{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T12:34:09Z","timestamp":1753878849694,"version":"3.41.2"},"reference-count":31,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2023,7,17]],"date-time":"2023-07-17T00:00:00Z","timestamp":1689552000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000050","name":"National Heart, Lung, and Blood Institute","doi-asserted-by":"publisher","award":["K23HL118152","R03HL144811"],"award-info":[{"award-number":["K23HL118152","R03HL144811"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000062","name":"National Institute of Diabetes and Digestive and Kidney Diseases","doi-asserted-by":"publisher","award":["R21DK114764"],"award-info":[{"award-number":["R21DK114764"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pediatric Obesity"],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:title>Summary<\/jats:title><jats:sec><jats:title>Background\/Objectives<\/jats:title><jats:p>Electronic phenotyping is a method of using electronic\u2010health\u2010record (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 \u2018attention\u2019 to high body mass index (BMI) and each of four distinct comorbidities.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We built five electronic phenotypes classifying 2\u201018\u2010year\u2010old children with overweight\/obesity (n = 17,397) by electronic\/health\u2010record evidence of distinct attention to high body mass index, hypertension, lipid disorders, fatty liver, and prediabetes\/diabetes. We reviewed, selected and cross\u2010checked 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\u2010attention 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In a random sample of 817 visit\u2010records reviewed\/coded, specificity of each electronic phenotype is 99%\u2013100% (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\u2010BMI attention (NPV, 92.3%).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>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\u2010BMI\/comorbidity attention.<\/jats:p><\/jats:sec>","DOI":"10.1111\/ijpo.13066","type":"journal-article","created":{"date-parts":[[2023,7,17]],"date-time":"2023-07-17T09:44:51Z","timestamp":1689587091000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["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"],"prefix":"10.1111","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6333-5535","authenticated-orcid":false,"given":"Christy B.","family":"Turer","sequence":"first","affiliation":[{"name":"Department of Pediatrics University of Texas Southwestern (UTSW)  Dallas Texas USA"},{"name":"Department of Medicine University of Texas Southwestern (UTSW)  Dallas Texas USA"},{"name":"Department of Population &amp; Data Sciences University of Texas Southwestern (UTSW)  Dallas Texas USA"},{"name":"Children's Health System of Dallas  Dallas Texas USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jenny J.","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Medicine University of Texas Southwestern (UTSW)  Dallas Texas USA"},{"name":"Department of Population &amp; Data Sciences University of Texas Southwestern (UTSW)  Dallas Texas USA"},{"name":"Department of Statistical Science Southern Methodist University (SMU)  Dallas Texas USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olga T.","family":"Gupta","sequence":"additional","affiliation":[{"name":"Department of Pediatrics University of Texas Southwestern (UTSW)  Dallas Texas USA"},{"name":"Department of Population &amp; Data Sciences University of Texas Southwestern (UTSW)  Dallas Texas USA"},{"name":"Children's Health System of Dallas  Dallas Texas USA"},{"name":"Department of Pediatrics Duke University  Durham North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Charina","family":"Ramirez","sequence":"additional","affiliation":[{"name":"Department of Pediatrics University of Texas Southwestern (UTSW)  Dallas Texas USA"},{"name":"Children's Health System of Dallas  Dallas Texas USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mujeeb A.","family":"Basit","sequence":"additional","affiliation":[{"name":"Department of Medicine University of Texas Southwestern (UTSW)  Dallas Texas USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel F.","family":"Heitjan","sequence":"additional","affiliation":[{"name":"Department of Population &amp; Data Sciences University of Texas Southwestern (UTSW)  Dallas Texas USA"},{"name":"Department of Statistical Science Southern Methodist University (SMU)  Dallas Texas USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1672-2126","authenticated-orcid":false,"given":"Sarah E.","family":"Barlow","sequence":"additional","affiliation":[{"name":"Department of Pediatrics University of Texas Southwestern (UTSW)  Dallas Texas USA"},{"name":"Department of Population &amp; Data Sciences University of Texas Southwestern (UTSW)  Dallas Texas USA"},{"name":"Children's Health System of Dallas  Dallas Texas 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