Applying a common data model to Asian databases for multinational pharmacoepidemiologic studies: opportunities and challenges.
Clin Epidemiol
; 10: 875-885, 2018.
Article
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| MEDLINE
| ID: mdl-30100761
ABSTRACT
OBJECTIVE:
The goal of the Asian Pharmacoepidemiology Network is to study the effectiveness and safety of medications commonly used in Asia using databases from individual Asian countries. An efficient infrastructure to support multinational pharmacoepidemiologic studies is critical to this effort. STUDY DESIGN ANDSETTING:
We converted data from the Japan Medical Data Center database, Taiwan's National Health Insurance Research Database, Hong Kong's Clinical Data Analysis and Reporting System, South Korea's Ajou University School of Medicine database, and the US Medicare 5% sample to the Observational Medical Outcome Partnership common data model (CDM).RESULTS:
We completed and documented the process for the CDM conversion. The coordinating center and participating sites reviewed the documents and refined the conversions based on the comments. The time required to convert data to the CDM varied widely across sites and included conversion to standard terminology codes and refinements of the conversion based on reviews. We mapped 97.2%, 86.7%, 92.6%, and 80.1% of domestic drug codes from the USA, Taiwan, Hong Kong, and Korea to RxNorm, respectively. The mapping rate from Japanese domestic drug codes to RxNorm (70.7%) was lower than from other countries, and we mapped remaining unmapped drugs to Anatomical Therapeutic Chemical Classification System codes. Because the native databases used international procedure coding systems for which mapping tables have been established, we were able to map >90% of diagnosis and procedure codes to standard terminology codes.CONCLUSION:
The CDM established the foundation and reinforced collaboration for multinational pharmacoepidemiologic studies in Asia. Mapping of terminology codes was the greatest challenge, because of differences in health systems, cultures, and coding systems.
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Bases de datos:
MEDLINE
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En
Revista:
Clin Epidemiol
Año:
2018
Tipo del documento:
Article
País de afiliación:
Taiwán