14. Rulebook example: division of income (from pharma)
10 % for the ecosystem infrastructure
5 % for top rated apps
5 % for most used apps
60 % for apps that stored the data that was monetized
20 % for apps that facilitated the consent process
Life with type 1 diabetes: you need to constantly monitor different variables, and you need to learn from the data.
With modern wellness apps and gadgets, gathering data is easy. However, learning from it remains a challenge.
This is where Sensotrend helps. We integrate with dozens of medical devices and wellness trackers, visualize the data in a way that helps in treatment of type 1 diabetes, and facilitate sharing it with healthcare professionals and peers.
People living with chronic conditions have an inherent motivation to share their data, in the hope of better treatments in the future. But they have a problem too, they cannot just send their data over to a pharma company on a USB stick, the channel is not there.
Pharma companies are in need of that data. They are transitioning into value based care, where they need to demonstrate the efficacy of their medicines in real life. But they don’t even know whom to ask that data from. And since GDPR, their access to the relevant data is more limited than ever.
eHealth apps dedicated to help in treatment of specific chronic conditions are in an ideal position to help here.
They have a trusted relationship and an ongoing dialogue with the citizen, and are already transferring the data from place to place.
They can facilitate the consent management process and the transfer of data - on demand.
However, most of the companies are small, and focused on providing excellent service to the citizens. Monetizing the data is not their core business.
To make this business model based on fair data ecosystem and on ethical sharing of health and wellness data a reality, we’ll set up a new platform company. It’s open for all eHealth apps, as getting more data into the ecosystem increases the total value of the offering.
In this model, the citizens provide their data to apps to get personalized treatment, but also happily consent to the data being used in medical research.
The apps provide the data to the platform company, with the consent from their users, to get revenue when the data is being used.
The platform company provides the data to pharma and healthcare providers, who then pay for it, and the platform company divides the income back to the apps.
The citizens get free, high quality apps, more personalized treatment, and also the hope for a better future!
We have already 8 data producing companies committed to working with the ecosystem, and one company working as the platform company.
We have identified other companies that are likely candidates for providing required infrastructure for the platform company, and are in active discussions with two pharma companies.
The challenge here is that the pharma companies are big and bureaucratic, and we don’t expect to close those deals in an immediate future.
So we start with a simpler case.
Here the party paying for the data is a healthcare organization. We are in discussions with several of them, and just might be able to get the ball rolling in early 2020.
Direct quote from a healthcare provider: “We want to have a coupon model where our users are free to select among several apps that best suit their individual goals and life situations”. The organization is very willing to make diabetes the first area where this model is used.
We have four different diabetes apps, each with their own target user group. And all are willing to work with a joint offering towards healthcare providers. We also have experience in integrating with the system. (In fact, we helped to create the specifications for the integration).
We do our best to operate according to the MyData principles. We don’t store any health or wellness data.
The platform company will implement critical trust-building components for the ecosystem.
Although we start with the simpler case, we still get to experiment how people react when asked how they would like to share their data for different purposes. We also get to collect the initial shared data sets that will be interesting for pharma.
The other critical component for the ecosystem is the rulebook.
We will fine tune the rulebook that we have already started drafting - specifying how income is distributed among different parties, for instance.