Development of a mother-child database for drug exposure and adverse event detection in the Military Health System

Taylor, Lisa; Jean, Rosenie Thelus; Gordon, Geoff; Fram, David; Coster, Trinka S.

doi:10.1002/pds.3759

Cited by 14 publications

(21 citation statements)

References 26 publications

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“…Prevalence estimates stratified by the quality assessment of an appropriate sample frame indicated lower prevalence rates in appropriate sample frames (2.20%) compared to non-appropriate sample frames (3.85%; p-value <0.01). Studies with a detailed description of subjects and setting had a lower prevalence rate (3.02%) compared to studies without (4.20%; p-value <0.01), although only two studies in this analysis lacked a detailed description (Taylor et al, 2015;Yamamoto-Sasaki et al, 2019).…”

Section: Sensitivity Analysismentioning

confidence: 65%

The international prevalence of antidepressant use before, during, and after pregnancy: A systematic review and meta-analysis of timing, type of prescriptions and geographical variability

Molenaar

Bais

Berg³

et al. 2020

Journal of Affective Disorders

110

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Background: Antidepressant use during pregnancy has increased over the last decades, while safety has been under debate. Our aim was to measure the international prevalence of antidepressant use before, during, and after pregnancy and examine timing, type of prescriptions and geographic variability. Methods: We searched Embase, Medline Ovid, Web of Science, Cochrane Central and Google Scholar from their inception until February 19, 2019. We determined pooled prevalence estimates of antidepressants before, during, and after pregnancy, as well as stratified according to substantive variables. Results: We identified 40 cohorts from 15 countries, together reporting on 14,072,251 pregnancies. Included studies had a low risk of bias, often reporting on large representative cohorts. Selective serotonin reuptake inhibitors (SSRIs) were the most commonly used antidepressants during pregnancy, with an international prevalence estimate of 3.0% (95%CI 2.3;3.7). While Europe and Australasia had pooled prevalence estimates of 1.6% and 1.3% respectively, Northern America had a prevalence estimate of 5.5% (Q-value = 126.19; df = 2; p-value<0.01). Highest SSRI prevalence rates were found for sertraline (1.10%), followed by citalopram and fluoxetine (0.77% and 0.76% respectively) (Q-value = 121.25; df = 5; p-value<0.01). Qualitative analysis indicated an increase in antidepressant use over subsequent calendar years. Limitations: Substantial heterogeneity remained unaccounted for throughout the analyses, even after accounting for hypothetical contributors. Conclusions: This meta-analysis revealed substantial regional differences in antidepressant use around pregnancy, which could be due to variability in prescription behavior, healthcare seeking behavior and organization of healthcare. There is an urgent need for evidence on effectiveness, benefit, and harm of antidepressants during pregnancy to guide clinical practice. greatly contribute to this increase (Andrade et al., 2016;Charlton et al., 2015;Cooper et al., 2007). In the general population, antidepressants are now among the top three most commonly prescribed therapeutic drug classes in the United States (Pratt et al., 2017). Antidepressants showed the largest increase in prescriptions during pregnancy over time, compared to other drugs associated with potential harmful neonatal effects (van Gelder et al., 2014).

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Section: Sensitivity Analysismentioning

confidence: 65%

The international prevalence of antidepressant use before, during, and after pregnancy: A systematic review and meta-analysis of timing, type of prescriptions and geographical variability

Molenaar

Bais

Berg³

et al. 2020

Journal of Affective Disorders

110

View full text Add to dashboard Cite

show abstract

“…A few focused exclusively on live births, excluding other birth outcomes such as abortions (6, 7, 10). Some estimated pregnancy start by subtracting an estimated gestational age from the pregnancy outcome date [ 2 , 6 , 9 , 10 ], while others used early pregnancy markers or combined both methods to infer start [ 1 , 3 – 5 , 7 , 8 ]. Early pregnancy markers such as the nuchal ultrasound procedure can be used to infer pregnancy start based on clinical care guidelines (recommended gestational age for procedure can be subtracted from procedure date to infer a pregnancy start).…”

Section: Introductionmentioning

confidence: 99%

Inferring pregnancy episodes and outcomes within a network of observational databases

et al. 2018

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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.

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“…However, health insurance claims data tend to lack critical pieces of information (e.g., estimated due date, date of last menstrual period, date of delivery) that make it difficult to accurately identify pregnant women, pregnancy outcomes, or estimate the gestational length of pregnancies. Although some researchers have overcome these challenges by linking maternal and infant records within the same data source (Taylor et al, ) or linking administrative claims data to vital records, electronic medical records, or other healthcare data (Cooper et al, ; Pasternak et al, ), these types of linkages are not always possible. Thus, some researchers have attempted to identify and estimate gestational ages of pregnancy outcomes solely from information in administrative data; many of these methods are well‐described by Margulis and colleagues (Margulis et al, ).…”

Section: Introductionmentioning

confidence: 99%

Using insurance claims data to identify and estimate critical periods in pregnancy: An application to antidepressants

Ailes

Simeone

Dawson

et al. 2016

Birth Defects Research

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Background Health insurance claims are a rich data source to examine medication use in pregnancy. Our objective was to identify pregnant women, their pregnancy outcomes, and date of their last menstrual period (LMP), and to estimate antidepressant dispensations in pregnancy. Methods From a literature search, we identified diagnosis and procedure codes indicating the end of a pregnancy. Using Truven Health MarketScan® Commercial Claims and Encounters Databases, we identified all inpatient admissions and outpatient service claims with these codes. We developed an algorithm to assign: (1) pregnancy outcome (ectopic pregnancy, induced or spontaneous abortion, live birth, or stillbirth), and (2) estimated gestational age, to each inpatient or outpatient visit. For each pregnancy outcome, we estimated the LMP as the admission (for inpatient visits) or service (for outpatient visits) date minus the gestational age. To differentiate visits associated with separate pregnancies, we required ≥ 2 months between one pregnancy outcomes and the LMP of the next pregnancy. We used this algorithm to identify pregnancies in 2013 and to estimate the proportion of women who filled a prescription for an antidepressant from an outpatient pharmacy at various time points in pregnancy. Results We identified 488,887 pregnancies in 2013; 79% resulted in a live birth. A prescription for an antidepressant was filled in 6.2% of pregnancies. Dispensations varied throughout pregnancy and were lowest (3.1%) during the second trimester. Conclusion This work will inform future efforts to estimate medication dispensations during critical periods of preconception, interconception, and pregnancy using health insurance claims data.

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Development of a mother-child database for drug exposure and adverse event detection in the Military Health System

Cited by 14 publications

References 26 publications

The international prevalence of antidepressant use before, during, and after pregnancy: A systematic review and meta-analysis of timing, type of prescriptions and geographical variability

The international prevalence of antidepressant use before, during, and after pregnancy: A systematic review and meta-analysis of timing, type of prescriptions and geographical variability

Inferring pregnancy episodes and outcomes within a network of observational databases

Using insurance claims data to identify and estimate critical periods in pregnancy: An application to antidepressants

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