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Lyons JG, Shinde MU, Maro JC, Petrone A, Cosgrove A, Kempner ME, Andrade SE, Mwidau J, Stojanovic D, Hernández-Muñoz JJ, Toh S. Use of the Sentinel System to Examine Medical Product Use and Outcomes During Pregnancy. Drug Saf 2024; 47:931-940. [PMID: 38940904 DOI: 10.1007/s40264-024-01447-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/15/2024] [Indexed: 06/29/2024]
Abstract
While many pregnant individuals use prescription medications, evidence supporting product safety during pregnancy is often inadequate. Existing electronic healthcare data sources provide large, diverse samples of health plan members to allow for the study of medical product utilization during pregnancy, as well as pregnancy, maternal, and infant outcomes. The Sentinel System is a national medical product surveillance system that includes administrative claims and electronic health record databases from large national and regional health insurers. In addition to these data sources, Sentinel develops and maintains a sizeable selection of analytic tools to facilitate epidemiologic analyses in a way that protects patient privacy and health system autonomy. In this article, we provide an overview of Sentinel System infrastructure, including the Mother-Infant Linkage Table, parameterizable analytic tools, and algorithms to estimate gestational age and identify pregnancy outcomes. We also describe past and future Sentinel work that contributes to our understanding of the way medical products are used and the safety of these products during pregnancy.
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Affiliation(s)
- Jennifer G Lyons
- Division of Therapeutics Research and Infectious Disease Epidemiology, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401 East, Boston, MA, 02215, USA.
| | - Mayura U Shinde
- Division of Therapeutics Research and Infectious Disease Epidemiology, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401 East, Boston, MA, 02215, USA
| | - Judith C Maro
- Division of Therapeutics Research and Infectious Disease Epidemiology, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401 East, Boston, MA, 02215, USA
| | - Andrew Petrone
- Division of Therapeutics Research and Infectious Disease Epidemiology, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401 East, Boston, MA, 02215, USA
| | - Austin Cosgrove
- Division of Therapeutics Research and Infectious Disease Epidemiology, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401 East, Boston, MA, 02215, USA
| | - Maria E Kempner
- Division of Therapeutics Research and Infectious Disease Epidemiology, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401 East, Boston, MA, 02215, USA
| | - Susan E Andrade
- Division of Therapeutics Research and Infectious Disease Epidemiology, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401 East, Boston, MA, 02215, USA
| | - Jamila Mwidau
- Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Danijela Stojanovic
- Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - José J Hernández-Muñoz
- Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Sengwee Toh
- Division of Therapeutics Research and Infectious Disease Epidemiology, Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, 401 Park Drive, Suite 401 East, Boston, MA, 02215, USA
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Chiu YH, Huybrechts KF, Zhu Y, Straub L, Bateman BT, Logan R, Hernández-Díaz S. Internal validation of gestational age estimation algorithms in health-care databases using pregnancies conceived through fertility procedures. Am J Epidemiol 2024; 193:1168-1175. [PMID: 38583933 PMCID: PMC11299027 DOI: 10.1093/aje/kwae045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 01/15/2024] [Accepted: 04/04/2024] [Indexed: 04/09/2024] Open
Abstract
Fertility procedures recorded in health-care databases can be used to estimate the start of pregnancy, which can serve as a reference standard to validate gestational age estimates based on International Classification of Diseases codes. In a cohort of 17 398 US MarketScan pregnancies (2011-2020) in which conception was achieved via fertility procedures, we estimated gestational age at the end of pregnancy using algorithms based on (1) time (days) since the fertility procedure (the reference standard); (2) International Classification of Diseases, Ninth Revision (ICD-9)/International Classification of Diseases, Tenth Revision (ICD-10) (before/after October 2015) codes indicating gestational length recorded at the end of pregnancy (method A); and (3) ICD-10 end-of-pregnancy codes enhanced with Z3A codes denoting specific gestation weeks recorded at prenatal visits (method B). We calculated the proportion of pregnancies with an estimated gestational age falling within 14 days ($\pm$14 days) of the reference standard. Method A accuracy was similar for ICD-9 and ICD-10 codes. After 2015, method B was more accurate than method A: For term births, within-14-day agreement was 90.8% for method A and 98.7% for method B. Corresponding estimates were 70.1% and 95.6% for preterm births; 35.3% and 92.6% for stillbirths; 54.3% and 64.2% for spontaneous abortions; and 16.7% and 84.6% for elective terminations. ICD-10-based algorithms that incorporate Z3A codes improve the accuracy of gestational age estimation in health-care databases, especially for preterm births and non-live births.
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Affiliation(s)
- Yu-Han Chiu
- CAUSALab and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States
| | - Krista F Huybrechts
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02120, United States
| | - Yanmin Zhu
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02120, United States
| | - Loreen Straub
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02120, United States
| | - Brian T Bateman
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA 94305, United States
| | - Roger Logan
- CAUSALab and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States
| | - Sonia Hernández-Díaz
- CAUSALab and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States
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Margulis AV, Huybrechts K. Identification of pregnancies in healthcare data: A changing landscape. Pharmacoepidemiol Drug Saf 2023; 32:84-86. [PMID: 35976191 DOI: 10.1002/pds.5526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 08/13/2022] [Indexed: 02/06/2023]
Affiliation(s)
- Andrea V Margulis
- Pharmacoepidemiology and Risk Management, RTI Health Solutions, Barcelona, Spain
| | - Krista Huybrechts
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
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