External Validation of an Electronic Phenotyping Algorithm Detecting Attention to High Body Mass Index in Pediatric Primary Care.

ABSTRACT:

Objectives

 The lack of feasible and meaningful measures of clinicians' behavior hinders efforts to assess and improve obesity management in pediatric primary care. In this study, we examined the external validity of a novel algorithm, previously validated in a single geographic region, using structured electronic health record (EHR) data to identify phenotypes of clinicians' attention to elevated body mass index (BMI) and weight-related comorbidities.

Methods

 We extracted structured EHR data for 300 randomly selected 6- to 12-year-old children with elevated BMI seen for well-child visits from June 2018 to May 2019 at pediatric primary care practices affiliated with Yale. Using diagnosis codes, laboratory orders, referrals, and medications adapted from the original algorith

SUBMITTER: Barron AG 

PROVIDER: S-EPMC11387092 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature