Evidence map›Paper›PMID 35576979›Full record

ArticleHealthcare informatics research2022

Applying the OMOP Common Data Model to Facilitate Benefit-Risk Assessments of Medicinal Products Using Real-World Data from Singapore and South Korea.

Hui Xing Tan, 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 and 1 more

Abstract read
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Article in Healthcare informatics research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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  3. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Hui Xing TanVigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore.
Desmond Chun Hwee TeoVigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore.
Dongyun LeeDepartment of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.
Chungsoo KimDepartment of Biomedical Sciences, Graduate School of Medicine, Ajou University, Suwon, Korea.
Jing Wei NeoVigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore.
Cynthia SungVigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore.
Haroun ChahedVigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore.
Pei San AngVigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore.
Doreen Su Yin TanDepartment of Pharmacy, Khoo Teck Puat Hospital, Singapore.
Rae Woong ParkDepartment of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.
Sreemanee Raaj DorajooVigilance & Compliance Branch, Health Products Regulation Group, Health Sciences Authority, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe 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.

methodsEMRs 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.

resultsOver 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.

conclusionsWhile 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.

Indexed as

AnticoagulantsData VisualizationHealth PolicyPharmacovigilanceRisk Assessment

Identifiers

PMID35576979
PMCPMC9117808

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.