Human-Centered Innovation: Using data as a resource for good

Human-Centered Innovation: Using data as a resource for good

This article is part of the Forum Network series on Digitalisation

Karla Childers is Senior Director of Strategic Projects at Johnson & Johnson and lead of the YODA Project.

Living in this era of big data and analytics, it can sometimes feel like information is everywhere but not always easy to access or understand – especially when it comes to healthcare. Storing, mining, merchandising, owning and searching for data are ever-growing topics. The Economist has even suggested that the world’s most valuable resource is no longer oil, but data!

Is data the new oil?
Image: David Parkins for The Economist

So the question for us is: where do we stand? What do we believe about data? What do we do with it? When it comes to our clinical trials, the answer is simple. We believe that sharing clinical trial data advances the science that is the foundation of medicine. Putting people first is what dictates the way we think about data and how we manage that valuable, growing resource in a constructive and responsible way. 

Aligned with the Institute of Medicine (IOM) guidelines, our guiding principles for sharing clinical trial data include:

  • Protecting the privacy of the participants
  • Upholding the commitments made in obtaining consent
  • Approving only scientifically sound proposals that are important from a medical/scientific perspective
  • Distributing data strictly within the terms of a legally binding agreement
  • Requiring all applicants to report the results of their work
  • Being transparent in all decisions

We have a strong belief in, and practice of partnership in our business that tells us no one has a monopoly on good ideas, and the same is true of our view on data; we believe that great ideas can come from anywhere, and we can nurture them by providing access to data.

Image: Johnson & Johnson

This notion is what propelled us to establish a first-of-its-kind process to share clinical trial data through an agreement with the Yale University Open Data Access (YODA) Project. To achieve our enterprise-wide approach to sharing our clinical trial data with researchers, we overcame many obstacles – a journey you can learn more about in an article recently penned by Joanne Waldstreicher, MD. Our collaboration ensures that the YODA Project objectively and independently reviews every request for access to our pharmaceutical or medical devices and consumer products’ clinical trials data.

Our data are developed to answer specific questions, and we use them to make decisions and create our medicines. But that does not mean others cannot leverage those data to answer questions of their own.

We honor the patients that participate in clinical trials by responsibly sharing their data with researchers around the world. Sharing data furthers our understanding of diseases, expands the base of knowledge needed to develop new treatments and generates new insights and more complete evidence to enable better healthcare decisions for patients. Patients volunteer to participate in clinical trials – giving their time and often their bodies – to help advance research. Sharing data continues that advancement.

Photo by rawpixel on Unsplash

We also continue to collaborate with a broad working group of industry, academic, regulatory and patient advocate stakeholders to develop robust, transparent and sustainable solutions for responsible clinical data sharing that can be employed by both industry and academia. 

It’s terrific to see forums including Data for Good Exchange, hosted by Bloomberg today, and OECD Forum 2018 where I was thrilled to participate in the panel “The Centrality of Data” where we discussed common approaches to remove barriers and increase incentives to unlock the full power of data through sharing and analysis. The practices of “data for good” and “data philanthropy” are nascent and need to be nurtured while having the right controls to protect individual privacy and ensure the security of data sets. 

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