Evaluating common data models for use with a longitudinal community registry.
OBJECTIVE: To evaluate common data models (CDMs) to determine which is best suited for sharing data from a large, longitudinal, electronic health record (EHR)-based community registry. MATERIALS AND METHODS: Four CDMs were chosen from models in use for clinical research data: Sentinel v5.0 (referred to as the Mini-Sentinel CDM in previous versions), PCORnet v3.0 (an extension of the Mini-Sentinel CDM), OMOP v5.0, and CDISC SDTM v1.4. Each model was evaluated against 11 criteria adapted from previous research. The criteria fell into six categories: content coverage, integrity, flexibility, ease of querying, standards compatibility, and ease and extent of implementation. RESULTS: The OMOP CDM accommodated the highest percentage of our data elements (76%), fared well on other requirements, and had broader terminology coverage than the other models. Sentinel and PCORnet fell short in content coverage with 37% and 48% matches respectively. Although SDTM accommodated a significant percentage of data elements (55% true matches), 45% of the data elements mapped to SDTM's extension mechanism, known as Supplemental Qualifiers, increasing the number of joins required to query the data. CONCLUSION: The OMOP CDM best met the criteria for supporting data sharing from longitudinal EHR-based studies. Conclusions may differ for other uses and associated data element sets, but the methodology reported here is easily adaptable to common data model evaluation for other uses.
Garza, M; Del Fiol, G; Tenenbaum, J; Walden, A; Zozus, MN
Volume / Issue
Start / End Page
Pubmed Central ID
Electronic International Standard Serial Number (EISSN)
Digital Object Identifier (DOI)