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Updated: Feb 2, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
Published on: December 15, 2023
Algorithm to detect pediatric provider attention to high BMI and associated medical risk
Christy B Turer1,2,3,4, Celette S Skinner3,4, Sarah E Barlow1,3
1Department of Pediatrics, University of Texas Southwestern Medical Center and Children's Health, Dallas, TX, USA.
Abstract:
We developed and validated an algorithm that uses combinations of extractable electronic-health-record (EHR) indicators (diagnosis codes, orders for laboratories, medications, and referrals) that denote widely-recommended clinician practice behaviors: attention to overweight/obesity/body mass index alone (BMI Alone), with attention to hypertension/other comorbidities (BMI/Medical Risk), or neither (No Attention). Data inputs used for each EHR indicator were refined through iterative chart review to identify and resolve modifiable coding errors. Validation was performed through manual review of randomly selected visit encounters (n = 308) coded by the refined algorithm. Of 104 encounters coded as No Attention, 89.4% lacked any evidence (specificity) of attention to BMI/Medical Risk. Corresponding evidence (sensitivity) of attention to BMI Alone was identified in 96.0% (of 101 encounters coded as BMI Alone) and BMI/Medical Risk in 96.1% (of 103 encounters coded as BMI/Medical Risk). Our EHR data algorithm can validly determine provider attention to BMI alone, with Medical Risk, or neither.
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