It’s hard to open any industry magazine or conference program without seeing references to big data and personalized medicine. These hot topics have at least one thing in common: genetics. The ability to decode our unique genomes leads to copious amounts of data that can in turn be used to provide personalized medicine, such as identifying drugs that are most likely to be effective for different people and explain why other drugs are not.
It’s been 10 years since the Human Genome Project was declared completed. Co-incidentally, it’s been about 10 years since I first sat in on the HL7 Genomics Special Interest Group (SIG), which at the time was gearing up for the anticipated demand for Health Information Systems to exchange genetic data in structured, codified manner. The Genomics SIG has accomplished a lot since then and is starting to see some real world applications of its work. In turn these applications are leading to interesting questions about new services, models of care, and the handling of consent directives to share this data.
HL7 Standards for Genetic Data
The Genomics SIG worked with other groups to develop the HL7 Clinical Genomics Pedigree Model.1 Your pedigree is essentially the record of the ancestors from which your genome is derived, and is often used in human genetics to analyze inheritance of certain traits, or in this case familial diseases (think Mendelian genetics for those of you who can recall high school biology).
Now an approved ANSI standard, the HL7 Pedigree Model is used for transmitting family health histories between systems. This includes describing a patient’s full family health history with diseases and conditions, and the option to link them with genetic and risk analysis data. All of this data can be used to support increasingly sophisticated risk analysis and decision support algorithms. HL7 has also produced a Clinical Document Architecture (CDA) Implementation Guide for the Reporting of Genetic Test Results, which can be used for the exchange of gene expression, genetic variation, and cytogenetic data for chromosomal based tests.
Simple Genetics: Your Family Health History
Family health history is one of the best and least expensive ‘genetic tests’ currently available for clinical use. Simply knowing your relationship to family members with specific health problems and the associated “age of onset” can predict the likelihood of you encountering similar health problems. The HL7 Pedigree Model provides us with a consistent way of sharing this data to support improved risk analysis and selection of preventative actions to take.
Imagine a female patient with a family history of breast cancer who decides to talk to her doctor about it. The doctor questions her about her family members’ history of cancer, and it turns out she also has family members who have had ovarian cancer. The doctor records the family health history information in an EMR, which sends the data using the HL7 Pedigree Model to a cloud-based decision support service that runs the BRCAPRO algorithm3 and returns a result stating that there is a 25% risk of having a deleterious (harmful) BRCA1 or BRCA2 mutation. At which point the doctor refers the patient to a high risk genetic clinic, and sends the family health history and risk analysis data to the specialist using the HL7 Pedigree Model.
There are many ways this story could branch out. Perhaps the patient receives counseling at the clinic on the pros and cons of genetic screening tests and opts to take a test such as BRCAnalysis. The test could come back positive and the exact mutation in the BRCA 1 gene could be added to her data in the HL7 Pedigree Model. The patient would then receive counseling on options for lowering her risk of developing breast cancer, ranging from lifestyle changes to taking risk-lowering drugs. Alternatively, perhaps she opts not to take the test, but informs her aunts on her father’s side that they are potentially at high risk of developing breast cancer and should speak with their doctors.
The HL7 Pedigree Model is used by the US Surgeon General’s online tool called My Family Health Portrait4 to save and import data from other applications such as Microsoft Health Vault. Intermountain Health is using the HL7 Pedigree Model to send patient’s genetic data to cloud based risk analysis services that are kept up to date with the latest research and best practices, and to share the data with its genetic testing labs. Given the implications to support personalized medicine, it is not surprising that the Partner’s Healthcare Centre for Personalized Genetic Medicine in Boston is also a reported implementer.
Emerging Technology Raises Interesting Questions
The value of my family health history data grows over time, particularly as I add more specific data about the precise health problems, age of onset, and associated genetic data for myself and my ancestors. But who benefits the most from that data? The easy answer is my children, and eventually my grandchildren, and so on. They benefit even more if my wife’s family health history data is shared with them. Which leads to an interesting consent policy question; how can we construct consent directives so that my wife and I can share the relevant portions of our family health history data with an unforeseeable amount of future generations and their respective providers?
Knowing my ancestors family health history is definitely useful, but it’s not the sort of information I need to be accessing on a daily basis. Pedigree data will ideally be stored in a centralized repository where I, and the people I select, can access it when needed. Provincial EHR repositories such as the Shared Health Record or Clinical Document Repository would be an ideal home for this data. If this data is stored in a provincial EHR repository how can the future generations of my off spring access it if they move to another province?
There’s also the question of what’s relevant for sharing. Genetic tests often identify “variants of unknown significance”, which are not likely to be deemed relevant for sharing today, but could be significant in the future as new knowledge is gained. Will the data that is deemed irrelevant today be stored for future generations? How can I consent to sharing data that is irrelevant today but potentially relevant in the future?
What other ways might this standard support new models of care? One thought is that it could be used to facilitate the sharing of my individual genetic data with a drug company overseeing a clinical trial of personalized medicine that I’m enrolled in. The drug company could in turn use the standard to send anonymized genetic data and other clinical information to Health Canada or the FDA in the US to assist with approvals.
What about new business models? Is it possible that a prevalence of accurate pedigree data will spur new businesses, such as companies specializing in HIAL or cloud-based risk analysis and decision support services?
So where do we go from here?
Anyone interested in capturing their family health history today so that it can be shared in the future should be looking at personal health record applications and tools like My Family Health Portrait that can import and export data using the HL7 Pedigree Model. Similarly, stakeholders of Lab Information Systems that exchange genetic test data with clinicians or other agencies for secondary uses should look at the CDA Implementation Guide for Reporting of Genetic Test Results. Finally, anyone looking to capture and exchange family health history data, perhaps as part of a referral or a patient health profile, should be aware of this standard and how it is incorporated into other HL7 v3 CDA implementation guides.
2 Grant Wood, HL7 Genetic Testing Webinar. August 3, 2011.