{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T06:17:20Z","timestamp":1793254640678,"version":"4.5.0"},"reference-count":26,"publisher":"Public Library of Science (PLoS)","issue":"4","license":[{"start":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T00:00:00Z","timestamp":1682294400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Pregnancy is a condition of broad interest across many medical and health services research domains, but one not easily identified in healthcare claims data. Our objective was to establish an algorithm to identify pregnant women and their pregnancies in claims data. We identified pregnancy-related diagnosis, procedure, and diagnosis-related group codes, accounting for the transition to International Statistical Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) diagnosis and procedure codes, in health encounter reporting on 10\/1\/2015. We selected women in Merative MarketScan commercial databases aged 15\u201349 years with pregnancy-related claims, and their infants, during 2008\u20132019. Pregnancies, pregnancy outcomes, and gestational ages were assigned using the constellation of service dates, code types, pregnancy outcomes, and linkage to infant records. We describe pregnancy outcomes and gestational ages, as well as maternal age, census region, and health plan type. In a sensitivity analysis, we compared our algorithm-assigned date of last menstrual period (LMP) to fertility procedure-based LMP (date of procedure + 14 days) among women with embryo transfer or insemination procedures. Among 5,812,699 identified pregnancies, most (77.9%) were livebirths, followed by spontaneous abortions (16.2%); 3,274,353 (72.2%) livebirths could be linked to infants. Most pregnancies were among women 25\u201334 years (59.1%), living in the South (39.1%) and Midwest (22.4%), with large employer-sponsored insurance (52.0%). Outcome distributions were similar across ICD-9 and ICD-10 eras, with some variation in gestational age distribution observed. Sensitivity analyses supported our algorithm\u2019s framework; algorithm- and fertility procedure-derived LMP estimates were within a week of each other (mean difference: -4 days [IQR: -13 to 6 days]; n = 107,870). We have developed an algorithm to identify pregnancies, their gestational age, and outcomes, across ICD-9 and ICD-10 eras using administrative data. This algorithm may be useful to reproductive health researchers investigating a broad range of pregnancy and infant outcomes.<\/jats:p>","DOI":"10.1371\/journal.pone.0284893","type":"journal-article","created":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T13:32:54Z","timestamp":1682343174000},"page":"e0284893","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":63,"title":["Identification of pregnancies and their outcomes in healthcare claims data, 2008\u20132019: An algorithm"],"prefix":"10.1371","volume":"18","author":[{"given":"Elizabeth C.","family":"Ailes","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weiming","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth A.","family":"Clark","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ya-lin A.","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Margaret A.","family":"Lampe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Athena P.","family":"Kourtis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennita","family":"Reefhuis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4942-7905","authenticated-orcid":true,"given":"Karen W.","family":"Hoover","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2023,4,24]]},"reference":[{"issue":"11","key":"pone.0284893.ref001","doi-asserted-by":"crossref","first-page":"927","DOI":"10.1002\/bdra.23573","article-title":"Using insurance claims data to identify and estimate critical periods in pregnancy: An application to antidepressants.","volume":"106","author":"EC Ailes","year":"2016","journal-title":"Birth Defects Res A Clin Mol Teratol"},{"issue":"7","key":"pone.0284893.ref002","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1002\/pds.4556","article-title":"Development of an algorithm to identify pregnancy episodes and related outcomes in health care claims databases: An application to antiepileptic drug use in 4.9 million pregnant women in France.","volume":"27","author":"PO Blotiere","year":"2018","journal-title":"Pharmacoepidemiol Drug Saf."},{"issue":"6","key":"pone.0284893.ref003","doi-asserted-by":"crossref","first-page":"758","DOI":"10.1089\/thy.2012.0488","article-title":"Prevalence of thyrotoxicosis, antithyroid medication use, and complications among pregnant women in the United States","volume":"23","author":"JJ Korelitz","year":"2013","journal-title":"Thyroid"},{"issue":"4","key":"pone.0284893.ref004","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1007\/s10995-007-0256-6","article-title":"An enhanced method for identifying obstetric deliveries: implications for estimating maternal morbidity.","volume":"12","author":"EV Kuklina","year":"2008","journal-title":"Matern Child Health J"},{"issue":"16","key":"pone.0284893.ref005","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1002\/bdr2.1580","article-title":"Data-driven queries between medications and spontaneous preterm birth among 2.5 million pregnancies.","volume":"111","author":"I Maric","year":"2019","journal-title":"Birth Defects Res"},{"issue":"2","key":"pone.0284893.ref006","doi-asserted-by":"crossref","first-page":"e0192033","DOI":"10.1371\/journal.pone.0192033","article-title":"Inferring pregnancy episodes and outcomes within a network of observational databases.","volume":"13","author":"A Matcho","year":"2018","journal-title":"PLoS One.PubMed Central PMCID"},{"issue":"9","key":"pone.0284893.ref007","doi-asserted-by":"crossref","first-page":"1211","DOI":"10.1002\/pds.4794","article-title":"Identifying pregnancies in insurance claims data: Methods and application to retinoid teratogenic surveillance.","volume":"28","author":"SC MacDonald","year":"2019","journal-title":"Pharmacoepidemiol Drug Saf"},{"key":"pone.0284893.ref008","doi-asserted-by":"crossref","first-page":"1129","DOI":"10.2147\/CLEP.S269400","article-title":"Impact of the Transition from ICD-9-CM to ICD-10-CM on the Identification of Pregnancy Episodes in US Health Insurance Claims Data.","volume":"12","author":"A Sarayani","year":"2020","journal-title":"Clin Epidemiol."},{"key":"pone.0284893.ref009","author":"Center for Medicare and Medicaid Services","journal-title":"General Equivalence Mappings for ICD-10-CM and ICD-10-PCS[11\/20\/2021]"},{"issue":"3","key":"pone.0284893.ref010","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1097\/AOG.0b013e3181d0c328","article-title":"Trends in the diagnosis and treatment of ectopic pregnancy in the United States.","volume":"115","author":"KW Hoover","year":"2010","journal-title":"Obstet Gynecol."},{"key":"pone.0284893.ref011","unstructured":"IBM MarketScan Research Databases User Guide: Commercial Insurance Weights (Data year 2019 edition)."},{"issue":"2","key":"pone.0284893.ref012","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1093\/aje\/kwy237","article-title":"Misclassification in Assessment of First Trimester In-utero Exposure to Drugs Used Proximally to Conception: the Example of Letrozole Utilization for Infertility Treatment","volume":"188","author":"ST Bird","year":"2019","journal-title":"Am J Epidemiol"},{"issue":"1","key":"pone.0284893.ref013","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1002\/pds.3319","article-title":"Validity of health plan and birth certificate data for pregnancy research.","volume":"22","author":"SE Andrade","year":"2013","journal-title":"Pharmacoepidemiol Drug Saf"},{"issue":"1","key":"pone.0284893.ref014","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1002\/pds.1862","article-title":"The identification of pregnancies within the general practice research database","volume":"19","author":"S Devine","year":"2010","journal-title":"Pharmacoepidemiol Drug Saf"},{"issue":"2","key":"pone.0284893.ref015","doi-asserted-by":"crossref","first-page":"908","DOI":"10.1111\/j.1475-6773.2006.00635.x","article-title":"Development of an algorithm to identify pregnancy episodes in an integrated health care delivery system","volume":"42","author":"MC Hornbrook","year":"2007","journal-title":"Health Serv Res"},{"issue":"5","key":"pone.0284893.ref016","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1002\/pds.3407","article-title":"Validation of an algorithm to estimate gestational age in electronic health plan databases.","volume":"22","author":"Q Li","year":"2013","journal-title":"Pharmacoepidemiol Drug Saf."},{"issue":"1","key":"pone.0284893.ref017","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1002\/pds.3284","article-title":"Algorithms to estimate the beginning of pregnancy in administrative databases.","volume":"22","author":"AV Margulis","year":"2013","journal-title":"Pharmacoepidemiology and Drug Safety"},{"issue":"27","key":"pone.0284893.ref018","doi-asserted-by":"crossref","first-page":"2898","DOI":"10.1016\/j.vaccine.2013.03.069","article-title":"Identifying pregnancy episodes, outcomes, and mother\u2013infant pairs in the Vaccine Safety Datalink","volume":"31","author":"AL Naleway","year":"2013","journal-title":"Vaccine"},{"issue":"4","key":"pone.0284893.ref019","first-page":"1","article-title":"Cause-of-death Data From the Fetal Death File, 2015\u20132017.","volume":"69","author":"DL Hoyert","year":"2020","journal-title":"Natl Vital Stat Rep."},{"issue":"1","key":"pone.0284893.ref020","first-page":"17","article-title":"Using a Birth Defects Surveillance Program to Enhance Existing Surveillance of Stillbirth","volume":"49","author":"C Duke WA","year":"2022","journal-title":"Journal of Registry Management"},{"issue":"2","key":"pone.0284893.ref021","first-page":"1","article-title":"Births: Final Data for 2019.","volume":"70","author":"JA Martin","year":"2021","journal-title":"Natl Vital Stat Rep."},{"issue":"1","key":"pone.0284893.ref022","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1080\/10796126.2016.1254601","article-title":"Examining the association between Medicaid coverage and preterm births using 2010\u20132013 National Vital Statistics Birth Data","volume":"23","author":"KS Markus AR","year":"2017","journal-title":"Journal of Children and Poverty"},{"issue":"5","key":"pone.0284893.ref023","first-page":"1","article-title":"Measuring Gestational Age in Vital Statistics Data: Transitioning to the Obstetric Estimate.","volume":"64","author":"JA Martin","year":"2015","journal-title":"Natl Vital Stat Rep."},{"issue":"2","key":"pone.0284893.ref024","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1002\/pds.5143","article-title":"Ondansetron use in early pregnancy and the risk of miscarriage.","volume":"30","author":"EA Suarez","year":"2021","journal-title":"Pharmacoepidemiol Drug Saf"},{"issue":"2","key":"pone.0284893.ref025","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1002\/pds.5151","article-title":"Ondansetron use in early pregnancy and the risk of late pregnancy outcomes.","volume":"30","author":"EA Suarez","year":"2021","journal-title":"Pharmacoepidemiol Drug Saf"},{"issue":"5","key":"pone.0284893.ref026","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1097\/EDE.0000000000001223","article-title":"Conceiving of Questions Before Delivering Analyses: Relevant Question Formulation in Reproductive and Perinatal Epidemiology.","volume":"31","author":"JM Snowden","year":"2020","journal-title":"Epidemiology."}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0284893","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T13:33:16Z","timestamp":1682343196000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0284893"}},"subtitle":[],"editor":[{"given":"Dickens Otieno","family":"Onyango","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2023,4,24]]},"references-count":26,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,4,24]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0284893","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,4,24]]}}}