The Health Research Exchange: A collaborative model for improving participation in health research
- Author(s): O'Connor, Laurie Jean;
- Advisor(s): Parker, Douglas S;
- et al.
Advancement in medical therapies requires clinical research to test a therapy's efficacy and safety in humans, yet this process can be slow, inefficient, and error prone. Two key problems resulting in delays are: 1) the translation of research ideas into relevant, testable hypotheses, and 2) the enrollment of subjects in clinical research that test these hypotheses. A crucial need for computational support is indicated by several challenges: the complex nature of the medical field, the large number of possible health hypotheses, and the variety and size of clinical research data.
Strong social and economic forces are changing the way healthcare works. Clinical research is evolving to emphasize increased efficiencies, productivity, and inclusion of health-consumer-centered outcomes. In the period of change, this research seeks to address these challenges through the design of a Health Research Exchange (HRE) that is a development and communication hub for health research hypotheses. The HRE improves upon existing health research databases, such as clinicaltrials.gov, by addressing the process of hypothesis formation. It seeks to facilitate health hypothesis development by non-medical professionals, enabling health research to become more relevant to health consumers.
The HRE is centered on the innovative Molecular Hypothesis Model (MoHM), featuring structured representation and reasoning about health hypotheses. The MoHM &mdash based upon the principles of connectedness, modularity, and functional specificity &mdash decomposes hypotheses into reusable, function-specific domains connected to each other and to facts, relationships, and other hypotheses. Implemented in a Hybrid Hypergraph Description Logic (HDL), integrating SNOMED&ndashCT medical terminology with hypergraph and Boolean formula representations, the MoHM overlays functional domains specialized for efficient, scalable reasoning with hypergraph connectivity of concepts.
The Molecular Hypothesis Model provides the foundation for three essential HRE capabilities: 1) an incremental hypothesis development methodology, enabling the reuse and recombination of hypothesis domain elements to form new hypotheses; 2) a hypothesis management capability, leveraging MoHM connectivity and modularity to provide support for construction and querying of hypotheses, and 3) a hypothesis collaboration protocol, enabling progressive engagement in health research collaboration, and efficient matching of health profiles to health research. These innovations are illustrated in the context of several health research examples.