Identification of pregnancies and infants within a US commercial healthcare administrative claims database

Abstract

Purpose: Health care insurance claims databases are becoming a more common data source for studies of medication safety during pregnancy. While pregnancies have historically been identified in such databases by pregnancy outcomes, International Classification of Diseases, 10th revision Clinical Modification (ICD-10-CM) Z3A codes denoting weeks of gestation provide more granular information on pregnancies and pregnancy periods (i.e., start and end dates). The purpose of this study was to develop a process that uses Z3A codes to identify pregnancies, pregnancy periods, and links infants within a commercial health insurance claims database. Methods: We identified pregnancies, gestation periods, pregnancy outcomes, and linked infants within the US-based Optum Research Database between 2015 and 2020 via a series of algorithms utilizing diagnosis and procedure codes on claims. The diagnosis and procedure codes included ICD-10-CM codes, Current Procedural Terminology (CPT) codes, and Healthcare Common Procedure Coding System (HCPCS) codes. Results:We identified 1 030 874 pregnancies among 841 196 women of reproductive age. Of pregnancies with livebirth outcomes, 84% were successfully linked to infants. The prevalence of pregnancy outcomes (livebirth, stillbirth, ectopic, molar, and abortion) was similar to national estimates. Conclusions:This process provides an opportunity to study drug safety and care patterns during pregnancy and may be replicated in other claims databases containing ICD-10-CM, CPT, and HCPCS codes. Work is underway to validate and refine the various algorithms.

Distribution of gestational age by maternal and infant characteristics in US birth certificate data: informing gestational age assumptions when clinical estimates are not available

“…Research groups have used the median 1,2,4 or the mode 1 GAB to estimate pregnancy duration; one may wonder whether the median, the mode, or even the mean GAB is most appropriate for estimations. We found that the median and the mode are the same for many groups.…”

“…International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) Z3A codes for gestational age facilitate the process in claims data sources in the United States (US) to a certain extent. 1 For pregnancies without the relevant clinical or obstetric information and without informative codes, researchers use other estimation methods. Often, such pregnancies are assigned a fixed duration based on the observed mode or median gestational age at birth (GAB) of pregnancies with some known characteristic, such as 34, 2 35 ,1,3,4 or 36 5 weeks for preterm live births; 39 1,4 or 40 2,3,5 weeks for term live births, or 37 weeks for multifetal pregnancies.…”

“…1 For pregnancies without the relevant clinical or obstetric information and without informative codes, researchers use other estimation methods. Often, such pregnancies are assigned a fixed duration based on the observed mode or median gestational age at birth (GAB) of pregnancies with some known characteristic, such as 34, 2 35 ,1,3,4 or 36 5 weeks for preterm live births; 39 1,4 or 40 2,3,5 weeks for term live births, or 37 weeks for multifetal pregnancies. 5 Then, the assigned GAB is subtracted from the delivery or birth date (which is usually available) to estimate the pregnancy start date and assess the timing of exposure relative to pregnancy start.…”

Identification of pregnancies in healthcare data: A changing landscape

“…However, such pregnancy‐related entries have typically been used only in gestational age algorithms to pinpoint the beginning of pregnancy in completed pregnancies 3–5 . The recently published paper by Bertoia et al 6 puts forward two interesting concepts. First, it uses the relatively new US‐specific Z3A codes in the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD‐10‐CM), which indicate gestational age in weeks on the date of the encounter.…”

“…If the pregnancy is assumed to have ended at the time that the first outcome‐related code is observed and is classified as that particular outcome, subsequent conflicting codes will never be considered and these inconsistencies in the data will never be addressed. Bertoia et al 6 addressed this by looking for pregnancy outcomes in appropriate windows after the estimated LMP and applying hierarchical algorithms to identify the most likely outcome and outcome date for each pregnancy. While this approach is helpful for resolving data inconsistencies, it is debatable whether such an approach, which implies looking into the future to classify the outcome, is consistent with the idea of prospective identification and follow‐up of pregnancies.…”