Distributed Research Networks for Next-Generation Knowledge Acquisition
Abstract: Over the past half-century and longer, researchers from many quarters have successfully investigated many varied health-related questions using existing data from clinical settings such as hospitals, clinics, and health systems. These included evaluating the comparative effectiveness of therapeutic modalities, identifying new adverse effects of drugs, conducting disease surveillance, and performing retrospective studies of diseases. However, it was not long before researchers and clinicians realized the inadequacy of these data for teasing out the complexities of disease or for establishing results that are generalizable to a population broader than that which was investigated. It became evident that larger, more representative datasets needed to be created and made available to a wide research community in order to conduct these investigations. As a result, researchers have been turning to Distributed Research Networks (DRNs) to investigate myriad health problems.
DRNs provide researchers, clinicians, and administrators with a sophisticated platform for sharing and using data across multiple institutions in such a way that patient privacy and confidentiality are preserved, while facilitating rapid access and dissemination of analytic results. However, DRNs also create substantial challenges for the informatics community in areas such as syntactic and semantic harmonization, data currency, and data governance. We will explore the opportunities and challenges posed by the DRN model, from its beginnings to the current day in the US, especially with the advent of the Clinical Data Research Networks of the Patient Centered Clinical Research Network (PCORnet). Most importantly, we will explore the use of DRNs not only as sources of data, but their potential as platforms for acquiring, and managing new knowledge.