In my last semester in college (early 2012), I took an entrepreneurship class in which I drafted a platform for aggregating patient data, and connecting patients and hospitals for better outcomes.
Following Apple’s further detailing of HealthKit - and notably their collaboration with Stanford, Duke, and Mayo Clinic - I couldn’t help but be remembered of a project I did a few years ago. So I’m going to talk about that thing, because it’s still relevant a few years later.
Notably similar is the focus on chronic conditions, and especially diabetes. Diabetes affects millions of people, and already has several (albeit, often awful) health tracking tools available, which people are more likely to use than the consumer-focused metrics more widely available.
As part of an entrepreneurship class, with an internship under Eric Topol fresh on my mind, I proposed a platform which would aggregate health tracking information, and provide access to patients, and their doctors if they opted in.
Initially, the idea was to develop a proprietary cloud platform, which would hook into several EHRs, and connect patients and doctors. This model, while easy to monetize and run our own data analysis, wasn’t really feasible - nobody is willing to just give away their data.
We toyed around with the idea of creating our own wearables, since there were only a few major competitors in the market, but decided that wasn’t a game we wanted to - or needed to - play. The platform’s purpose was to tie data together, not collect it.
I also didn’t like the idea of creating a new wearable which measured the same (meaningless) data. The technology didn’t exist then to create which would measure more useful things, and cheaply. Arguably, it still doesn’t, but the Tricorder XPrize is seeking to change that.
We also had no interest in pioneering privacy concerns of hosting medical information in the cloud. Particularly because only a large company could absorb a privacy hit, like Apple last week, and because attacks on hospitals have skyrocketed.
The model we settled on was a base platform which received disparate sets of patient information, and was hosted at, and purchased by, a hospital. The outcomes of patients would improve, which an Obamacare provision makes all the more important, payments to hospitals and doctors shift toward positive outcomes, rather than number of tests/treatments.
The local installation allowed easy tying together of our platform and their existing EHR. Because our platform would integrate with their EHR, we could display all of it’s information within our own platform, allowing a consistent interface across hospitals and EHRs.
It would also make more information accessible to patients, as well as doctors. 90% of patients trust their doctor with their genetic information, but 90% of doctors don’t feel comfortable conferring treatment and advice based on genetic information.
It would enable the hospital to take advantage of any data processing done by our platform, and make it easy to share those algorithms. It also would allow hospitals to easily provide patients access to their information.
Our platform had the advantage of allowing the collection of any type of data, easily adding new types of data as they are collected.
The platform would revolutionize platforms like PatientsLikeMe, which are incredibly beneficial to patients, once they have found groups relevant to them. By driving connections and discovery with data, and finding potential treatments based on what was successful for similar patients, care would be personalized and revolutionized.
Unfortunately, such a platform was largely possible only because we were not focused on driving profit, but solving a problem. Perhaps our biggest differentiator, it ultimately may render the solution infeasible - you can’t solve problems without people working on them. It relied on funding from a few magnanimous contributors.
Initial proposals are attached if they’re at all interesting to you…