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

Abstract

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.

Keywords: body mass index; electronic health records; evidence-based medicine; phenotype; sensitivity and specificity.

FIGURE 1.. Flowchart of study cohort

Target population: 2–18-year-olds followed in primary care. The flowchart shows the target population, study cohort (n=17,397), and random sample used as the reference standard to examine the validity of electronic attention phenotypes (compared to masked comprehensive chart review) for ruling out prior distinct attention to high BMI, high blood pressure, prediabetes/diabetes, fatty liver, or dyslipidemia. ^aWe allowed the inclusion criterion “at least two visits with overweight or obesity” to use visits that would not be included as “high-BMI” visits in the study cohort, for example when a child had overweight/obesity but age at visit was less than two years old or 19 years or older. ^bExclusion criteria: Type 1 diabetes, cancer, major limb abnormality affecting measurements, pregnancy, chronic steroid use, foster care (intakes with 1–2 follow-up visits performed and unstable follow up), and major genetic/metabolic, congenital, or acquired diseases of the endocrine organs, heart, neurological system/brain, gastrointestinal system/liver, or the kidneys.