Biomedical Engineering Reference
In-Depth Information
Objectives
and
deliverables
OMOP is testing whether observational data can be used
to improve understanding of drug safety and benefi t
outcomes. The three main objectives are:
•
Conduct a series of experiments to assess the
value, feasibility, and utility of observational data
(claims and electronic health record data) to
identify and evaluate the safety risks and potential
benefi ts of prescription drugs using a range of
analytical methods and multiple observational data
sources, beyond the currently available tools and
data sources
•
Test approaches for creating the infrastructure for
accessing and managing the required data, including
multiple claims and electronic health records data
sources
•
Establish and evaluate a suitable governance
structure for a public-private partnership for
these tasks and to inform future efforts to
monitor drug safety and benefi t outcomes
systematically
Description of
consortium
The core research team has designed and developed tools
and technologies for assessing data and databases.
Collaborators will be selected via an open, competitive
application and award process managed by the principle
investigators (PIs) and the OMOP executive director.
The research protocols, data models, database evaluation
and quality assurance tools, analytical programs, and
fi ndings generated by OMOP are being published and
made available, allowing other researchers the
opportunity to run the protocols on their own data and
develop parallel or complementary tools and approaches.
OMOP aims to encourage sharing of results and tools
developed in this way for the public benefi t; external
institutions whose aims are in alignment with those of
OMOP, who can credibly perform relevant research, and
who are willing to share tools, approaches, fi ndings, and
other intellectual property developed as a result may be
additionally recognized as members of the OMOP
Extended Research Consortium as announced in April
2010.
Time frame
2008 - 2010
Current status
Phase 1: completed in 2009
•
Established a consistent framework to use across
disparate observational data sources and an OMOP
research community
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