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Related Experiment Video

Updated: May 6, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

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Utility of Treatment Pattern Analysis Using a Common Data Model: A Scoping Review.

Eun-Gee Park¹, Min Jung Kim², Jinseo Kim¹

¹Center for Data Science, Biomedical Research Institute, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea.

Healthcare Informatics Research

|February 20, 2025

Summary

This review of common data model publications shows Type 2 diabetes mellitus, hypertension, and depression are frequently studied diseases. Metformin is the most common first-line treatment for diabetes, with OMOP CDM enabling global research.

Keywords:

Cohort Studies Common Data Elements Drug Utilization Epidemiologic Methods Scoping Review

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Area of Science:

Observational Health Research
Data Science
Pharmacovigilance

Background:

Treatment patterns are crucial for understanding real-world drug effectiveness and safety.
Common Data Models (CDM) facilitate standardized analysis of large-scale health data.
The Observational Health Data Sciences and Informatics (OHDSI) initiative promotes collaborative research using CDMs.

Purpose of the Study:

To conduct a scoping review of publications utilizing common data models (CDM) to derive evidence on real-world treatment patterns.
To identify prevalent diseases, treatments, and analytical methods employed in CDM-based research.
To highlight the role of the Observational Medical Outcomes Partnership (OMOP) Common Data Model in multinational observational studies.

Main Methods:

A systematic literature search was performed on PubMed, EMBASE, and the OHDSI website.
Publications from January 1, 2010, to August 21, 2023, were screened for relevance to treatment patterns using CDMs.
Study characteristics, including disease phenotypes, patient populations, data sources, and analytical tools, were extracted and summarized.

Main Results:

Eighteen articles met the inclusion criteria for the scoping review.
Type 2 diabetes mellitus (5 articles), hypertension (4 articles), and depression (4 articles) were the most frequently studied conditions.
Biguanides (primarily metformin) were the most common first-line treatment for Type 2 diabetes mellitus; sunburst and Sankey plots were used for visualization.

Conclusions:

The review underscores the increasing significance of the OMOP CDM in facilitating large-scale, multinational observational studies.
CDM-based research enables robust analysis of treatment patterns, contributing to evidence-based healthcare.
The findings support the value of collaborative research networks in advancing understanding of real-world treatment strategies.