The Growing Availability of Wearable Devices: A Perspective on Current Applications in Clinical Trials

May 27, 2016

The rapid consumer adoption of wearable devices for the collection of health data is laying the foundation for the next revolution in clinical trial operations. The integration of wearable health monitors with smartphones offers capabilities to collect continuous, accurate health data in real time. This emerging digital research platform has the potential to increased data accuracy and timeliness, improve operational efficiencies, and achieve greater patient engagement in the clinical trial process.1   

In the burgeoning consumer market, more than 97,000 mHealth apps were available to consumers by 2013.2 Health and wellness devices like the FitBit wristband and the Misfit Wearables clothing tag conveniently track physical activity based on smartphone and GPS technology. Apple is developing a biometric headphone system to monitor vital signs while the wearer listens to music.3

Broad consumer use of such devices is building familiarity and will facilitate the implementation of similar medical grade devices in clinical studies. Anticipating this future, major technology companies are entering the clinical research space. Google recently developed a health-tracking wristband for use in clinical trials capable of measuring pulse, heart rhythm, skin temperature, light exposure, and noise levels.4 The new Apple ResearchKit offers a software platform that allows researchers to create apps to manage data collected via wearable devices and smartphones.5

Medical grade monitoring devices now support patient care in most therapeutic areas including gerontology and chronic disease. Devices are available that monitor respiration, oxygen saturation, ECG, blood pressure, skin and core temperature, and galvanic skin response. Other devices transmit patient measurements directly to caregivers using Bluetooth technology. A number of technologies are available to monitor drug adherence. For example, ingestible monitors are available that collect data on medication ingestion, dose timing and physiologic responses, then transmit measurements to the patient’s smartphone. In our experience, we are seeing more and more biopharma and technology companies partnering to launch mHealth apps that monitor conditions ranging from diabetes to heart attacks.

In clinical trial applications, electronic patient-reported outcome (ePRO) companies are integrating wearable devices to advance data collection by adding objective data points to subjective PROs. For example, one company offers ePRO software for mobile devices with apps on Android, Windows 8, and iOS. Another company offers dedicated mobile devices for use in clinical trials, including site-based devices and “bring-your-own-device” options that allow patients to use their own smartphone apps.

 

mHealth in Clinical Trials: Benefits and challenges

Clinical trial models based on the integration of wearable devices and smartphones are in their infancy, but early applications demonstrate compelling benefits, including:

  • Real-world, continuous measurement of health status as subjects follow their daily routines; opportunities to build richer patient health profiles
  • Accurate measurements to improve patient-reported outcomes (PRO); deliver time-marked data to compare and verify PROs
  • Improvement in subject retention by delivering prompts, encouraging compliance, sharing information; more convenience to encourage research participation
  • Reduced costs by decreasing the need for expensive clinic visits

An increasing number of trials use mobile devices or applications in therapeutic areas ranging from asthma and cancer to schizophrenia and diabetes. Results from the comparative Mobile Diabetes Intervention Study of 163 patients found that adding a mobile patient coaching application, together with feedback on personalized analysis of blood glucose data and lifestyle behaviors via smartphones, substantially lowered glycated hemoglobin levels for more than a year.6 The long-term Healthy eHeart Study will combine use of social media, smartphones and wearable mHealth devices with clinic visits to develop more accurate predictions of heart disease, while creating personalized tools to forecast patients’ risk and disease progression.7

According to a 2015 SCORR/Applied Clinical Trials survey of CROs and other service providers, mHealth’s greatest benefits will come from improving data accuracy and patient experience.8 A growing body of research is evaluating mHealth capabilities to improve subject retention and reduce site management costs. With dropout rates as high as 30%9 and site management costs as high as $2,500 per month,10 data collection based on integrated wearable devices and smartphones could reduce site dependence and deliver significant cost reductions.

Drug developers identify five major challenges in the adoption of mHealth technologies in clinical trials:11

  • Data security and privacy
  • Data qualification and validation
  • Regulatory acceptance
  • Adoption costs and demonstration of return on investment
  • Implementing mHealth technology on a global scale

Evolving regulation will help drive adoption of mHealth-based research models. In this fast-moving environment, however, regulators are hard-pressed to keep guidance current and industry informed regarding the accepted use of these new technologies in the setting of regulatory submissions and product registration. The U.S. Food and Drug Administration has issued two sets of guidance (in 2014 and 2015, respectively) presenting regulatory views on use of mHealth technologies in clinical trials.11, 12 These evolving guidelines, together with regulatory consultation, can help sponsors determine regulatory acceptance of a given mHealth application in a specific trial setting.

 

Pilot Study: Evaluating feasibility of a wearable device in data collection

The ultimate goal of this transformative technology is to exceed standards for data quality and study efficiencies delivered by the current “gold standard” operational models. The application of wearable devices in clinical trials is beginning with feasibility evaluations to determine how mHealth technologies can be deployed effectively.

PPD participated in a collaborative, early-stage feasibility study of a wearable device-plus-smartphone application. Its goal was to evaluate the usability of the interface in data collection; training requirements for appropriate use of the mHealth technologies; and the impact of the model on data quality and patient engagement.

The feasibility study was conducted as a second, mHealth-enabled arm of a large observational study. In this arm, a subset of patients used two wearable monitors: one measured blood pressure, while the second measured patient activity. Smartphones equipped with Bluetooth-enabled links transmitted and tracked the data from the wearable devices to an investigator portal. Patients received medications, the wearable device-plus-smartphone technologies, and training to use the devices and smartphones correctly.

The goal was to test as many hypotheses surrounding the uses and types of wearable technologies as possible. For example, some patients received smartphones provided by the research team with the study mobile app installed; others downloaded the study mobile app to their own smartphones. Patients were instructed to wear the activity monitor at all times and to take their blood pressure from the wearable device at scheduled times. This allowed for the analysis of data consistency, reliability and compliance from patients on data that is transmitted constantly and automatically—without any action by the patient—with data that needed patient interaction at scheduled times. Measurements were aggregated for use in feasibility and operational future studies.

 

Conclusion

The volume of health data generated by mHealth devices will be transformative across the entire health care spectrum, from wellness and prevention to treatment and research. During the next five years, mHealth technologies will mature to enable advanced research models, including cloud-based health databases of continuously uploaded patient data and Internet-based trials conducted remotely. This future envisions “mTrials” that use wearable devices, smartphone and tablet apps, and patient-physician interactions via telemedicine to collect accurate data in real time. The immediate challenge is to integrate mHealth technologies into global research processes, and to learn how best to apply and interpret the data tsunami they are about to deliver.

 

Niklas Morton, is Senior Vice President of Biostatistics, Programming, Medical Writing and Innovation, PPD; David Blackman, is Business Innovations Director, PPD

 

References

1. PriceWaterhouseCooper, “Emerging mHealth: Paths for Growth,” Global Research Study 2012, https://www.pwc.com/gx/en/healthcare/mhealth/assets/pwc-emerging-mhealth-full.pdf 

2. J.E. Andrews and J.B. Moore, “Mobile Technology in Human Research,” Journal of Clinical Research Best Practices, 11(2) (2015).

3. M. Campbell, “Apple Patents Sensor-packed Health Monitoring Headphones with ‘Head Gesture’ Control,” AppleInsider.com, February 18, 2014, http://appleinsider.com/articles/14/02/18/apple-patents-sensor-packed-health-monitoring-headphones-with-head-gesture-control

4. S. McKee, “Google’s Wristband Tracker to be Fit for Clinical Research,” PharmaTimes, June 23, 2015, http://www.pharmatimes.com/article/15-06-23/Google_s_wristband_tracker_to_be_fit_for_clinical_research.aspx

5. Apple ResearchKit, “Now Everybody Can Do Their Part to Advance Medical Research,” http://www.apple.com/researchkit

6. C.C. Quinn, M.D. Shardell, M.L. Terrin et al, “Cluster-randomized Trial of a Mobile Phone Personalized Behavioral Intervention for Blood Glucose Control,” Diabetes Care, 34(9):1934-1942 (2011).

7. Health eHeart Study, “What Makes This Study Different?” https://www.health-eheartstudy.org/study 

8. SCORR Marketing and Applied Clinical Trials, “Mobile Health in Clinical Trials Survey Report,” 2015, http://www.scorrmarketing.com/resources/mobile-health-in-clinical-trials/

9. National Academy of Sciences, “The Prevention and Treatment of Missing Data in Clinical Trials,” Washington, D.C. National Academies Press, 2010. http://www.nap.edu/openbook.php?record_id=12955&page=14 

10. M.J. Lamberti, C. Brothers, D. Manak, K. Getz, “Benchmarking the Study Initiation Process,” Therapeutic Innovation & Regulatory Science, 47(1):101-109 (2013).

11. U.S. Food and Drug Administration, “Draft Guidance for Industry: Intent to Exempt Certain Class II and Class I reserved Medical Devices from Premarket Notification Requirements,” August 2014 http://www.fda.gov/ucm/groups/fdagov-public/@fdagov-meddev-gen/documents/document/ucm407292.pdf 

12. U.S. Food and Drug Administration, “Guidance for Industry: Mobile Medical Applications,” February 2015, http://www.fda.gov/downloads/MedicalDevices/.../UCM263366.pdf

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