Digital health approaches powered by advances in technology and consumer behavior is in the early phases of revolutionizing the way we conduct clinical research.

In a recent SCORR Marketing report, 50 percent of industry experts surveyed say they utilize mHealth technology in their clinical trials and protocols, and of those, 60 percent consider mHealth very or extremely important to their research. Although the majority of respondents also agreed that the industry’s use of mHealth technology is still in its infancy, recent trends suggest it is maturing quickly.

At the 2016 DIA annual meeting I will be joining a panel of experts to discuss digital health trends and how the industry can use these tools to run trials more efficiently, while potentially improving the quality of the data they collect. My speaking session will focus specifically on “4 Strategies for Executing Digital Health Approaches in Your Clinical Research Studies.”

Digital Health Engagement

Using the term “digital health” can often feel like saying “smartphone” in describing something that has large implications as well as differing definitions in our industry. Although the definition of digital health includes many technologies and solutions, Quintiles’ Digital Health Accelerator has been specifically focused on mHealth apps/integrations, wearables devices (consumer and clinical-use), IoT, virtual research studies and even virtual reality.

From a research perspective, these tools have initially been used to improve patient recruiting – and early results show the impact can be both immediate and hopeful. One of the most popular examples is with Apple ResearchKit, an open source platform for developing medical research apps that was launched in March 2015. Within 24 hours of its launch, the MyHeart Counts app reportedly recruited 11,000 volunteers for a cardiovascular trial run by Stanford Medicine, and by June it had more than 40,000 participants. The ResearchKit platform has seen similar success with apps recruiting patients to studies for autism, epilepsy, skin cancer and others. These and other initial studies conducted with ResearchKit have afforded us lessons learned for adaptations into future versions of these studies.  

It is also important to note that recruiting is only the first piece of the value proposition for mHealth in clinical research. These solutions offer tremendous advantages in providing an engaging experience that provides patients with real value via technology tools and gathers data needed by researchers.  

By gathering these kinds of data remotely via apps and other devices, clinical researchers can dramatically increase the quantity of data they collect while reducing the time and effort spent gathering it. This may allow them to shorten the duration of the trial, reduce the administrative work by the investigators, speed decision-making, and, most importantly, provide patients with a valuable and engaging experience via the research study.

Moving from Pilot to Platform

Execution of digital health approaches and driving them past pilots and into ROI-based platforms that drive internal adoption is the next frontier for our industry. As learned by delivering these approaches in our Digital Health Accelerator model, these four strategies are key to moving these innovations forward with the best probability of success;

  1. Influencing the KEY Stakeholders
  2. Developing the SCALED Business Case
  3. Integrating the OMNI-CHANNEL User Experience
  4. Implementing an INTERATIVE Design Process

Quality and Quantity

In other studies, mHealth apps with wearable integrations are helping to improve the quality of data collected in trials. For example in studies that require data about sleep patterns, patients can struggle to determine how often they wake during the night via self-reported surveys. Relying on biosensors that automatically track and transmit sleep pattern data, researchers can gather more accurate data without having to conduct on-site sleep studies. The improved quality of this endpoint driven data gives researchers new insight about the disease experience, which can help them make more informed decisions and deliver a more evidence-based value proposition for treatments.

The use of mobile health technology in clinical research has only just begun, but these early examples demonstrate how valuable these devices can be in generating faster, better and more insightful data. Regulatory bodies are also getting on board. In 2014, the European Medicines Agency’s (EMA) Innovation Task Force (ITF), widened its scope to assess the regulatory implications of mHealth in clinical trials. In October 2015, the US Food and Drug Administration published a notice seeking input on how mHealth technology might be used to improve clinical trials.

As these devices get more sophisticated, and the industry gets more comfortable employing them in clinical research the impact could be transformative. Gathering more, quality data in between the scheduled study visits via digital health approaches is a key approach to improving the efficiencies of any clinical trial.