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Evaluating common data models for use with a longitudinal community registry.

Maryam Garza1, Guilherme Del Fiol2, Jessica Tenenbaum3

  • 1Duke Translational Medicine Institute, Duke University, 2424 Erwin Road, Hock Plaza Box 3850, Durham, NC 27705, USA.

Journal of Biomedical Informatics
|December 20, 2016
PubMed
Summary
This summary is machine-generated.

The OMOP Common Data Model (CDM) is best for sharing electronic health record (EHR) data in longitudinal studies. It offers superior data element accommodation and terminology coverage compared to other models like Sentinel, PCORnet, and SDTM.

Keywords:
Common data modelData model evaluationElectronic health records

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Area of Science:

  • Health Informatics
  • Biomedical Data Standards
  • Electronic Health Records (EHR)

Background:

  • Sharing data from large, longitudinal electronic health record (EHR) databases is crucial for community registries.
  • Evaluating common data models (CDMs) is essential to identify the most effective methods for data standardization and interoperability.

Purpose of the Study:

  • To assess and compare the suitability of four prominent CDMs for sharing data from a large, longitudinal, EHR-based community registry.
  • To determine the optimal CDM that balances content coverage, data integrity, query efficiency, and implementation feasibility.

Main Methods:

  • Four CDMs were evaluated: Sentinel v5.0, PCORnet v3.0, OMOP v5.0, and CDISC SDTM v1.4.
  • An evaluation framework with 11 criteria across six categories (content coverage, integrity, flexibility, ease of querying, standards compatibility, ease/extent of implementation) was applied.
  • Data elements from a community registry were mapped to each CDM to assess compatibility.

Main Results:

  • The OMOP CDM demonstrated the highest data element accommodation (76%) and broader terminology coverage.
  • Sentinel and PCORnet showed lower content coverage at 37% and 48%, respectively.
  • CDISC SDTM accommodated 55% of data elements, but 45% required extensions (Supplemental Qualifiers), increasing query complexity.

Conclusions:

  • The OMOP CDM is the most suitable model for supporting data sharing from longitudinal EHR-based community registries.
  • The evaluation methodology is adaptable for assessing CDMs for other research applications and data types.