Korean Circ J.  2022 Dec;52(12):853-864. 10.4070/kcj.2022.0294.

Establishment of an International Evidence Sharing Network Through Common Data Model for Cardiovascular Research

• You SC
• Lee S
• Choi B
• Park RW

• KMID: 2536787
• DOI: http://doi.org/10.4070/kcj.2022.0294

Abstract

A retrospective observational study is one of the most widely used research methods in medicine. However, evidence postulated from a single data source likely contains biases such as selection bias, information bias, and confounding bias. Acquiring enough data from multiple institutions is one of the most effective methods to overcome the limitations. However, acquiring data from multiple institutions from many countries requires enormous effort because of financial, technical, ethical, and legal issues as well as standardization of data structure and semantics. The Observational Health Data Sciences and Informatics (OHDSI) research network standardized 928 million unique records or 12% of the world’s population into a common structure and meaning and established a research network of 453 data partners from 41 countries around the world. OHDSI is a distributed research network wherein researchers do not own or directly share data but only analyzed results. However, sharing evidence without sharing data is difficult to understand. In this review, we will look at the basic principles of OHDSI, common data model, distributed research networks, and some representative studies in the cardiovascular field using the network. This paper also briefly introduces a Korean distributed research network named FeederNet.

Keyword

OHDSI; OMOP CDM; Real world data; Real world evidence; Open science

Figure

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  Figure 1 Principles of distributed research network and CDM. Sharing data is very difficult due to various technical, legal and human issues. In a distributed research network, multiple data sources with different structures and semantics are standardized into CDM with same structure and semantics. Researchers can send analysis code in R or SQL format to each institution and receive analysis results without sharing individual patient data.CDM = common data model.

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  Figure 2 FeederNet main page: www.feedernet.com.CDM = common data model.

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  Figure 3 Cumulative number of analyses using FeederNet.

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  Figure 4 Number of published peer-reviewed scientific papers authored by Korean researchers.

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