Changes in Medication Use During Pregnancy for Women with Chronic Conditions: An Analysis of Claims Data.

PURPOSE: Evaluation of drug safety during pregnancy is dependent on the number of exposed women during routine clinical practice with data available for analysis. We examined medication fills in pregnant and nonpregnant women within select disease cohorts: general population, migraine, diabetes, and hyperlipidemia to explore the potential use of claims data to assess medication use and safety during pregnancy. METHODS: This cohort study, using IBM MarketScan® Research Databases claims data, included women 10-54 years of age with pregnancy resulting in a liveborn infant between January 2010 and September 2015 and matched nonpregnant women. Medication use (antidepressants, antihypertensives, sedatives, glucose-lowering medications, antiepileptics, antipsychotics, lipid-lowering medications) was abstracted from pharmacy claims 180 days before last menstrual period through 180 days postdelivery. RESULTS: Among 753,760 women in the general pregnancy population (including 73,268 migraine, 50,155 hyperlipidemia, and 8361 diabetes; non-exclusive cohorts), antidepressants, antihypertensives, and sedatives were the most commonly used medications during pregnancy. Medications of interest were less commonly used in the pregnancy cohort than in the matched nonpregnant cohort within each time period (e.g., 3.7% vs 13.1% antidepressant use in 1st trimester). Most prescription fills were less common during pregnancy then pre-pregnancy. Post-pregnancy, prescription fills increased to or exceeded pre-pregnancy levels, except antihypertensive and glucose-lowering medications, which increased during pregnancy. CONCLUSIONS: Medication use among pregnant women was low and different from that among matched nonpregnant women. The underlying size of large commercial claims databases offer opportunities for efficient evaluation of potential safety concerns, particularly for rare drug exposures, compared to traditional pregnancy registries.

Effects of expanding the look-back period to all available data in the assessment of covariates.

BACKGROUND: A fixed baseline period has been a common covariate assessment approach in pharmacoepidemiological studies from claims but may lead to high levels of covariate misclassification. Simulation studies have recommended expanding the look-back approach to all available data (AAD) for binary indicators of diagnoses, procedures, and medications, but there have been few real data analyses using this approach. OBJECTIVE: The objective of the study is to explore the impact on treatment effect estimates and covariate prevalence of expanding the look-back period within five validated studies in the Aetion system, a rapid cycle analytics platform. METHODS: We reran the five studies and assessed covariates using (i) a fixed window approach (usually 180 days before treatment initiation), (ii) AAD prior to treatment initiation, and (iii) AAD with a categorized by recency approach, where the most recent occurrence of a covariate was labeled as recent (occurring within the fixed window) or past (before the start of the fixed window). For each covariate assessment approach, we adjusted for covariates via propensity score matching. RESULTS: All studies had at least one covariate that had an increase in prevalence of 15% or higher from the fixed window to the AAD approach. However, there was little change in treatment effect estimates resulting from differing covariate assessment approaches. For example, in a study of acute coronary syndrome in high-intensity versus low-intensity statin users, the estimated hazard ratio from the fixed window approach was 1.11 (95% confidence interval 0.98, 1.25) versus 1.21 (1.07, 1.37) when using AAD and 1.19 (1.05, 1.35) using categorized by recency. CONCLUSION: Expanding the baseline period to AAD improved covariate sensitivity by capturing data that would otherwise be missed yet did not meaningfully change the overall treatment effect estimates compared with the fixed window approach. Copyright © 2017 John Wiley & Sons, Ltd.