Susan E Andrade1, Sengwee Toh2, Monika Houstoun3, Katrina Mott3, Marilyn Pitts3, Caren Kieswetter3, Carrie Ceresa3, Katherine Haffenreffer2, Marsha E Reichman3. 1. Meyers Primary Care Institute (Fallon Community Health Plan, Reliant Medical Group, and University of Massachusetts Medical School), 630 Plantation St., Worcester, MA, 01605, USA. sandrade@meyersprimary.org. 2. Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA. 3. Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD, USA.
Abstract
OBJECTIVES: Mini-Sentinel is a pilot project sponsored by the U.S. Food and Drug Administration to create an active surveillance system to monitor the safety of FDA-regulated medical products. We assessed the capability of the Mini-Sentinel pilot to provide prevalence rates of medication use among pregnant women delivering a liveborn infant. METHODS: An algorithm was developed to identify pregnancies for a reusable analytic tool to be executed against the Mini-Sentinel Distributed Database. Diagnosis and procedure codes were used to identify women ages 10-54 years delivering a liveborn infant between April 2001 and December 2012. A comparison group of age- and date-matched nonpregnant women was identified. The analytic code was distributed to all 18 Mini-Sentinel data partners. The use of specific medications, selected because of concerns about their safe use during pregnancy, was identified from outpatient dispensing data. We determined the frequency of pregnancy episodes and nonpregnant episodes exposed to medications of interest, any time during the pregnant/matched nonpregnant period, and during each trimester. RESULTS: The analytic tool successfully identified 1,678,410 live birth deliveries meeting the eligibility criteria. The prevalence of use at any time during pregnancy was 0.38 % for angiotensin-converting enzyme inhibitors and 0.22 % for statins. For ≤0.05 % of pregnancy episodes, the woman was dispensed warfarin, methotrexate, ribavirin, or mycophenolate. CONCLUSIONS: The analytic tool developed for this study can be used to assess the use of medications during pregnancy as safety issues arise, and is adaptable to include different medications, observation periods, pre-existing conditions, and enrollment criteria.
OBJECTIVES: Mini-Sentinel is a pilot project sponsored by the U.S. Food and Drug Administration to create an active surveillance system to monitor the safety of FDA-regulated medical products. We assessed the capability of the Mini-Sentinel pilot to provide prevalence rates of medication use among pregnant women delivering a liveborn infant. METHODS: An algorithm was developed to identify pregnancies for a reusable analytic tool to be executed against the Mini-Sentinel Distributed Database. Diagnosis and procedure codes were used to identify women ages 10-54 years delivering a liveborn infant between April 2001 and December 2012. A comparison group of age- and date-matched nonpregnant women was identified. The analytic code was distributed to all 18 Mini-Sentinel data partners. The use of specific medications, selected because of concerns about their safe use during pregnancy, was identified from outpatient dispensing data. We determined the frequency of pregnancy episodes and nonpregnant episodes exposed to medications of interest, any time during the pregnant/matched nonpregnant period, and during each trimester. RESULTS: The analytic tool successfully identified 1,678,410 live birth deliveries meeting the eligibility criteria. The prevalence of use at any time during pregnancy was 0.38 % for angiotensin-converting enzyme inhibitors and 0.22 % for statins. For ≤0.05 % of pregnancy episodes, the woman was dispensed warfarin, methotrexate, ribavirin, or mycophenolate. CONCLUSIONS: The analytic tool developed for this study can be used to assess the use of medications during pregnancy as safety issues arise, and is adaptable to include different medications, observation periods, pre-existing conditions, and enrollment criteria.
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