{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T10:33:57Z","timestamp":1772447637579,"version":"3.50.1"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Objective To develop an efficient surveillance approach for childhood diabetes by type across 2 large US health care systems, using phenotyping algorithms derived from electronic health record (EHR) data.<\/jats:p>\n               <jats:p>Materials and Methods Presumptive diabetes cases &amp;lt;20 years of age from 2 large independent health care systems were identified as those having \u22651 of the 5 indicators in the past 3.5 years, including elevated HbA1c, elevated blood glucose, diabetes-related billing codes, patient problem list, and outpatient anti-diabetic medications. EHRs of all the presumptive cases were manually reviewed, and true diabetes status and diabetes type were determined. Algorithms for identifying diabetes cases overall and classifying diabetes type were either prespecified or derived from classification and regression tree analysis. Surveillance approach was developed based on the best algorithms identified.<\/jats:p>\n               <jats:p>Results We developed a stepwise surveillance approach using billing code\u2013based prespecified algorithms and targeted manual EHR review, which efficiently and accurately ascertained and classified diabetes cases by type, in both health care systems. The sensitivity and positive predictive values in both systems were approximately \u226590% for ascertaining diabetes cases overall and classifying cases with type 1 or type 2 diabetes. About 80% of the cases with \u201cother\u201d type were also correctly classified. This stepwise surveillance approach resulted in a &amp;gt;70% reduction in the number of cases requiring manual validation compared to traditional surveillance methods.<\/jats:p>\n               <jats:p>Conclusion EHR data may be used to establish an efficient approach for large-scale surveillance for childhood diabetes by type, although some manual effort is still needed.<\/jats:p>","DOI":"10.1093\/jamia\/ocv207","type":"journal-article","created":{"date-parts":[[2016,4,24]],"date-time":"2016-04-24T00:18:19Z","timestamp":1461457099000},"page":"1060-1067","source":"Crossref","is-referenced-by-count":31,"title":["An efficient approach for surveillance of childhood diabetes by type derived from electronic health record data: the SEARCH for Diabetes in Youth Study"],"prefix":"10.1093","volume":"23","author":[{"given":"Victor W","family":"Zhong","sequence":"first","affiliation":[{"name":"Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jihad S","family":"Obeid","sequence":"additional","affiliation":[{"name":"Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jean B","family":"Craig","sequence":"additional","affiliation":[{"name":"Biomedical Informatics Center, Medical University of South Carolina, Charleston, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emily R","family":"Pfaff","sequence":"additional","affiliation":[{"name":"North Carolina TraCS Institute, University of North Carolina, Chapel Hill, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joan","family":"Thomas","sequence":"additional","affiliation":[{"name":"Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lindsay M","family":"Jaacks","sequence":"additional","affiliation":[{"name":"Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel P","family":"Beavers","sequence":"additional","affiliation":[{"name":"Department of Biostatistical Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Timothy S","family":"Carey","sequence":"additional","affiliation":[{"name":"Cecil G. Sheps Center for Health Services Research, University of North Carolina, Chapel Hill, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jean M","family":"Lawrence","sequence":"additional","affiliation":[{"name":"Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dana","family":"Dabelea","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Colorado School of Public Health, University of Colorado, Aurora, CO, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard F","family":"Hamman","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Colorado School of Public Health, University of Colorado, Aurora, CO, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deborah A","family":"Bowlby","sequence":"additional","affiliation":[{"name":"Division of Pediatric Endocrinology, Medical University of South Carolina, Charleston, SC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Catherine","family":"Pihoker","sequence":"additional","affiliation":[{"name":"Department of Washington, University of Washington, Seattle, WA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sharon H","family":"Saydah","sequence":"additional","affiliation":[{"name":"Centers for Disease Control and Prevention, Division of Diabetes Translation, Atlanta, GA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elizabeth J","family":"Mayer-Davis","sequence":"additional","affiliation":[{"name":"Department of Nutrition, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA"},{"name":"Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2016,4,23]]},"reference":[{"key":"2020110612365103200_ocv207-B1","doi-asserted-by":"crossref","first-page":"1778","DOI":"10.1001\/jama.2014.3201","article-title":"Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009","volume":"311","author":"Dabelea","year":"2014","journal-title":"JAMA."},{"key":"2020110612365103200_ocv207-B2","doi-asserted-by":"crossref","first-page":"1597","DOI":"10.2337\/dc12-0767","article-title":"Increasing incidence of type 1 diabetes in youth: twenty years of the Philadelphia Pediatric Diabetes Registry","volume":"36","author":"Lipman","year":"2013","journal-title":"Diabetes Care."},{"key":"2020110612365103200_ocv207-B3","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1515\/JPEM.2007.20.10.1093","article-title":"Incidence of childhood type I and non-type 1 diabetes mellitus in a diverse population: the Chicago Childhood Diabetes Registry, 1994 to 2003","volume":"20","author":"Smith","year":"2007","journal-title":"J Pediatr Endocrinol Metab."},{"key":"2020110612365103200_ocv207-B4","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1542\/peds.114.1.259","article-title":"An update on type 2 diabetes in youth from the National Diabetes Education Program","volume":"114","author":"Bobo","year":"2004","journal-title":"Pediatrics."},{"key":"2020110612365103200_ocv207-B5","doi-asserted-by":"crossref","first-page":"2716","DOI":"10.1001\/jama.297.24.2716","article-title":"Incidence of diabetes in youth in the United States","volume":"297","author":"Writing Group for the SEARCH for Diabetes in Youth Study Group","year":"2007","journal-title":"JAMA."},{"key":"2020110612365103200_ocv207-B6","doi-asserted-by":"crossref","first-page":"3938","DOI":"10.2337\/db13-1891","article-title":"Trends in incidence of type 1 diabetes among non-Hispanic white youth in the U.S., 2002-2009","volume":"63","author":"Lawrence","year":"2014","journal-title":"Diabetes."},{"key":"2020110612365103200_ocv207-B7","first-page":"A412","article-title":"Factors influencing time to case ascertainment in youth with type 1 and type 2 diabetes in the SEARCH for Diabetes in Youth Study [Abstract]","volume":"62","author":"Crume","year":"2013","journal-title":"Diabetes."},{"key":"2020110612365103200_ocv207-B8","doi-asserted-by":"crossref","first-page":"1478","DOI":"10.1377\/hlthaff.2013.0308","article-title":"Adoption of electronic health records grows rapidly, but fewer than half of US hospitals had at least a basic system in 2012","volume":"32","author":"DesRoches","year":"2013","journal-title":"Health.Aff. 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