Algorithm to detect pediatric provider attention to high BMI and associated medical risk. (16th November 2018)

• Record Type: Journal Article
• Authors: Turer, Christy B; Skinner, Celette S; Barlow, Sarah E
• Is Part Of: Journal of the American Medical Informatics Association. Volume 26:Number 1(2019)
• Page Start: 55
• Page End: 60
• Publication Date: 2018-11-16
• Subjects: body mass index -- electronic health record -- validation; Medical informatics -- Periodicals; Information Services -- Periodicals; Medical Informatics -- Periodicals; Médecine -- Informatique -- Périodiques; Informatica; Geneeskunde; Informatique médicale; Computer network resources; Electronic journals; 610.285
• DOI: 10.1093/jamia/ocy126
• Languages: English
• ISSNs: 1067-5027

Abstract

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.