Document Detail


Identifying appropriate reference data models for comparative effectiveness research (CER) studies based on data from clinical information systems.
MedLine Citation:
PMID:  23774519     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
INTRODUCTION: 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.
DISCUSSION: 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:
Omolola I Ogunyemi; Daniella Meeker; Hyeon-Eui Kim; Naveen Ashish; Seena Farzaneh; Aziz Boxwala
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  Medical care     Volume:  51     ISSN:  1537-1948     ISO Abbreviation:  Med Care     Publication Date:  2013 Aug 
Date Detail:
Created Date:  2013-06-24     Completed Date:  2013-09-13     Revised Date:  2014-04-08    
Medline Journal Info:
Nlm Unique ID:  0230027     Medline TA:  Med Care     Country:  United States    
Other Details:
Languages:  eng     Pagination:  S45-52     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Comparative Effectiveness Research / organization & administration*
Humans
Information Storage and Retrieval / methods
Models, Theoretical*
Systems Integration*
Vocabulary, Controlled
Grant Support
ID/Acronym/Agency:
1R01HS19913/HS/AHRQ HHS

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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