Abstract
Background/Aims The American Recovery and Reinvestment Act (ARRA) provided $1.1 billion for Comparative Effectiveness Research (CER) with the goal of generating new evidence on the effectiveness of different treatments, diagnostic procedures, and care models under “real world” conditions. AHRQ awarded $100 million of ARRA funds to a dozen R01 projects to develop clinical infrastructure focusing on use of comprehensive electronic medical record (EMR) systems for large-scale, multi-institutional CER. However, numerous informatics challenges must be overcome when combining and sharing data across EMR systems and across institutions. In short, CER requires aggregation and analysis of disparate electronic clinical data sources held by different institutions, each with its own representation of relevant events and concerns for protecting data.
Methods The AHRQ-funded CER-HUB project will provide infrastructure for flexible, rapid, and efficient utilization of distributed, heterogeneous, electronic clinical data for CER analyses. The CER- HUB will provide a means for collaborative development and validation of standardized, study-specific processors of distributed clinical data. These processors extend a classification technology (MediClass) that uses both free-text and coded data, enabling comprehensive capture of the clinical events of interest. A central website hosts these tools including a library of processors that can be iteratively refined, validated, and reused by any end-user.
Results Dr. Hazlehurst will describe 18 months of progress toward CER-HUB study aims, including progress reports on two demonstration studies (addressing the effectiveness of smoking cessation services and step-up therapies for asthma control) being conducted by a consortium of six geographically-distributed and demographically-diverse health systems. He will demonstrate the processes of using the CER-HUB including
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policies and methods for creating a new research study,
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building and validating a study-specific data processor addressing study questions, and
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generating standardized study data from multiple health care systems while protecting patient confidentiality.
Discussion CER-HUB users collaboratively build software applications (specializations of the base MediClass system) that process EMR data within their respective healthcare organizations, creating standardized datasets that can be pooled for analysis. The CER-HUB provides an open platform for researchers, program evaluators, and health system managers to use EMR data to answer diverse healthcare study questions.
