04/04/23

You’re Not Selling Your Soul To Pharma

on digital health being a stepping stone for data collection and distribution

This piece is written in collaboration with Shraddha Hakani, a budding leader in digital health innovation.

Unification vs. Precision 

Digital health as a concept has been maturing for about two decades now. It can include everything from wearable devices to telemedicine. In the quest for making our lives easier, and workflows more uniform, it sometimes ends up adding more complexity, especially for patients and users who now have to fill more forms, download more apps, and press more buttons. While digital health apps often try to make personalized recommendations, the experience of accessing that care is still the exact same for every user. 

Pharma on the other hand with centuries of history surrounding one-size-fits-all care, is finally realizing and addressing the need for personalized medicine. Millions of dollars are poured every year into identifying nuances that help scientists understand how one individual is different from the other – and connecting them to the right treatment for them. 

From a birds-eye view it looks exactly like what we discussed above – digital health as a unifying force, and pharma as a personalizing force. However, if we take a deeper look, we can see that the data that pharma is using to personalize is actually being powered by digital health. 

Digital health is powering precision medicine

Because all patients and providers’ experience on a day-to-day basis is encountering digital health’s complexity, they tend to run away from it, causing a deceleration in adoption. It’s important that they realize that this unification of experience leads to structured data that can then benefit them via innovation and personalized medicine later on.

The adoption of unified digital health platforms now will help democratize personalized medicine in the future. 

The potential of digital health data

Data bridges unified and personalized 

The only way these new personalized discoveries can continue is by adopting digital and letting these unifying platforms collect data that research institutions can use. Data linking existing SaaS solutions to personalized medicine holds the key to breaking the barrier and viewing patients as people instead of standard records.

We understand that accommodating every single want and need in one platform is one of the main reasons why digital health tools have low adoption – they become extremely tedious, complex, and expensive to use – contrary to their initial intention. Digital health companies tried their best to have faster adoption by making the “new systems” as similar to the old (analog) ones as possible, but in doing that, they also inherited the flaws of the old ones. 

In order to drive adoption, we may want to adopt the Apple model of operation – minimal deviance – to fuel personalization with highest quality structured data. That’s the goal. Good data that is structured, has integrity, and is accessible. 

Digital health is not the solution, it is a vessel for feeding data into precision medicine. We must continue to use it. 

This piece is 4/50 from my 50 days of writing series. Subscribe to hear about new posts.