{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T14:46:35Z","timestamp":1792161995343,"version":"4.4.0"},"reference-count":10,"publisher":"American Diabetes Association","issue":"5","license":[{"start":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T00:00:00Z","timestamp":1788998400000},"content-version":"vor","delay-in-days":9,"URL":"https:\/\/www.diabetesjournals.org\/journals\/pages\/license"}],"funder":[{"DOI":"10.13039\/100000062","name":"National Institute of Diabetes and Digestive and Kidney Diseases","doi-asserted-by":"publisher","award":["R01DK139116"],"award-info":[{"award-number":["R01DK139116"]}],"id":[{"id":"10.13039\/100000062","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":["R01HL177516"],"award-info":[{"award-number":["R01HL177516"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["diabetesjournals.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,9,1]]},"abstract":"<jats:sec>\n                    <jats:title>OBJECTIVE<\/jats:title>\n                    <jats:p>Accurate classification of diabetes type in early-onset populations is essential for epidemiologic and health services research but remains challenging when using electronic health record (EHR) data alone. Our objective was to develop and validate a diabetes typing algorithm distinguishing type 1 from type 2 diabetes in adolescents and young adults (AYAs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESEARCH DESIGN AND METHODS<\/jats:title>\n                    <jats:p>We developed and validated an EHR-based algorithm to identify and classify diabetes type among individuals aged 10\u201330 years enrolled in the Kaiser Permanente Northern California network (2007\u20132024). Identification of AYAs with diabetes incorporated diagnosis codes, laboratory results, and medications. Diabetes type was classified using a hierarchical algorithm that leveraged pancreatic autoantibody results and longitudinal diagnostic patterns. Algorithm performance was assessed via blinded medical record review in a random subset of 100 AYAs with diabetes, representing 0.14% of the 71,385 AYAs with algorithm-identified diabetes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Among 71,385 AYAs with diabetes, the disease was classified as type 1 diabetes in 16.6%, as type 2 diabetes in 75.2%, as other diabetes in 3.0%, and as indeterminate in 5.2%. When validated against blinded medical record review in a subset of patients, sensitivity and specificity were 100% and 98%, respectively, for type 1 diabetes and 98% and 95%, respectively, for type 2 diabetes. Inclusion of pancreatic autoantibody data prevented potential misclassification of type 1 diabetes in 609 patients, representing \u223c6% of those with algorithm-classified type 1 diabetes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS<\/jats:title>\n                    <jats:p>This validated diabetes typing algorithm supports scalable early-onset diabetes research using EHR data.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2337\/doc26-0088","type":"journal-article","created":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T13:31:31Z","timestamp":1789047091000},"page":"947-952","update-policy":"https:\/\/doi.org\/10.2337\/ada-journal-policies","source":"Crossref","is-referenced-by-count":0,"title":["Development and Validation of a Novel Algorithm for Classifying Diabetes Type in Adolescents and Young Adults Using Electronic Health Record Data"],"prefix":"10.2337","volume":"1","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8049-6370","authenticated-orcid":false,"given":"Shylaja","family":"Srinivasan","sequence":"first","affiliation":[{"name":"Division of Pediatric Endocrinology, Department of Pediatrics, University of California, San Francisco 1 , San Francisco, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew J.","family":"Karter","sequence":"additional","affiliation":[{"name":"Division of Research, Kaiser Permanente Northern California 2 , Pleasanton, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julia","family":"Acker","sequence":"additional","affiliation":[{"name":"School of Public Health, University of California 3 , Berkeley, Berkeley, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saher","family":"Daredia","sequence":"additional","affiliation":[{"name":"School of Public Health, University of California 3 , Berkeley, Berkeley, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cindy J.","family":"Huang","sequence":"additional","affiliation":[{"name":"Division of Research, Kaiser Permanente Northern California 2 , Pleasanton, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julianna","family":"Deardorff","sequence":"additional","affiliation":[{"name":"School of Public Health, University of California 3 , Berkeley, Berkeley, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer Y.","family":"Liu","sequence":"additional","affiliation":[{"name":"Division of Research, Kaiser Permanente Northern California 2 , Pleasanton, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siyan","family":"Chen","sequence":"additional","affiliation":[{"name":"Division of Research, Kaiser Permanente Southern California 4 , Pasadena, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sonya","family":"Negriff","sequence":"additional","affiliation":[{"name":"Division of Research, Kaiser Permanente Southern California 4 , Pasadena, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8903-1457","authenticated-orcid":false,"given":"Alka M.","family":"Kanaya","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine, Department of Medicine, University of California 5 , San Francisco, San Francisco, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ai","family":"Kubo","sequence":"additional","affiliation":[{"name":"Division of Research, Kaiser Permanente Northern California 2 , Pleasanton, CA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1167","published-online":{"date-parts":[[2026,9,10]]},"reference":[{"key":"2026101610024624100_B1","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1001\/jama.2021.11165","article-title":"Trends in prevalence of type 1 and type 2 diabetes in children and adolescents in the US, 2001-2017","volume":"326","author":"Lawrence","year":"2021","journal-title":"JAMA"},{"key":"2026101610024624100_B2","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/S2213-8587(23)00025-6","article-title":"Trends in incidence of youth-onset type 1 and type 2 diabetes in the USA, 2002-18: results from the population-based SEARCH for Diabetes in Youth study","volume":"11","author":"Wagenknecht","year":"2023","journal-title":"Lancet Diabetes Endocrinol"},{"key":"2026101610024624100_B3","doi-asserted-by":"crossref","first-page":"2313","DOI":"10.1016\/S0140-6736(25)00830-X","article-title":"Early-onset type 2 diabetes: the next major diabetes transition","volume":"405","author":"Luk","year":"2025","journal-title":"Lancet"},{"key":"2026101610024624100_B4","author":"Noiman","year":"2026"},{"key":"2026101610024624100_B5","author":"Fryar","year":"2026"},{"key":"2026101610024624100_B6","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1002\/pds.4377","article-title":"Validation of an algorithm for identifying type 1 diabetes in adults based on electronic health record data","volume":"27","author":"Schroeder","year":"2018","journal-title":"Pharmacoepidemiol Drug Saf"},{"key":"2026101610024624100_B7","doi-asserted-by":"crossref","first-page":"914","DOI":"10.2337\/dc12-0964","article-title":"Automated detection and classification of type 1 versus type 2 diabetes using electronic health record data","volume":"36","author":"Klompas","year":"2013","journal-title":"Diabetes 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(DISTANCE)","volume":"36","author":"Karter","year":"2013","journal-title":"Diabetes Care"}],"container-title":["Diabetes Obesity and CardioMetabolic CARE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/diabetesjournals.org\/docm-care\/article-pdf\/1\/5\/947\/893956\/docm260088.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/diabetesjournals.org\/docm-care\/article-pdf\/1\/5\/947\/893956\/docm260088.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T14:02:55Z","timestamp":1792159375000},"score":1,"resource":{"primary":{"URL":"https:\/\/diabetesjournals.org\/docm-care\/article\/1\/5\/947\/172464\/Development-and-Validation-of-a-Novel-Algorithm"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,1]]},"references-count":10,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2026,9,10]]},"published-print":{"date-parts":[[2026,9,1]]}},"URL":"https:\/\/doi.org\/10.2337\/doc26-0088","relation":{},"ISSN":["3067-3518","3067-3534"],"issn-type":[{"value":"3067-3518","type":"print"},{"value":"3067-3534","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,1]]}}}