Developing a Prototype System for Integrating Pharmacogenomics Findings into Clinical Practice
by
1,2,*,†, Peter Tarczy-Hornoch 1,3,4,†, Ira J. Kalet 1,5, Kenneth E. Thummel 6, Joe W. Smith 7, Guilherme Del Fiol 8, David Fenstermacher 9 and Emily Beth Devine 1,10,11
1
Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA
2
Department of Biomedical Informatics, Columbia University, New York, NY 10032, USA
3
Department of Pediatrics, University of Washington, Seattle, WA 98195, USA
4
Department of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA
5
Department of Radiation Oncology, University of Washington, Seattle, WA 98195, USA
6
Department of Pharmaceutics, University of Washington, Seattle, WA 98195, USA
7
Pharmacy Informatics, University of Washington, Seattle, WA 98195, USA
8
Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84112, USA
9
Department of Biomedical Informatics, Moffitt Cancer Center, Tampa, FL 33612, USA
10
Department of Pharmacy, University of Washington, Seattle, WA 98195, USA
11
Department of Health Services, University of Washington, Seattle, WA 98195, USA
*
Author to whom correspondence should be addressed.
J. Pers. Med. 2012, 2(4), 241-256; https://doi.org/10.3390/jpm2040241
Received: 5 September 2012 / Revised: 13 November 2012 / Accepted: 15 November 2012 / Published: 20 November 2012
(This article belongs to the Special Issue Untold Stories about Personalized Medicine: If You Thought Personalized Medicine Is for Others to Worry about, Think Again)
Findings from pharmacogenomics (PGx) studies have the potential to be applied to individualize drug therapy to improve efficacy and reduce adverse drug events. Researchers have identified factors influencing uptake of genomics in medicine, but little is known about the specific technical barriers to incorporating PGx into existing clinical frameworks. We present the design and development of a prototype PGx clinical decision support (CDS) system that builds on existing clinical infrastructure and incorporates semi-active and active CDS. Informing this work, we updated previous evaluations of PGx knowledge characteristics, and of how the CDS capabilities of three local clinical systems align with data and functional requirements for PGx CDS. We summarize characteristics of PGx knowledge and technical needs for implementing PGx CDS within existing clinical frameworks. PGx decision support rules derived from FDA drug labels primarily involve drug metabolizing genes, vary in maturity, and the majority support the post-analytic phase of genetic testing. Computerized provider order entry capabilities are key functional requirements for PGx CDS and were best supported by one of the three systems we evaluated. We identified two technical needs when building on this system, the need for (1) new or existing standards for data exchange to connect clinical data to PGx knowledge, and (2) a method for implementing semi-active CDS. Our analyses enhance our understanding of principles for designing and implementing CDS for drug therapy individualization and our current understanding of PGx characteristics in a clinical context. Characteristics of PGx knowledge and capabilities of current clinical systems can help govern decisions about CDS implementation, and can help guide decisions made by groups that develop and maintain knowledge resources such that delivery of content for clinical care is supported.
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Keywords:
electronic health records; clinical decision support systems; pharmacogenomics; personalized medicine; computerized provider order entry; knowledge representation
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MDPI and ACS Style
Overby, C.L.; Tarczy-Hornoch, P.; Kalet, I.J.; Thummel, K.E.; Smith, J.W.; Fiol, G.D.; Fenstermacher, D.; Devine, E.B. Developing a Prototype System for Integrating Pharmacogenomics Findings into Clinical Practice. J. Pers. Med. 2012, 2, 241-256.
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