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Accepted for/Published in: JMIR Medical Informatics

Date Submitted: Feb 5, 2025
Date Accepted: May 20, 2025

The final, peer-reviewed published version of this preprint can be found here:

Pharmacoepidemiologic Research Based on Common Data Models: Systematic Review and Bibliometric Analysis

Zheng Y, Zhang M, Wang C, Gao L, Xie J, Shen P, Sun Y, Feng M, You Sc, Sun F

Pharmacoepidemiologic Research Based on Common Data Models: Systematic Review and Bibliometric Analysis

JMIR Med Inform 2025;13:e72225

DOI: 10.2196/72225

PMID: 40720860

PMCID: 12303556

Systematic review in pharmacoepidemiologic research based on common data models: a bibliometric perspective

  • Yongqi Zheng; 
  • Meng Zhang; 
  • Conghui Wang; 
  • Ling Gao; 
  • Junqing Xie; 
  • Peng Shen; 
  • Yexiang Sun; 
  • Menglin Feng; 
  • Seng chan You; 
  • Feng Sun

ABSTRACT

Background:

The adoption of Common Data Model (CDM) has significantly advanced pharmacoepidemiologic research by enabling standardized analyses across large populations through shared analytical code. Despite their growing importance, no systematic review has comprehensively assessed their global implementation.

Objective:

We conducted a systematic review and bibliometric analysis to map the landscape of CDM usage in pharmacoepidemiology, including publication trends, institutional authors and collaborations, and citation impacts.

Methods:

Five English databases (PubMed, Web of Science, EMBASE, Scopus, Virtual Health Library) and four Chinese databases (CNKI, Wan-Fang Data, VIP, SinoMed) were searched for studies applying CDMs in pharmacoepidemiology from database inception to January 2024. Two reviewers independently screened studies and extracted information about basic publication details, methodological details, and exposure and outcome information. The studies were categorized into two groups according to their Total Citation per Year (TCpY), and a comparative analysis was conducted to examine the differences in characteristics between the two groups.

Results:

Our analysis included 308 studies published between 1997 and 2024, from 32 countries, 1,580 authors and 140 journals. Among the ten top-cited studies, seven used the Vaccine Safety Datalink, two used Sentinel, and one used the Observational Medical Outcomes Partnership. High TCpY studies were significantly associated with multi-center collaboration (p=0.008), U.S.-based research (p=0.045), and and vaccine-focused investigations (p = 0.009) in comparison with the low TCpY studies. Most studies originated from the United States-based researchers and institutions, and reflected increasing international collaboration.

Conclusions:

This review supports the expanding use of CDMs in pharmacoepidemiology, with U.S. institutions leading the field, particularly on multi-center vaccine research. Our findings provide strategic insights for researchers in planning future studies, identifying collaboration opportunities, and selecting target journals in this rapidly evolving field.


 Citation

Please cite as:

Zheng Y, Zhang M, Wang C, Gao L, Xie J, Shen P, Sun Y, Feng M, You Sc, Sun F

Pharmacoepidemiologic Research Based on Common Data Models: Systematic Review and Bibliometric Analysis

JMIR Med Inform 2025;13:e72225

DOI: 10.2196/72225

PMID: 40720860

PMCID: 12303556

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