Some physicians advocate measuring less rather than more, because they find themselves uncomfortable with data that doesn’t have obvious significance. The real challenge is in identifying the strength of the association between a piece of data and the outcome of interest. We believe in harnessing as much data as we can, in a cost-effective way, to obtain as complete a picture as possible of your health.
Truly personalized care needs to consider the significant variability found between individuals. This can only be done by integrating larger volumes and more complex sets of data. This complexity can be intimidating for most physicians, but as experienced physician-scientists with strong backgrounds in data science and machine learning, we see this as an opportunity.
In data science, you will come across two complimentary ideas. The first, "garbage in - garbage out", says it is critical that all data being used to make decisions must be of high quality. Second, "a thousand weak predictors makes a good one". This mantra is demonstrated by the near psychic abilities of advertisers to identify who you are or what you want based on web browsing experiences.
We apply both philosophies to our practice. We gather the high-grade medical data where possible and lean on the massive amounts of data that less precise sources such as wearables can bring to the table. Using each set of data responsibly allows us to do much more than with any isolated piece of information.
We recognize that for some people, information without clear significance can just breed anxiety and ultimately be detrimental. This is why, after our personalized intake process, we are careful to really get to know you and your goals before recommending a plan that works best for you.
