Evidence map›Paper›PMID 39732164›Full record

ArticleAcademic pediatrics2025

Accuracy of Electronic Health Record Phenotypes to Detect Recognition of Hypertension in Pediatric Primary Care.

James T Nugent, Victoria Cueto, Christina Tong, Mona Sharifi

Abstract read
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Article in Academic pediatrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

James T NugentDepartment of Pediatrics (JT Nugent, V Cueto, and M Sharifi), Yale School of Medicine, New Haven, Conn. Electronic address: james.nugent@yale.edu.
Victoria CuetoDepartment of Pediatrics (JT Nugent, V Cueto, and M Sharifi), Yale School of Medicine, New Haven, Conn.
Christina TongDepartment of Social and Behavioral Sciences (C Tong), Yale School of Public Health, New Haven, Conn.
Mona SharifiDepartment of Pediatrics (JT Nugent, V Cueto, and M Sharifi), Yale School of Medicine, New Haven, Conn; Department of Biostatistics (M Sharifi), Yale School of Public Health, New Haven, Conn.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

objectiveTo evaluate the accuracy of extractable electronic health record (EHR) data to define clinician recognition of hypertension in pediatric primary care.

methodsWe used EHR data to perform a cross-sectional study of children aged 3 to 18 years at well-visits in Connecticut from 2018 to 2023 (n = 50,290) that had either 1) incident hypertension (hypertensive blood pressure [BP] at the well-visit and ≥2 prior hypertensive BPs without prior diagnosis of hypertension) or 2) isolated hypertensive BP at the well-visit without necessarily having prior hypertensive BPs. We tested the accuracy of EHR phenotypes to detect recognition of incident hypertension or hypertensive BP using structured elements, including diagnosis codes, problem list entries, number of BP measurements, orders, and follow-up information. The primary outcome of hypertension recognition was determined by chart review.

resultsAmong 239 children with incident hypertension and a random sample of 220 children with hypertensive BP, 13% in each sample had clinician recognition of hypertension and hypertensive BP, respectively. An algorithm using International Classification of Diseases, Tenth Revision (ICD-10) encounter diagnosis code, ICD-10 problem list, or multiple BPs during the visit had the highest area under the curve (AUC) for attention to incident hypertension (AUC, 0.84; sensitivity, 71.9%; specificity, 95.7%). Adding follow-up BP information to this algorithm had the highest AUC for attention to hypertensive BP (AUC, 0.85; sensitivity, 75.9%; specificity, 93.2%). For patients with hypertension recognition by chart review, ∼20% had only free text documentation of hypertension without any structured elements.

conclusionsEHR phenotypes for hypertension recognition have high specificity and moderate sensitivity and may be used in clinician decision support to improve guideline-recommended care.

Indexed as

Electronic Health RecordsHypertensionPrimary Health CareAdolescentAlgorithmsChildChild, PreschoolConnecticutCross-Sectional StudiesFemaleHumansMalePediatricsPhenotypeSensitivity and Specificityblood pressurecomputable phenotypeelectronic health recordhypertension

Identifiers

PMID39732164
PMCPMC11893226

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