Applying the OMOP Common Data Model to Facilitate Benefit-Risk Assessments of Medicinal Products Using Real-World Data from Singapore and South Korea
10.4258/hir.2022.28.2.112
- Author:
Hui Xing TAN
1
;
Desmond Chun Hwee TEO
;
Dongyun LEE
;
Chungsoo KIM
;
Jing Wei NEO
;
Cynthia SUNG
;
Haroun CHAHED
;
Pei San ANG
;
Doreen Su Yin TAN
;
Rae Woong PARK
;
Sreemanee Raaj DORAJOO
Author Information
1. Vigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore
- Publication Type:Original Article
- From:Healthcare Informatics Research
2022;28(2):112-122
- CountryRepublic of Korea
- Language:English
-
Abstract:
Objectives:The aim of this study was to characterize the benefits of converting Electronic Medical Records (EMRs) to a common data model (CDM) and to assess the potential of CDM-converted data to rapidly generate insights for benefit-risk assessments in post-market regulatory evaluation and decisions.
Methods:EMRs from January 2013 to December 2016 were mapped onto the Observational Medical Outcomes Partnership-CDM (OMOP-CDM) schema. Vocabulary mappings were applied to convert source data values into OMOP-CDM-endorsed terminologies. Existing analytic codes used in a prior OMOP-CDM drug utilization study were modified to conduct an illustrative analysis of oral anticoagulants used for atrial fibrillation in Singapore and South Korea, resembling a typical benefit-risk assessment. A novel visualization is proposed to represent the comparative effectiveness, safety and utilization of the drugs.
Results:Over 90% of records were mapped onto the OMOP-CDM. The CDM data structures and analytic code templates simplified the querying of data for the analysis. In total, 2,419 patients from Singapore and South Korea fulfilled the study criteria, the majority of whom were warfarin users. After 3 months of follow-up, differences in cumulative incidence of bleeding and thromboembolic events were observable via the proposed visualization, surfacing insights as to the agent of preference in a given clinical setting, which may meaningfully inform regulatory decision-making.
Conclusions:While the structure of the OMOP-CDM and its accessory tools facilitate real-world data analysis, extending them to fulfil regulatory analytic purposes in the post-market setting, such as benefit-risk assessments, may require layering on additional analytic tools and visualization techniques.
