Future of Patient Data

The world’s healthcare systems are seeing significant changes. A more information-rich, digital approach to healthcare over the next decade will lead to more patient focus and improved effectiveness. The think tank Future Agenda (www.futureagenda.org) run a series of 12 events around the world to brainstorm these changes and implications for all healthcare players. Multiple experts from across a wide range of industries, providers, researchers, governments, and start-ups discussed these topics between September 2017 and January 2018. I had the privilege to participate in the discussion in Frankfurt.

After all events, 24 themes have emerged ranging from data ownership to AI, digital transformation, efficiency, and few country-specific topics. The themes reflect the broad list of 300 meeting participants across the world. Two topics are especially relevant for ALL players in the healthcare system, i.e., in the Healthcare Trifecta. And they trigger or are caused by few other ones.

3. New Models – Key areas of healthcare will be reconfigured as new models come from unexpected places. Led by Amazon, big tech will disrupt and reinvent some core elements and unify fragmented systems.

There seem to be two drivers of new business models in healthcare. One is supply-driven and one demand-driven. With the growing supply of computing power, new patient data (theme #1), and analytics/AI capabilities (theme #19), there is a race by many big tech firms to develop new business models around data and analytics. Google's Verily is working for example on a 10,000-person study that explores why people who are generally healthy become sick and it's collaborating with Novartis on a smart contact lens that measures blood sugar levels. Apple wants to turn your iPhone into the one-stop shop for all your health data and allow you to share it with any party you choose. IBM Watson wants to remake healthcare with AI and so does Alibaba. Baidu is developing a bot-based medical assistant trained on medical textbooks. And there is of course Amazon, which is hiring people to break into the multibillion-dollar pharmacy market. Its health tech lab 1492 is working on medical records and virtual doc visits. Alexa for doctors, anybody?

The demand side may be less obvious since it’s a slower and more gradual change, and it’s impacting different market participants differently. The increasing demand for preventative healthcare from insurers, governments, and the general population is disrupting existing business models. The money flow between patients, providers, and payers in the existing healthcare trifecta is built around sick care. This will change, assuming preventative healthcare will lead to healthier population. There will be less income for pharma companies and physicians while insurers will be able to reduce their expenses. This profit shift will require reevaluating how pharma and physicians are compensated for their contribution to a healthy population.

11. Personal Data Stores – New platforms help patients and providers to manage and curate their data across multiple partners. Universally accepted credentials help to drive greater personalization of health services.

“Stores” may not be the best word to describe where individuals not only manage their personal information but also extract the best value from it, whether it’s social, economic, or health related. The concept is that individuals will increasingly be able to oversee and maintain their own health records and give permissions to others to use and share key information. This will lead to data exchanges, most likely with assigned monetary value, through healthcare data marketplaces (theme #4).

Data exchanges have been the cornerstone of the online economy since the first pay-per-click web search service. Individuals offered their search key words to the search provider and received as an exchange “free” search results. The search provider monetized these key words by selling advertising to third parties. This model has continued with social networks, online shopping, and “free” traffic updates. These data exchanges have been implicit though. Healthcare data exchanges call for explicit definition of how data is managed, requiring many fundamental problems to be overcome: privacy concerns and trust in technology (themes #13 & #14), security of centralized and decentralized data (theme #15), and unwillingness of some organizations to share proprietary data (theme #8). The biggest challenge is probably to figure out who will ultimately own and control patient data (theme #10).

Here is the list of all 24 themes:

1. Changing Definition of Patient Data
2. Improving Efficiency
3. New Models
4. Data Marketplaces
5. Re-engineering from Within
6. India Setting Standards
7. EHR Integration
8. Combining Data Sets
9. Managing Data Quality
10. Increasing Control
11. Personal Data Stores
12. Data Sovereignty
13. Building Trust
14. Managing Distrust
15. Enhanced Security
16. Personalization
17. Individualized Medicine
18. The Initial Impact of AI
19. AI and Unstructured Patient Data
20. AI and Mental Health
21. Open Source vs. Private AI
22. Access Inequality
23. Agreed Standards
24. Digital Skills