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Characterizing Fit-for-Purpose Real-World Data: An Assessment of a Mother-Infant Linkage in the Japan Medical Data Center Claims Database.
Barberio, Julie; Hernandez, Rohini K; Naimi, Ashley I; Patzer, Rachel E; Kim, Christopher; Lash, Timothy L.
Affiliation
  • Barberio J; Department of Epidemiology, Emory University, Atlanta, GA, USA.
  • Hernandez RK; Center for Observational Research, Amgen, Inc, Thousand Oaks, CA, USA.
  • Naimi AI; Center for Observational Research, Amgen, Inc, Thousand Oaks, CA, USA.
  • Patzer RE; Department of Epidemiology, Emory University, Atlanta, GA, USA.
  • Kim C; Department of Epidemiology, Emory University, Atlanta, GA, USA.
  • Lash TL; Regenstrief Institute, Indianapolis, IN, USA.
Clin Epidemiol ; 16: 31-43, 2024.
Article in En | MEDLINE | ID: mdl-38313043
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Clin Epidemiol Year: 2024 Document type: Article Affiliation country: Estados Unidos Country of publication: Nueva Zelanda

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Clin Epidemiol Year: 2024 Document type: Article Affiliation country: Estados Unidos Country of publication: Nueva Zelanda