Informatics Research Seminar: Standards-Based, Open-Source Clinical Decision Support Services: Rationale and Potential Opportunities for Inter-Institutional Collaboration

September 8 @ 4:00 – 5:00 pm


Speaker:  Kensaku Kawamoto
Presented from Duke University



While health informaticists have demonstrated repeatedly how clinical decision support (CDS) systems can improve health and health care, most patient care continues to be conducted with minimal CDS, if any. A promising strategy for enabling CDS at scale is the use of CDS Web services, which are capable of providing patient-specific inferencing capabilities as a software service accessed over a secure Internet connection. At Duke University, Dr. Kawamoto developed a CDS Web service known as SEBASTIAN that is currently in operational clinical use both within and outside of the Duke University Health System. Moreover, Dr. Kawamoto has led the development of a number of international standards required for scaling CDS services across institutions, including the HL7/OMG Decision Support Service standard and the emerging HL7 Virtual Medical Record standard.

Currently, Dr. Kawamoto is leading a multi-institutional collaborative effort to develop a next-generation CDS platform that is fully compliant with relevant international health IT standards and is freely available to the global clinical community. Ultimately, the goal of this effort is to create a widely deployed, Web-accessible CDS infrastructure that will enable evidence-based, computable CDS resources to be developed once and then efficiently shared across many healthcare institutions to improve health and health care, including through the appropriate use of advanced genomic technologies. In this talk, Dr. Kawamoto will describe why standards-based, open-source CDS services have the potential to enable advanced CDS and improved clinical care at scale, and he will seek to stimulate discussions on potential inter-institutional collaboration opportunities beyond those already initiated with key collaborators at UNC Chapel Hill.


Kensaku Kawamoto, MD, PhD is an Assistant Professor of Clinical Informatics with research interests in clinical decision support systems, electronic health record systems, population health management, and genomic and personalized medicine.

Dr. Kawamoto trained in biochemical sciences as an undergraduate at Harvard University, completed a Ph.D. in medical informatics from the Duke University Department of Biomedical Engineering in 2006, and earned an M.D. from the Duke University School of Medicine in 2008.

Dr. Kawamoto has been on the Duke clinical informatics faculty since 2006, and a Member of the Duke Institute for Genome Sciences & Policy since 2008. He has been the author or co-author of over a dozen peer-reviewed manuscripts and two book chapters, including two manuscripts that have been honored as seminal papers in medical informatics by the International Medical Informatics Association.

Beyond academics, Dr. Kawamoto has led the development of an international clinical decision support standard known as the Health Level 7 Decision Support Service standard. Dr. Kawamoto is actively engaged in operational health IT projects within the Duke University Health System, where a clinical decision support technology that he developed is being operationally used to provide patient-specific chronic disease management recommendations at the point of care. Under the mentorship of Dr. Geoffrey Ginsburg, Dr. Huntington Willard, and other senior faculty at the Duke Institute for Genome Sciences & Policy, Dr. Kawamoto is currently pursuing a K01 career development award from the National Human Genome Research Institute to develop a scalable and widely deployable clinical decision support system that could serve as a prototype for a replicable approach to integrating genomic medicine into routine clinical practice. His current areas of focus within genomic medicine include genetically guided warfarin dosing and the genetically guided selection of pharmaceutical interventions in the context of common chronic diseases.