This Small Business Innovation Research (SBIR) Phase I project will focus on the enablement of comparative effectiveness research (CER) and evidence based medicine (EBM) by health care researchers utilizing both clinical and biomolecular data. The quality of health care can be significantly improved through the secondary use of health care data from electronic medical records systems (EMR) and also through the use of genomic biomarkers. Today, the current process of health care research using retrospective data from EMR requires a team of IT professionals and is very error prone. Further, these systems do not readily utilize the information that is available from genomic and genetic screens. The two goals of this project are: 1) to create a self-service, highly efficient query tool for health care data that can be utilized by clinical researchers and 2) to create a data mart that integrates EMR data with molecular data using a knowledge engine that brings context to biomarker data. The ultimate deliverable will be a system enables the entire life cycle of personalized medicine (PM); retrospective analysis, validation and report generation that directly impacts the care of the individual patient.
The broader impact/commercial potential of this project is significant because it capitalizes on two trends in health care - digitizing patient clinical data and the increased use of sequencing and microarray technology - in order to provide Personalized Medicine. The commercialization of the technical innovations referenced in this project will enable researchers and clinicians to generate EBM, CER and PM reports with the ultimate objective of improving patient outcomes. Leveraging historical patient data in CER to eliminate ineffective therapies from the health care system in general coupled with utilizing genetic information to create a more personalized model of health care will focus precious health care dollars on effective therapies optimized for the individual. Ultimately, this tool will be appealing to every segment of the health care industry including clinicians, researchers, pharmaceutical companies, and insurance companies due to the increases in quality and cost savings that will be created. True Personalized Medicine will have arrived.
Thanks to the Phase I grant and guidance by the NSF program manager Dr. Juan Figueroa, we have successfully accomplished our Phase I objectives. The project has delivered the following main outcomes. First, by providing a set of query and analysis tools for disparate data types including clinical data and molecular data (for example DNA, RNA, Proteins, etc.) that are accessible to physicians, our tools fulfill a key market need that will enable widespread Comparative Effectiveness Research (CER) and Evidence based medical research. This will enable researchers to use tools to do even more effective research. Second, we were able to create a new data integration environment enabling real-time access to clinical data for both analysis and for use in clinical decision support. Finally, we were able to validate with our customers and potential customers that our technology is feasible and beneficial to the needs of the researchers and clinicians seeking to do CER and evidence-based medicine. Taken together these components will improve clinical research and reduce the amount of time that is required before clinical discoveries can be employed to help patients. The inclusion of molecular data from genome seqencing in the tool will allow for the advancement of the state of practice of medicine to include truly personalized medicine, where drugs are prescribed that target the individual patient's disease instead of the disease as a class. The overall effect will be the simultaneous reduction of health care costs and improvement of the quality of care.
