Characterizing Fit-for-Purpose Real-World Data: An Assessment of a Mother–Infant Linkage in the Japan Medical Data Center Claims Database

Abstract

Purpose

Observational postapproval safety studies are needed to inform medication safety during pregnancy. Real-world databases can be valuable for supporting such research, but fitness for regulatory purpose must first be vetted. Here, we demonstrate a fit-for-purpose assessment of the Japan Medical Data Center (JMDC) claims database for pregnancy safety regulatory decision-making.

Patients and Methods

The Duke-Margolis framework considers a database’s fitness for regulatory purpose based on relevancy (capacity to answer the research question based on variable availability and a sufficiently sized, representative population) and quality (ability to validly answer the research question based on data completeness and accuracy). To assess these considerations, we examined descriptive characteristics of infants and pregnancies among females ages 12–55 years in the JMDC between January 2005 and March 2022.

Results

For relevancy, we determined that critical data fields (maternal medications, infant major congenital malformations, covariates) are available. Family identification codes permitted linkage of 385,295 total mother–infant pairs, 57% of which were continuously enrolled during pregnancy. The prevalence of specific congenital malformation subcategories and maternal medical conditions were representative of the general population, but preterm births were below expectations (3.6% versus 5.6%) in this population. For quality, our methods are expected to accurately identify the complete set of mothers and infants with a shared health insurance plan. However, validity of gestational age information was limited given the high proportion (60%) of missing live birth delivery codes coupled with suppression of infant birth dates and inaccessibility of disease codes with gestational week information.

Conclusion

The JMDC may be well suited for descriptive studies of pregnant people in Japan (eg, comorbidities, medication usage). More work is needed to identify a method to assign pregnancy onset and delivery dates so that in utero medication exposure windows can be defined more precisely as needed for many regulatory postapproval pregnancy safety studies.

Keywords:

• routine health care data
• international databases
• database evaluation

Acknowledgments

This paper is based on the doctoral thesis of Julie Barberio, which is stored in Emory University’s institutional repository: https://etd.library.emory.edu/concern/etds/1j92g867s. The results of this study were presented as an oral presentation at the International Society for Pharmacoepidemiology’s 2023 Mid-Year Meeting. The conference abstract was published Pharmacoepidemiology and Drug Safety: https://doi.org/10.1002/pds.5688.

Disclosure

This study was funded by Amgen, Inc. Julie Barberio was supported by a doctoral training agreement between Emory University and Amgen, Inc and was an employee of Epidemiologic Research & Methods, LLC when this work was performed. Rohini K. Hernandez and Christopher Kim are employees of and own stock in Amgen, Inc. Timothy L. Lash is a member of the Amgen Methods Council, for which he receives travel support and consulting fees. The authors report no other conflicts of interest in this work.