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A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine.
Full Abstract
BACKGROUND: In recent years, the completion of the Human Genome Project and other rapid advances in genomics have led to increasing anticipation of an era of genomic and personalized medicine, in which an individual's health is optimized through the use of all available patient data, including data on the individual's genome and its downstream products. Genomic and personalized medicine could transform healthcare systems and catalyze significant reductions in morbidity, mortality, and overall healthcare costs. DISCUSSION: Critical to the achievement of more efficient and effective healthcare enabled by genomics is the establishment of a robust, nationwide clinical decision support infrastructure that assists clinicians in their use of genomic assays to guide disease prevention, diagnosis, and therapy. Requisite components of this infrastructure include the standardized representation of genomic and non-genomic patient data across health information systems; centrally managed repositories of computer-processable medical knowledge; and standardized approaches for applying these knowledge resources against patient data to generate and deliver patient-specific care recommendations. Here, we provide recommendations for establishing a national decision support infrastructure for genomic and personalized medicine that fulfills these needs, leverages existing resources, and is aligned with the Roadmap for National Action on Clinical Decision Support commissioned by the U.S. Office of the National Coordinator for Health Information Technology. Critical to the establishment of this infrastructure will be strong leadership and substantial funding from the federal government. SUMMARY: A national clinical decision support infrastructure will be required for reaping the full benefits of genomic and personalized medicine. Essential components of this infrastructure include standards for data representation; centrally managed knowledge repositories; and standardized approaches for leveraging these knowledge repositories to generate patient-specific care recommendations at the point of care.
Author information
Author/s: Kawamoto, Kensaku (K); Lobach, David F (DF); Willard, Huntington F (HF); Ginsburg, Geoffrey S (GS);
Affiliation: Division of Clinical Informatics, Department of Community and Family Medicine, Box 104007, Duke University Medical Center, Durham, North Carolina 27710, USA. kawam001(-atsign-)mc.duke.edu
Grants: K01HG004645 (Agency:NHGRI NIH HHS)
Journal and publication information
Publication Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
Journal: BMC medical informatics and decision making (BMC Med Inform Decis Mak), published in England. (Language: eng)
Reference: 2009-; vol 9 (issue ) : pp 17
Dates: Created 2009/04/08; Completed 2009/05/13;
PMID: 19309514, status: MEDLINE (last retrieval date: 5/13/2009, IMS Date: 13 May 2009 00:00:00)
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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