I recently did a talk about the explosion of companies who are trying to motivate behavior change through digital health. Not surprisingly, many of the companies that I mentioned are being built on the back of increasingly complex and interesting data sets. As I was preparing the talk, it occurred to me that it was going to be difficult to elegantly summarize the ecosystem.
So I came up with something that I thought provided a pretty simple overview and decided to call it the ‘Health Data Spectrum’.
As you can see, the data types are arranged in a linear fashion with ‘Behavioral’ Data (steps, activity…), followed by ‘Physiological’ Data (heart rate, blood pressure…), ‘Systems Biology’ Data (glycomics, lipidomics…) and then ‘Omics’ Data (DNA, RNA…).
Although a linear categorization is not technically correct (it is actually technically very incorrect), I found that when explaining it to people it seemed to serve my goal of providing a quick and relatively easy to understand overview.
Behavioral data is what behaviors are you currently exhibiting (such as walking vs running); Physiological is how your body is responding in realtime to those stimulus to regulate various feedback loops; Systems Biology represents your bodies internal mechanisms for signaling change, transporting energy, adapting to threats etc; and Omics represents the code that is expressed to form us, and the instructions for how to do it.
As you can probably tell, this concept is a work in progress and I would love feedback so that I can refine and adapt. If you have any thoughts or criticism, please let me know!
For now, the real question is, is this data simply interesting, or is it also going to positively change behaviors in a persistent way? My hypothesis is, with proper design, it can – my thoughts on this topic coming soon!