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Electronic phenotypes to distinguish clinician attention to high body mass index, hypertension, lipid disorders, fatty liver and diabetes in pediatric primary care: Diagnostic accuracy of electronic phenotypes compared to masked comprehensive chart review.

Publication ,  Journal Article
Turer, CB; Park, JJ; Gupta, OT; Ramirez, C; Basit, MA; Heitjan, DF; Barlow, SE
Published in: Pediatr Obes
October 2023

BACKGROUND/OBJECTIVES: Electronic phenotyping is a method of using electronic-health-record (EHR) data to automate identifying a patient/population with a characteristic of interest. This study determines validity of using EHR data of children with overweight/obesity to electronically phenotype evidence of clinician 'attention' to high body mass index (BMI) and each of four distinct comorbidities. METHODS: We built five electronic phenotypes classifying 2-18-year-old children with overweight/obesity (n = 17,397) by electronic/health-record evidence of distinct attention to high body mass index, hypertension, lipid disorders, fatty liver, and prediabetes/diabetes. We reviewed, selected and cross-checked random charts to define items clinicians select in EHRs to build problem lists, and to order medications, laboratory tests and referrals to electronically classify attention to overweight/obesity and each comorbidity. Operating characteristics of each clinician-attention phenotype were determined by comparing comprehensive chart review by reviewers masked to electronic classification who adjudicated evidence of clinician attention to high BMI and each comorbidity. RESULTS: In a random sample of 817 visit-records reviewed/coded, specificity of each electronic phenotype is 99%-100% (with PPVs ranging from 96.8% for prediabetes/diabetes to 100% for dyslipidemia and hypertension). Sensitivities of the attention classifications range from 69% for hypertension (NPV, 98.9%) to 84.7% for high-BMI attention (NPV, 92.3%). CONCLUSIONS: Electronic phenotypes for clinician attention to overweight/obesity and distinct comorbidities are highly specific, with moderate (BMI) to modest (each comorbidity) sensitivity. The high specificity supports using phenotypes to identify children with prior high-BMI/comorbidity attention.

Duke Scholars

Published In

Pediatr Obes

DOI

EISSN

2047-6310

Publication Date

October 2023

Volume

18

Issue

10

Start / End Page

e13066

Location

England

Related Subject Headings

  • Primary Health Care
  • Prediabetic State
  • Phenotype
  • Overweight
  • Obesity
  • Lipids
  • Hypertension
  • Humans
  • Fatty Liver
  • Electronic Health Records
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Turer, C. B., Park, J. J., Gupta, O. T., Ramirez, C., Basit, M. A., Heitjan, D. F., & Barlow, S. E. (2023). Electronic phenotypes to distinguish clinician attention to high body mass index, hypertension, lipid disorders, fatty liver and diabetes in pediatric primary care: Diagnostic accuracy of electronic phenotypes compared to masked comprehensive chart review. Pediatr Obes, 18(10), e13066. https://doi.org/10.1111/ijpo.13066
Turer, Christy B., Jenny J. Park, Olga T. Gupta, Charina Ramirez, Mujeeb A. Basit, Daniel F. Heitjan, and Sarah E. Barlow. “Electronic phenotypes to distinguish clinician attention to high body mass index, hypertension, lipid disorders, fatty liver and diabetes in pediatric primary care: Diagnostic accuracy of electronic phenotypes compared to masked comprehensive chart review.Pediatr Obes 18, no. 10 (October 2023): e13066. https://doi.org/10.1111/ijpo.13066.
Journal cover image

Published In

Pediatr Obes

DOI

EISSN

2047-6310

Publication Date

October 2023

Volume

18

Issue

10

Start / End Page

e13066

Location

England

Related Subject Headings

  • Primary Health Care
  • Prediabetic State
  • Phenotype
  • Overweight
  • Obesity
  • Lipids
  • Hypertension
  • Humans
  • Fatty Liver
  • Electronic Health Records