title: Identifying appropriate reference data models for comparative effectiveness research (CER) studies based on data from clinical information systems.
abstract: BACKGROUND
  The need for a common format for electronic exchange of clinical data prompted federal endorsement of applicable standards. However, despite obvious similarities, a consensus standard has not yet been selected in the comparative effectiveness research (CER) community.
  
  
  METHODS
  Using qualitative metrics for data retrieval and information loss across a variety of CER topic areas, we compare several existing models from a representative sample of organizations associated with clinical research: the Observational Medical Outcomes Partnership (OMOP), Biomedical Research Integrated Domain Group, the Clinical Data Interchange Standards Consortium, and the US Food and Drug Administration.
  
  
  RESULTS
  While the models examined captured a majority of the data elements that are useful for CER studies, data elements related to insurance benefit design and plans were most detailed in OMOP's CDM version 4.0. Standardized vocabularies that facilitate semantic interoperability were included in the OMOP and US Food and Drug Administration Mini-Sentinel data models, but are left to the discretion of the end-user in Biomedical Research Integrated Domain Group and Analysis Data Model, limiting reuse opportunities. Among the challenges we encountered was the need to model data specific to a local setting. This was handled by extending the standard data models.
  
  
  CONCLUSIONS
  We found that the Common Data Model from the OMOP met the broadest complement of CER objectives. Minimal information loss occurred in mapping data from institution-specific data warehouses onto the data models from the standards we assessed. However, to support certain scenarios, we found a need to enhance existing data dictionaries with local, institution-specific information.
authors.affiliation: Center for Biomedical Informatics, Charles Drew University of Medicine and Science, Los Angeles, CA 90262, USA. lolaogunyemi@cdrewu.edu
authors.forename: Omolola I
authors.initials: OI
authors.lastname: Ogunyemi
authors.forename: Daniella
authors.initials: D
authors.lastname: Meeker
authors.forename: Hyeon-Eui
authors.initials: HE
authors.lastname: Kim
authors.forename: Naveen
authors.initials: N
authors.lastname: Ashish
authors.forename: Seena
authors.initials: S
authors.lastname: Farzaneh
authors.forename: Aziz
authors.initials: A
authors.lastname: Boxwala
mesh_terms: D057186:Comparative Effectiveness Research / Q000458:organization & administration*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D008962:Models, Theoretical; D018511:Systems Integration; D018875:Vocabulary, Controlled