Graduated: January 1, 2011
A Clinical Decision Support Model for Incorporating Pharmacogenomics Knowledge into Electronic Health Records for Drug Therapy Individualization: A Microcosm of Personalized Medicine
Personalized medicine, where treatment may be tailored to individual characteristics, has the potential to improve patient outcomes. As a microcosm of personalized medicine, findings from pharmacogenomics (PGx) studies have the potential to be applied to individualize drug therapy such that the efficacy is improved and the occurrence of adverse drug events are reduced. In this context, the overarching research question this research project aimed to address was: what needs to be done to incorporate PGx knowledge into an electronic health record (EHR) in a useful way that facilitates drug therapy individualization? Clinical decision support (CDS) imbedded in the EHR was investigated as a model for providing access to PGx knowledge to support accurately using and interpreting patient genetic data to individualize drug therapy. The aims of this research were: (1) characterizing PGx knowledge resources; (2) determining capabilities of current CDS systems; (3) developing a prototype implementation of a model for PGx CDS; and (4) evaluating the utility of the PGx CDS model implementation. Findings from this work enhances our understanding of how PGx knowledge should be made accessible via CDS in the EHR given characteristics of PGx knowledge, technical capabilities of current clinical systems and characteristics of clinicians. More generally, the results of this study contribute a model that is directly applicable to the incorporation of genetic and molecular data into EHRs and its usability by healthcare providers.
Last Known Position:
Assistant Professor, Johns Hopkins University
Peter Tarczy-Hornoch (Chair), Emily E. Devine, David Fenstermacher, Ira J. Kalet, Kenneth E. Thummel, Kelly Fryer-Edwards (GSR)