Grant Number:	1RC2CA150911-01 Interpret this number
Primary Investigator:	Knaus, William
Organization:	University Of Virginia
Project Title:	Building a Genome Enabled Electronic Medical Record
Fiscal Year:	2009

DESCRIPTION (provided by applicant): Conducting timely, high quality, comparative effectiveness research (CER) and creating and delivering recommendations for genomic tests in cancer care and prevention are major technical and intellectual challenges. Yet with the increased use of Electronic Medical Records stimulated by the American Recovery and Reinvestment Act, they can be addressed through improved use of information technologies. This project will create a new Genome-Enabled Electronic Medical Record (GenE EMR). This record will build a foundation for the efficient collection and sharing of relevant family history and personal risk factor data, the input of information from new genetic and molecular test results, and facilitating their connection to other clinical data, treatment records, and patient outcomes. This GenE EMR will also be able to display recommendations from reviews conducted by multidisciplinary teams that address the analytic and clinical validity, clinical utility, and ethical, legal, and societal implications for Genomic and Personalized Medicine tools in cancer care and prevention. The final product will enable real-time clinical decision support for clinicians and their patients in user-friendly formats. This entire application will be embedded initially within the most widely used electronic medical record system in the United States (EpicareR) (current installations covering 22% of the U.S. population - 70 million persons - and 150,000 providers) and developed in a manner that insures interoperability with other commercial and open source Electronic Medical Records nationwide. The GenE EMR will also accept family history information collected using the Surgeon General's My Family Health History Tool. Concurrent with these efforts, two proof of principle CER studies will be conducted. The first CER will evaluate the clinical utility of family history data collection and individualized recommendations on risk reduction behaviors for cancer prevention. The second will evaluate the impact of genetic counseling for patients at high risk for hereditary cancer. Furthermore, by collaborating with other NCI grantees and with the Evaluation of Genomic Applications in Practice and Prevention (EGAPP) network, the NCI's CaBigR network, and the CDC's FamilyHealthwareT project, these efforts will enable the creation of a national road map for the more efficient and timely evaluation of GPM tools. This project also provides the basis for creating new jobs and a self- sustaining foundation for these efforts through licensing fees paid for by incorporating the GenE EMR into Electronic Medical Records nationwide. The goals of this entire project are achievable in a 2-year timeframe because they will be done with the full cooperation and support of Epic, and will be incorporated into the design of the 2011 release of the EpiCareR suite of Electronic Medical Records. PUBLIC HEALTH RELEVANCE: This project embeds an expanded release of Health Heritage(c); a family history based genomic risk assessment and clinical decision support tool, into the largest provider of Electronic Medical and Personal Health Records in the United States (Epic). This will create a Genome Enabled Electronic Medical Record (GenE EMR) that will help clinicians and their patients better understand the meaning and personal implications of family history and other genomic data. GenE EMR will assist clinicians and patients in making decisions about which are the optimal preventative practices for an individual to follow to reduce the risk of inherited cancer. It will also help in making decisions about genomic testing and, should cancer occur, what are the best treatments. GenE EMR, while embedded initially into Epic, will be designed so it can be incorporated into all nationally certified electronic medical records.




Building the evidence base for decision making in cancer genomic medicine using comparative effectiveness research.
Authors: Goddard K.A. , Knaus W.A. , Whitlock E. , Lyman G.H. , Feigelson H.S. , Schully S.D. , Ramsey S. , Tunis S. , Freedman A.N. , Khoury M.J. , et al. .
Source: Genetics in medicine : official journal of the American College of Medical Genetics, 2012 Jul; 14(7), p. 633-42.
PMID: 22516979
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