Validic Survey Raises Hopes of Merging Big Data Into Clinical Trials

Validic has been integrating medical device data with electronic health records, patient portals, remote patient monitoring platforms, wellness challenges, and other health databases for years. On Monday, they highlighted a particularly crucial and interesting segment of their clientele by releasing a short report based on a survey of clinical researchers. And this report, although it doesn’t go into depth about how pharmaceutical companies and other researchers are using devices, reveals great promise in their use. It also opens up discussions of whether researchers could achieve even more by sharing this data.

The survey broadly shows two trends toward the productive use of device data:

  • Devices can report changes in a subject’s condition more quickly and accurately than conventional subject reports (which involve marking observations down by hand or coming into the researcher’s office). Of course, this practice raises questions about the device’s own accuracy. Researchers will probably splurge for professional or “clinical-grade” devices that are more reliable than consumer health wearables.

  • Devices can keep the subject connected to the research for months or even years after the end of the clinical trial. This connection can turn up long-range side effects or other impacts from the treatment.

Together these advances address two of the most vexing problems of clinical trials: their cost (and length) and their tendency to miss subtle effects. The cost and length of trials form the backbone of the current publicity campaign by pharma companies to justify price hikes that have recently brought them public embarrassment and opprobrium. Regardless of the relationship between the cost of trials and the cost of the resulting drugs, everyone would benefit if trials could demonstrate results more quickly. Meanwhile, longitudinal research with massive amounts of data can reveal the kinds of problems that led to the Vioxx scandal–but also new off-label uses for established medications.

So I’m excited to hear that two-thirds of the respondents are using “digital health technologies” (which covers mobile apps, clinical-grade devices, and wearables) in their trials, and that nearly all respondents plan to do so over the next five years. Big data benefits are not the only ones they envision. Some of the benefits have more to do with communication and convenience–and these are certainly commendable as well. For instance, if a subject can transmit data from her home instead of having to come to the office for a test, the subject will be much more likely to participate and provide accurate data.

Another trend hinted at by the survey was a closer connection between researchers and patient communities. Validic announced the report in a press release that is quite informative in its own right.

So over the next few years we may enter the age that health IT reformers have envisioned for some time: a merger of big data and clinical trials in a way to reap the benefits of both. Now we must ask the researchers to multiply the value of the data by a whole new dimension by sharing it. This can be done in two ways: de-identifying results and uploading them to public or industry-maintained databases, or providing identifying information along with the data to organizations approved by the subject who is identified. Although researchers are legally permitted to share de-identified information without subjects’ consent (depending on the agreements they signed when they began the trials), I would urge patient consent for all releases.

Pharma companies are already under intense pressure for hiding the results of trials–but even the new regulations cover only results, not the data that led to those results. Organizations such as Sage Bionetworks, which I have covered many times, are working closely with pharmaceutical companies and researchers to promote both the software tools and the organizational agreements that foster data sharing. Such efforts allow people in different research facilities and even on different continents to work on different aspects of a target and quickly share results. Even better, someone launching a new project can compare her data to a project run five years before by another company. Researchers will have millions of data points to work with instead of hundreds.

One disappointment in the Validic survey was a minority of respondents saw a return on investment in their use of devices. With responsible data sharing, the next Validic survey may raise this response rate considerably.

About the author

Andy Oram

Andy Oram

Andy Oram writes and edits documents about many aspects of computing, ranging in size from blog postings to full-length books. Topics cover a wide range of computer technologies: data science and machine learning, programming languages, Web performance, Internet of Things, databases, free and open source software, and more. My editorial output at O'Reilly Media included the first books ever published commercially in the United States on Linux, the 2001 title Peer-to-Peer (frequently cited in connection with those technologies), and the 2007 title Beautiful Code. He is a regular correspondent on health IT and health policy for He also contributes to other publications about policy issues related to the Internet and about trends affecting technical innovation and its effects on society. Print publications where his work has appeared include The Economist, Communications of the ACM, Copyright World, the Journal of Information Technology & Politics, Vanguardia Dossier, and Internet Law and Business.