Practical considerations to guide development of access controls and decision support for genetic information in electronic medical records
- Equal contributors
1 South Bay Regional Genetics Center, Santa Clara Valley Medical Center, San Jose California, USA
2 Program Evaluation and Resource Center and Center for Health Care Evaluation, Department of Veterans Affairs, Menlo Park California, USA
3 Human Genetics and Genetic Counseling Program, Stanford University, Stanford California, USA
4 Anesthesiology Department, Stanford University and VA Palo Alto Health Care System, Palo Alto California, USA
Citation and License
BMC Health Services Research 2011, 11:294 doi:10.1186/1472-6963-11-294Published: 2 November 2011
Genetic testing is increasingly used as a tool throughout the health care system. In 2011 the number of clinically available genetic tests is approaching 2,000, and wide variation exists between these tests in their sensitivity, specificity, and clinical implications, as well as the potential for discrimination based on the results.
As health care systems increasingly implement electronic medical record systems (EMRs) they must carefully consider how to use information from this wide spectrum of genetic tests, with whom to share information, and how to provide decision support for clinicians to properly interpret the information. Although some characteristics of genetic tests overlap with other medical test results, there are reasons to make genetic test results widely available to health care providers and counterbalancing reasons to restrict access to these test results to honor patient preferences, and avoid distracting or confusing clinicians with irrelevant but complex information. Electronic medical records can facilitate and provide reasonable restrictions on access to genetic test results and deliver education and decision support tools to guide appropriate interpretation and use.
This paper will serve to review some of the key characteristics of genetic tests as they relate to design of access control and decision support of genetic test information in the EMR, emphasizing the clear need for health information technology (HIT) to be part of optimal implementation of genetic medicine, and the importance of understanding key characteristics of genetic tests when designing HIT applications.