{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,28]],"date-time":"2026-05-28T14:10:48Z","timestamp":1779977448797,"version":"3.53.1"},"reference-count":19,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T00:00:00Z","timestamp":1775692800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T00:00:00Z","timestamp":1775692800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100009633","name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","doi-asserted-by":"publisher","award":["R01HD107083"],"award-info":[{"award-number":["R01HD107083"]}],"id":[{"id":"10.13039\/100009633","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","award":["UL1 TR002345"],"award-info":[{"award-number":["UL1 TR002345"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Paediatric Perinatal Epid"],"published-print":{"date-parts":[[2026,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Accurate algorithms are needed to support real\u2010world studies of medication safety in pregnancy. Kharbanda et\u00a0al. developed and validated algorithms for congenital malformations that incorporate death data and diagnosis codes from the ICD\u20109\u2010CM and ICD\u201010\u2010CM coding eras.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To modify an EHR\u2010based malformation algorithm for use with claims data and quantify the impact of missing death by calculating prevalence and sensitivity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using the MarketScan Commercial Database (2007\u20132022), we established a linked cohort of birthing parents and their liveborn infants, and a claims subcohort restricted to years with inpatient death information. We established a cohort of liveborn infants in Kaiser Permanente Washington (KPWA) integrated EHR\/claims data (2007\u20132022) that included comprehensive death information. We applied the validated algorithm to identify 22 malformations in MarketScan and 7 in KPWA (those with a prevalence \u2265\u200910 per 10,000 live births in MarketScan). In MarketScan, we calculated malformation prevalence with and without death information. We assessed the contribution of death on malformation identification by calculating sensitivity (with death as the gold standard).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among 2,203,328 infants in the MarketScan cohort, malformation prevalence was 201.3 per 10,000 live births. In the MarketScan subcohort (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20091,287,384), prevalence was 198.2 and 199.1 per 10,000 live births without and with death information, respectively. Among the most prevalent malformations, estimated sensitivity ranged from 95.8% for severe cardiac defects to 100.0% for intestinal atresia or stenosis, pyloric stenosis and limb deficiency (claims\/EHR cohort) and from 98.6% for severe cardiac defects to 100.0% for intestinal atresia or stenosis and pyloric stenosis (claims subcohort). Limitations include the use of an imperfect gold standard and a lack of chart review.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>We adapted a validated malformation algorithm for use with claims data. Omitting death information did not meaningfully impact sensitivity, suggesting this algorithm can be applied to data sources lacking death information.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/ppe.70146","type":"journal-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T11:09:38Z","timestamp":1775732978000},"page":"471-476","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Exploring the Impact of Missing Death Data on Identification of Congenital Malformations in Insurance Claims Data"],"prefix":"10.1111","volume":"40","author":[{"given":"Katelin B.","family":"Nickel","sequence":"first","affiliation":[{"name":"Department of Medicine, Division of Infectious Diseases Washington University School of Medicine  St. Louis Missouri USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sascha","family":"Dublin","sequence":"additional","affiliation":[{"name":"Kaiser Permanente Washington Health Research Institute  Seattle Washington, DC USA"},{"name":"Department of Epidemiology University of Washington  Seattle Washington, DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sharon","family":"Fuller","sequence":"additional","affiliation":[{"name":"Kaiser Permanente Washington Health Research Institute  Seattle Washington, DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7626-9992","authenticated-orcid":false,"given":"Sarah S.","family":"Osmundson","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology Vanderbilt University Medical Center  Nashville Tennessee USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan","family":"Colvin","sequence":"additional","affiliation":[{"name":"Department of Medicine, Division of Infectious Diseases Washington University School of Medicine  St. Louis Missouri USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dustin","family":"Stwalley","sequence":"additional","affiliation":[{"name":"Institute for Informatics Washington University School of Medicine  St. Louis Missouri USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1806-6502","authenticated-orcid":false,"given":"Elyse O.","family":"Kharbanda","sequence":"additional","affiliation":[{"name":"Pregnancy and Child Health Research Center HealthPartners Institute  Minneapolis Minnesota USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catherine A.","family":"Panozzo","sequence":"additional","affiliation":[{"name":"Epiphany Consulting, LLC  Pawtucket Rhode Island USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara S.","family":"Procknow","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Division of Genetics &amp; Genomic Medicine Washington University School of Medicine  St. Louis Missouri USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7307-6864","authenticated-orcid":false,"given":"Anne M.","family":"Butler","sequence":"additional","affiliation":[{"name":"Department of Medicine, Division of Infectious Diseases Washington University School of Medicine  St. Louis Missouri USA"},{"name":"Department of Surgery, Division of Public Health Sciences Washington University School of Medicine  St. Louis Missouri USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,4,9]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s40264\u2010025\u201001606\u2010w"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.4153"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.5177"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.3627"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.4967"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.1534"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.5128"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1161\/JAHA.121.024911"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.5244"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0067405"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0284893"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2025.19544"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/pds.4794"},{"key":"e_1_2_11_15_1","unstructured":"Sentinel Initiative \u201cCharacterizing Pregnant Women With and Without Evidence of Heart Failure and Non\u2010Pregnant Women With Heart Failure: A Propensity Score Matched Analysis \u201d(2024) https:\/\/dev.sentinelsystem.org\/projects\/AP\/repos\/sentinel\u2010analytic\u2010packages\/browse?at=refs%2Fheads%2Fcder_mpl2p_wp029."},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1097\/EDE.0000000000001559"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/26.4.404"},{"issue":"1","key":"e_1_2_11_18_1","first-page":"1","article-title":"Update on Overall Prevalence of Major Birth Defects \u2013 Atlanta, Georgia, 1978\u20132005","volume":"57","author":"Centers for Disease C, Prevention","year":"2008","journal-title":"MMWR. 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