Recently, there has been an explosion in personalized data collection, which includes genetic and biometric data and its analysis for use in research and healthcare management. From genetic testing companies like 23andme to makers of wearable gadgets, pro-active wellness care has literally taken over the modern health care landscape. This launches the age of holistic, truly personalized healthcare.
How data sharing enables “Scientific wellness”
To encompass all the aspects of this brave new world, the term “Scientific wellness” has been coined. With the information over load contributed by digital health devices, systems biology, AI, big data and everyday informatics from sleep schedules to cancer susceptibility, the health care paradigm will shift form the current norm of life style change to using the information to predict and manage health for each person.
What this means for health care’s future
This has huge implications for both the health care industry and the patient. Leroy Hood, the grand old man of Seattle Bio- tech innovation predicts that “Over the next 10-15 years there will be a scientific wellness industry in contrast to the disease industry and the market cap will far exceed that of the disease industry,” and that “The contrast between 20th and 21st Century medicine is striking, 21st is proactive, focused on the individual, disease and it employs personalized data clouds to explore the complexities of human beings.” We can all agree that this is the ideal health care strategy.
Can we enable voluntary data sharing?
But for this brave new world to really dawn and be meaningful, a major hurdle needs to be crossed- that of voluntary data sharing. In the past week, I came across several articles expressing apprehension about how genetic testing companies may share data on gene biomarkers with other entities that can then use them in developing tests and drugs.
“Scientific wellness” depends on data sharing?
Unless voluntary data sharing becomes routine and safe, “Scientific Wellness” will remain elusive. The FDA sets forth clear and precise guidelines for good clinical practices that include obtaining informed consent, coding, sharing and storing data for use by companies and research institutes. They are both concerned about the privacy of the sharing process, how their identities will be protected and more importantly, whether this may lead to conclusions that will restrict their access to regular health care. The real challenge is for data generators to convince their clients that sharing their data with all the privacy protections set forth by the FDA is safe and contributes to their good.
How to enable voluntary data sharing
As an example, setting forth a transparent consent and data sharing process through simple questions that may guide the client in an interactive manner such as, “Who will see my data?” and “Will they know me?” or “When my DNA sequence for a biomarker is shared, what else is shared about me?”, as well as “If something critical is established about me, will my health insurance know it and use it to modify my health plan?” will be effective. A similar approach to explain the consent process will also help. I rather liked 23andme’s research consent process. Though one aspect that came up in discussions about sharing data, “Will anyone profit from my data and how will I be compensated if that occurs?” is not clearly spelt out.
Establishing a small group of professionals trained to guide this process and communicate with the client must be a priority for any entity that has data generation as its goal. Above all, the fact that privacy of the client and ethical research using the data is of utmost concern must be conveyed in unmistakable terms.