The definition of m-health can be cited as early as 2004 as “mobile computing, medical sensor, and communications technologies for health-care” and even prior to that as the self-explanatory “Unwired e-med.”1 This more than 13 years-old prediction on wireless tracking accurately stated that health monitoring would be taken outside of a stationed, physical locale—bound by the desktop—and onto the new frontier of mobility. No longer is a patient taxed with being hooked up to a plethora of devices, an unpleasant experience for most, when they can be reliant on technology that travels with them anywhere. This happens namely in the form of sensors, which are constantly screening everything from steps taken to heart rate, to do the job.
In a seminal paper on this technology entitled, “Introduction to the Special Section on M-Health: Beyond Seamless Mobility and Global Wireless Health-Care Connectivity,” the challenges perceived of m-Health turned out to be highly perceptive. For instance, one of the reasons cited for the industry’s slow progression of m-Health included the lax adaptation of the tools by healthcare organizations, which are often dependent on internal organizational changes before integrating new technology into their systems; this would be seen as an overhaul. The other definite challenge posed by m-Health and healthcare is the integration of the real-time results from the m-Health platform with the patient’s medical records and data collection methods in general, including the pertinence of the data.1
How willing are we to monitor?
In the general public, m-Health has already reached a saturation phase. According to results from the “Ketchum mHealth Monitor” there are five types of distinct users of mobile health technologies.2 The study chronicles user opinions on m-Health and reveals potential roadblocks and strengths of the technology. Each of the five personas establishes insights that are useful in understanding shortcomings or applications of m-Health earlier on. This is looking towards the ultimate target for m-Health as the successful and routine integration into clinical trials.
The most translatable evidence gleaned from monitoring the perception of the everyday user of m-Health is an overall willingness to share their personal findings with a medical professional. Out of 10 respondents, six would not only share their results but have already done so. Again, in keeping in line with the modes of the tech, this comes in user-friendly forms of communication such as “going on the Internet on their smartphone, mobile app or wearable device.”2 It should be noted that there is no mention of a visit to a clinician’s office, or even a call. It’s as though the user has become part of the tech itself, transmitting their personal data, which merges across a wireless, interconnected network. Of course, this is not possible in most clinical trials, but it does indicate that the user is more inclined to share when the task is easier, and therefore more likely to create a desired result.
That one in four users have texted or emailed a photo of a perceived medical issue2 for increased clarification to their medical practitioner is also worthy of mention—though this behavior is not as far-reaching as simply sharing with the doctor, it also reveals the inquisitiveness of patients when dealing with their issues—they want clarification and want it fast, and would likely prefer to send an image as opposed to spending time in an office. This points to the wireless nature of the future of medicine—as we become less bound to the physical act of visiting the doctor.
The trials of clinical trials
Hurdles to clinical trials are not few and far between. Robert Califf, vice chancellor for clinical research and director of the Duke Translational Medicine Institute, outlined the particular issues he faces in cardiovascular medicine, which are demonstrative of issues across the board. He noted the following problems or pressures in his dealing with trials:
- The time and financial demands of clinical practice
- Overall shortage of cardiovascular specialists
- Increasing complexity of regulations
- Increasing complexity of contracts
- Lack of local supportive infrastructure
- Inadequate research training
- Less enjoyment from participation (e.g., increasing business aspects, CRO pressures)
- Data collection challenges (medical records, reimbursement, quality control, pay for performance)3
And the issues do not stop there. Physicians are not incentivized to refer patients to trials, even though patients might stand to benefit from enrollment. Another problem is centered on the trial environment, where a decreasing workforce is common. Many are forsaking labor in clinical trials for lab work, where results come with fewer hurdles and it can be easier to publish. Lab research also leaves out the need for Institutional Review Board (IRB) approval, which is an integral component of all trials. IRB and in turn, ethical approval have been noted as two of the top barriers to clinical research. This also includes the approval of protocol, scientific review, adequate resources, and interaction with the industry as well as issues with technology transfer.
All this is on top of a general lack of clarity on what oversight bodies are meant to be doing in trials, and a taxing informed consent process. That being said, patient recruitment does not come easily—with eligibility proving a further hurdle. This, as well as time between studies, the poor collection of data and other ethical considerations, can all be further bottlenecks and contribute to poor subject retention. A study from 2009 chronicles that out of 14 cancer centers, only 50% were unable to recruit even one patient for study treatment; this illustrates just how difficult getting a clinical trial study together can be.3
The future of patient monitoring
Taking these inherent challenges into consideration, m-Health has the potential to revolutionize the way trial information is collected and the way that participants engage with the trial. Putting the onus on the patient will likely translate to more direct results in trials, as the patient feels responsible for, and in tune with, their own health. Some companies are already beginning to harness the power of m-Health for trials, with Takeda being one of them. The Big Pharma company has partnered with Cognition Kit, which was formed as a venture through both Cambridge Cognition and Ctrl Group, to test a tracking app, available through Apple Watch, that will monitor those suffering from depression. This trial will confirm the effectiveness of m-Health channels to track those suffering from mental health issues with emphasis placed on both moods and cognition.4
The trial will be conducted with 30 adult participants who suffer from depression that is either mild to moderate, and are currently taking an anti-depressant. The aim of connecting to the Apple Watch is to gather an overarching view of patient compliance and confirm how subjects report data when they are constantly connected to the monitoring device, including whether the data is useful. Mental health wearables, as these types of cognition-monitoring devices are deemed, are positioned to promisingly impact clinical trials for neuroscience in a big way. Cambridge Cognition chief science officer, Jenny Barnet, commented on this tool. She said, “By combining wearable technology with world leading neuroscience, we’ve created an app that collects real time passive and active high-frequency mental health data. Being able to access data regularly from daily life can help clinical decision-making. Healthcare professionals can obtain patient data and increase patient engagement in their treatment.”4
Research on the research
In the 2017 Nice Insight Preclinical and Clinical Contract Research Survey, 34% of buyers outsource to CROs for Clinical Trial Recruiting—a number that is up 14% in just one year. Clinical Trial Data Management rose sharply from 29% in 2014 to 50% in 2016, though 2017 numbers indicate this may have leveled off at 28%. While Electronic Data Capture (EDC), for Clinical Trials is outsourced by buyers at 20%. Buyers rank the top reason for engaging with a CRO as access to Specialized Technologies—which is seen as more important than either quality or being part of a company’s strategic plan.5
These figures indicate that the market is ripe for CROs to offer m-Health as part of their clinical trial platform. The results gathered from the 2017 survey on buyers of clinical and preclinical research services indicates that specialized technology is highly valued, more so than might have been previously imagined—who would assume specialized tech trumps quality? However, this is what the market indicates, and the CRO that can position itself at the forefront of e-capture tools, namely m-Health wearables, is certain to obtain a lion-share of the market.
This technology has the power to revolutionize trials, cutting out the bottlenecking of transport and the cumbersome middleman, cutting costs and ensuring efficacy by going to the subject directly. These technologies not only “go to the subject,” but for all intents and purposes, are the subject, as the clinical trial candidate is constantly monitored—their person is tracked at all times and in real-time. Whatever the hurdles that clinical trials present, m-Health has the potential to unlock data needed to confirm trial success in any phase, and eliminate the bottle-necking that has caused a strain on the industry thus far. Indeed, the future looks promising for the integration of m-Health wearables with the service offerings of CROs.
- 2017 Nice Insight Clinical and Preclinical Contract Research Study