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Algorithm to detect pediatric provider attention to high BMI and associated medical risk.
Turer, Christy B; Skinner, Celette S; Barlow, Sarah E.
Afiliación
  • Turer CB; Department of Pediatrics, University of Texas Southwestern Medical Center and Children's Health, Dallas, TX, USA.
  • Skinner CS; Department of Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Barlow SE; Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
J Am Med Inform Assoc ; 26(1): 55-60, 2019 01 01.
Article en En | MEDLINE | ID: mdl-30445547
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Índice de Masa Corporal / Adhesión a Directriz / Registros Electrónicos de Salud / Obesidad Infantil Tipo de estudio: Diagnostic_studies / Etiology_studies / Guideline / Prognostic_studies / Risk_factors_studies Límite: Child / Humans Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Índice de Masa Corporal / Adhesión a Directriz / Registros Electrónicos de Salud / Obesidad Infantil Tipo de estudio: Diagnostic_studies / Etiology_studies / Guideline / Prognostic_studies / Risk_factors_studies Límite: Child / Humans Idioma: En Revista: J Am Med Inform Assoc Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos