Data monetization in healthcare: Sharing data for the sake of science

Atul Butte, MD, PhD

Chief Data Scientist, University of California Health System (UC Health)

Jim Stolze

Tech Entrepeneur and founder of Aigency

Andreas Schneider

Head of Global Digital Marketing for Roche Diagnostic Solutions

Data monetization in healthcare: Sharing data for the sake of science

23 February 2022 | 4min

The exponential growth in healthcare data

Data is not the new oil, but the new soil

David McCandless

Gartner defines data monetization as “the process of using data to obtain quantifiable economic benefit.”1 

As vast amounts of healthcare data continue to pour into electronic health records (EHR), leaders need to understand how we can leverage this information in a regulated and responsible manner to improve patient care and business strategies.

How can stakeholders across the healthcare spectrum – from patients to clinicians to pharma – understand the value and benefits of using their data? How is data being handled by our health systems in a secure, private, and ethical manner? How are AI and computer algorithms helping solve the issues around data access and at the same time, improving clinical outcomes?

To address these questions, we brought together two experts to explore what our healthcare data is worth — Atul Butte, Chief Data Scientist across University of California Health System, and Jim Stolze, Tech Entrepreneur and founder of Aigency.

Watch the full, free recording of the event now!

Reducing healthcare costs and improving outcomes

To understand how data can drive healthcare savings, or monetization, Atul began the session by discussing the vast amounts of data within the single central database of records of the University of California Health System, composed of 8 million patients treated over the past decade. These enormous, yet expensive data assets are captured within patient electronic health records (EHR). 

Atul points to the value of using this data to create products and services for patients. More specifically, Atul believes that these databases, which contain information from millions of patient procedures and drug prescription orders and beyond, can help provide clues on what we’re doing right in medicine, what might be missing, and what areas are costing too much money, 

Atul says that as we’ve sunk billions of dollars into deploying EHR systems to collect all this data, it would be a “tragedy” if we didn’t use it to improve the practice of medicine. In this respect, we can figure out ways of saving on unnecessary costly items or services, and therefore, generate a better outcome for patients while also potentially yielding more revenue across the entire healthcare system. For example, this can come in the form of using the data for changing to better choices for prescription medicines or improving side-effect management for type 2 diabetics.

While many interesting topics such as real-world evidence data, AI training, and integrating genomics data into EHR were discussed, Atul wraps his session by emphasizing that using the data of the health record system can be utilized not to just save money, but provide more clinical options to patients.

Watch the full, free recording of the event now

Security, privacy and ethics in healthcare data

Following Atul’s lively and informative session, Jim shared how to safely share your data for the sake of science, focused on taking a more business and corporate perspective. Jim discusses this on three different levels: security, privacy, and ethics.

In terms of security, the issue that Jim wants to address is that because the data are sensitive, there need to be ways to safely hide personal information due to various risks, such as ransomware attacks on the companies who store your information. 

For privacy, one area which Jim believes can bring something to the table is blockchain technology – a decentralized technology where data is not stored in one place, but distributed across the network. An individual can decide how to provide or revoke data access as needed, similar to a “personal data vault.” These privacy-preserving technologies empower patients with their data, and Jim envisions that it could be as simple as an app on your phone.

Lastly, Jim speaks of ethics with computer modeling, AI, and data algorithms that should be utilized in an unbiased fashion that does not discriminate against specific genders, ethnicities, nationalities, or other features. Jim calls this being “ethical by design” and the need for FACT (fairness, accuracy, confidentiality, and transparency) when it comes to handling, monitoring, and analyzing healthcare data.

The next frontier, Jim explains, is that if healthcare professionals want to become more efficient,  there needs to be governance in place with the responsible management of data, algorithms, and AI.

Watch the full, free recording of the event now!

What questions are top of mind for healthcare leaders surrounding data monetization

The discussion continued during a live Q&A round guided by Andreas Schneider from Roche.  Some questions that Atul and Jim answered include:

  • How would a health system leader know which solutions are real and which are just hype?
  • ​​What is the minimum AI talent a health system is going to need to have in-house?
  • What is your current set of data good enough to do now? And which data do we need more of?
  • Who is the owner of the data and is there informed consent? 
  • Is it fair to share all records in a decentralized way so patients benefit directly from their data? Can patients monetize their data?
  • How can healthcare organizations best show the value of data sharing and how it is giving back to patients?

Watch the free live event recording now and learn more about how to transform data monetization in your healthcare organization.

Atul Butte, MD, PhD is the Priscilla Chan and Mark Zuckerberg Distinguished Professor and inaugural Director of the Bakar Computational Health Sciences Institute (bchsi.ucsf.edu) at the University of California, San Francisco (UCSF). Dr. Butte is also the Chief Data Scientist for the entire University of California Health System and has authored over 200 publications, with research repeatedly featured in the New York Times, Wall Street Journal, and Wired Magazine. Dr. Butte was elected into the National Academy of Medicine in 2015, and in 2013, he was recognized by the Obama Administration as a White House Champion of Change in Open Science for promoting science through publicly available data. Dr. Butte is also a founder of three investor-backed data-driven companies: Personalis (IPO, 2019), providing medical genome sequencing services, Carmenta (acquired by Progenity, 2015), discovering diagnostics for pregnancy complications, and NuMedii, finding new uses for drugs through open molecular data. Dr. Butte trained in Computer Science at Brown University, worked as a software engineer at Apple and Microsoft, received his MD at Brown University, trained in Pediatrics and Pediatric Endocrinology at Children's Hospital Boston, then received his PhD from Harvard Medical School and MIT.

Jim Stolze is a tech-entrepreneur and a prominent figure in the European startup scene. In 2009 he was approached by TED.com to become one of their twelve ambassadors worldwide. Between then and 2016 he was the driving force behind TEDxAmsterdam and many other TEDx events in Europe, the Middle East and even the Caribbean. An alumnus from the prestigious Singularity University (California) Jim Stolze is a thoughtleader and changemaker in the field of exponential technologies. Since 2017 Jim focuses on Artificial Intelligence (AI). With his platform Aigency he connects algorithms from PHD’s and startups to data-sets and challenges from big corporates. This initiatieve was labeled by the media as “the world’s first employment agency for artificial intelligence”.

Andreas Schneider has over 15 years of experience in various leadership roles within the Healthcare Industry after co-founding, managing and selling his own IT consultancy company.

References

  1. Gartner. Gartner glossary available from https://www.gartner.com/en/information-technology/glossary/data-monetization [Accessed February 2022]