Abstract
Administrative claims and electronic health records are valuable resources for evaluating pharmaceutical effects during pregnancy. However, direct measures of gestational age are generally not available. Establishing a reliable approach to infer the duration and outcome of a pregnancy could improve pharmacovigilance activities. We developed and applied an algorithm to define pregnancy episodes in four observational databases: three US-based claims databases: Truven MarketScan® Commercial Claims and Encounters (CCAE), Truven MarketScan® Multi-state Medicaid (MDCD), and the Optum ClinFormatics® (Optum) database and one non-US database, the United Kingdom (UK) based Clinical Practice Research Datalink (CPRD). Pregnancy outcomes were classified as live births, stillbirths, abortions and ectopic pregnancies. Start dates were estimated using a derived hierarchy of available pregnancy markers, including records such as last menstrual period and nuchal ultrasound dates. Validation included clinical adjudication of 700 electronic Optum and CPRD pregnancy episode profiles to assess the operating characteristics of the algorithm, and a comparison of the algorithm’s Optum pregnancy start estimates to starts based on dates of assisted conception procedures. Distributions of pregnancy outcome types were similar across all four data sources and pregnancy episode lengths found were as expected for all outcomes, excepting term lengths in episodes that used amenorrhea and urine pregnancy tests for start estimation. Validation survey results found highest agreement between reviewer chosen and algorithm operating characteristics for questions assessing pregnancy status and accuracy of outcome category with 99–100% agreement for Optum and CPRD. Outcome date agreement within seven days in either direction ranged from 95–100%, while start date agreement within seven days in either direction ranged from 90–97%. In Optum validation sensitivity analysis, a total of 73% of algorithm estimated starts for live births were in agreement with fertility procedure estimated starts within two weeks in either direction; ectopic pregnancy 77%, stillbirth 47%, and abortion 36%. An algorithm to infer live birth and ectopic pregnancy episodes and outcomes can be applied to multiple observational databases with acceptable accuracy for further epidemiologic research. Less accuracy was found for start date estimations in stillbirth and abortion outcomes in our sensitivity analysis, which may be expected given the nature of the outcomes.
Highlights
Administrative claims databases and electronic health records are valuable resources for evaluating effects of exposures, including prescription drug exposures during pregnancy, on pregnancy outcomes
Distributions of pregnancy outcome types were similar across all data sources: live birth proportions were 71.59%, 72.84%, 72.85% and 79.83%, abortion 27.16%, 25.59%, 25.49% and 18.05%, stillbirth 0.45%, 0.47%, 0.45% and 0.78% and ectopic pregnancies 0.79%, 1.10%, 1.21% and 1.35% in Clinical Practice Research Datalink (CPRD), Optum, Commercial Claims and Encounters (CCAE) and MDCD, respectively
To the best of our knowledge, there is no prior algorithm that incorporates all of the following features: assessment of multiple pregnancy outcomes, start estimation leveraging a hierarchy of available start markers, internal validation using electronic patient profiles with consideration of the patient’s entire clinical experience, and validation of the generic algorithm across multiple, disparate data sources
Summary
Administrative claims databases and electronic health records are valuable resources for evaluating effects of exposures, including prescription drug exposures during pregnancy, on pregnancy outcomes. Usually established when a medication is marketed, are expensive to execute They capture relatively modest numbers of pregnancies compared to administrative claims databases and electronic health records and are subject to recall bias, especially if the exposure data are collected after delivery. The use of claims and electronic health record data in the study of pregnancy exposures has several advantages including capture of prescription dispensing data, longitudinal follow-up from drug exposure through pregnancy outcome, potential mother-infant linkage, and large enough samples to study rare pregnancy outcomes. Direct measures of gestational age are usually not available in claims databases and electronic health records This creates challenges when estimating pregnancy start dates and understanding the potential impact of drug exposure on a fetus at a given gestational age
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