-World Identification of Obesity: Development and Internal Validation of a Machine Learning Algorithm.” Truvace, 2026-10-26. /record/TRV-2026-2273 (accessed at citation time). sha256 713f3e47ac1db7f2…
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