CUTTER BUSINESS TECHNOLOGY JOURNAL  VOL. 33, NO. 9
  

Healthcare disruption by technology is not a novel idea. Clayton Christensen predicted it in The Innovator’s Prescription: A Disruptive Solution for Health Care well over a decade ago, when he suggested that technological innovation would propel healthcare toward affordability and accessibility through the decentralization of healthcare delivery services.¹ While Christensen’s observations were more focused on medical devices and diagnostic equipment and less on the smartphone apps and wearables explosion, his decentralization concept is exactly what has hap­pened. In recent months, COVID-19 has made the potential of digital in healthcare clear to everyone who had not seen it yet, as pandemic restrictions have forced the wholesale adoption of mobile health (mHealth) in many areas. One of those areas is clinical trials, where sponsors, investigators, and patients have all had to adapt rapidly to a shifting environment. This shift will not be tem­porary, so now is a good time to take a new look at how mHealth can change many aspects of clinical trials.

mHealth, defined by the World Health Organization (WHO) as “any medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, personal digital assistants, and other wireless devices,”² can be seen as part of telehealth and also as a major component in the digital health space. This article provides an overview of the mHealth market and select innovations, benefits, barriers, and challenges of mHealth adoption in clini­cal trials, as well as what is required for success­ful mHealth adoption across stakeholders.

Rapid Growth of mHealth App Market

The mHealth market is primarily segmented into mobile apps and wearable devices/biosensors. While adoption of mHealth in clinical development has not been widespread, the general use of wearables and related apps (e.g., Apple Watch, Fitbit, Headspace, or Insight Timer) has exploded, making virtual clinical trials (VCTs) possible. VCTs, also called “remote” or “decentralized trials,” are “a relatively new and yet underutilized method of conducting clinical research taking full advantage of technologies such as apps, electronic monitoring devices, and online social engagement platforms.”³

The global mHealth app market reached US $28.3 billion in 2018 and is forecast to reach $102.4 billion in 2023.⁴ Recent studies show that there are 550 million+ global active users (at least once a month),⁵ 325,000+ health apps available in the market,⁶ and 45,000+ mHealth app developers.⁷ The app landscape is rapidly evolving as well. In 2015, only 10% of apps were able to connect to devices and sensors and even fewer could be integrated with provider systems.⁸ While the majority of apps still target consumer self-management of overall wellness, diet, and exercise, the number of apps for disease treatment, diagnostics, and remote monitor­ing has increased (see Figure 1). App connectivity to sensors, data aggregators, and other third parties has improved, too. Currently, the therapeutic areas leading the clinical use of health apps are diabetes, cardiovascular disease (weight management), and certain mental health and behavioral disorders.⁹

In 2015, 300 clinical trials used mHealth apps as part of the study design.¹⁰ Furthermore, a recent study by Kaiser Associates conducted for Intel forecasts that 70% of clinical trials will incorporate sensors by 2025.¹¹ As Table 1 (a snapshot of a ClinicalTrials.gov search) illustrates, the trend of app and sensor integration into clinical trials is clear. Although mHealth applications have not yet become prominent in trial descriptions on ClinicalTrials.gov, we can expect the number of mentions of mHealth applications to grow rapidly in the near future.

The mHealth Device and Sensor Market

The global healthcare wearable device market is projected to reach $46.6 billion in 2025.¹² Common wearable devices and sensors include fitness trackers, electrocardiogram monitors, smartwatches, and blood pressure monitors. These devices measure a variety of biological functions (e.g., blood oxygen saturation, heart rate, electrical signals) and can be worn on the body or attached to the skin in the form of a patch, a chip, a watch, wrist/ankle bands, necklaces, or headbands. This market is closely linked to the app market as many of the devices are managed through smartphones.

Significant innovation in devices and sensors has occurred over the past five years. One example is the ingestible wireless sensor Abilify MyCite from Proteus Digital Health.¹³ However, although Abilify MyCite gained significant interest and publicity within the digital health space, Proteus Digital Health was forced to file for bankruptcy protection in June 2020.¹⁴ Its assets have since been sold to Otsuka, the marketer of Abilify (the drug used in Abilify MyCite). It is likely that the bankruptcy of Proteus Digital Health was due, at least in part, to the inability of the firm to integrate the operations of its ingestible sensor technology into the workflow of healthcare providers (HCPs). The integration of workflow and data between the device, HCPs, and drug companies is a challenge that many technol­ogy innovators will likely face in the commercialization and launch of complex device and sensor products. Integration of workflow and data is often a challenge due to concerns with patient privacy, data integrity, system/IT integration, and data storage. Oftentimes, healthcare and drug companies, the intended custo­mers of device and sensor innovations, are not readily equipped with the internal capability and infrastructure to be able to seamlessly operate and transfer data from the device system to another system.

mHealth in Healthcare

Since the first introduction of the smartphone and wearable device technology, rapid progress has been made in using mobile and wireless technology for healthcare (see Figure 2). Today, COVID-19 has turbocharged the need for companies to be more aggressive and innovative in how they leverage mHealth and other digital applications in clinical trials.

This is becoming visible in various ways. Within the industry, many pharma companies have been forced to adopt mHealth applications in their ongoing trials to ensure patients were treated. Early in the pandemic, some companies delayed or paused trials, but after a few months most companies started adapt­ing to the new situation and introduced different approaches. Examples of this include monitoring, where new approaches to source data verification have been explored; patient assessments (through tele­health rather than in-person visits); and the introduction of apps and wearables to obtain required data, which became much more difficult to obtain as COVID-19 caused site closures and patients simply refused to leave their houses (or government guidelines did not allow them to do so). In the general health field, which is usually a bit in advance of clinical trials in the adoption of mHealth, Evidation Health launched COVID-19 Pulse, a national study that tracks the attitudes and behaviors of the population during the pandemic using Evidation’s Achievement app.¹⁵ Similarly, San Diego-based Scripps Research Translational Institute launched DETECT to gather data via the MyDataHelps app on activity, heart rate, and sleep patterns.¹⁶ The Consumer Technology Association (CTA) launched the Public Health Tech Initiative to explore opportunities for using consumer technology to address public health emergencies.¹⁷ These initiatives will not only improve disease tracking and public health sur­veillance but will also enable better understanding of how to implement mobile technology in future clinical trials.

Major Benefits of Leveraging mHealth in Clinical Trials

Figure 3 outlines potential usage and applications of mHealth across the lifecycle of a trial. When used effectively, mHealth can provide significant advantages in clinical trial execution. These benefits include: (1) improved data quality and availability, (2) better patient engagement and adherence, and (3) more effective execution, which overall will lead to a more robust trial and faster time to market.

Improved Data Quality and Availability

mHealth, in the form of apps, sensors, wearables, and so forth, enables the collection of a significantly higher (in some cases, continuous) data volume. By reducing human involvement in data collection and documen­tation, one can expect the quality to improve. The increased volume improves robustness, especially if data collection is in real time, continuous, and passive. Another key advantage is that because mHealth allows for a better understanding of a patient’s normal, everyday behavior, it becomes easier to differentiate the effects of treatment. The use of real-world data in combination with trial data, obtained through mobile technology and by engaging patients and HCPs, is another avenue to strengthen the data overall.

Better Patient Engagement and Adherence

The use of mHealth with patients can start early, in the study design process, and continue in recruitment. Using an app or other feedback mechanisms during the enrollment process can provide valuable input into the protocol early in the trial. Moreover, making mHealth an important component in the protocol design with the patient in mind can reduce patient burden by limiting the number of clinic visits for treatment and assessments. mHealth is already being successfully used in the informed consent process; rather than having the patient meet in person with the HCP, informed consent can, in some situations, be obtained from patients through apps and video, live remote video meetings, or other “mobile” applications. In many cases, patients’ own smartphones can be used for data collection with­out the need for additional devices. Many devices use passive data collection and cause minimal disruption to a patient’s daily routine. Reducing patient burden is becoming more and more important as patients become better informed and look for clinical trials that meet their needs. Being able to respond to patient needs provides sponsors with a competitive advantage in enrolling studies. Effective application of mHealth results in more engaged patients, making it easier/quicker to recruit and enroll patients, which has a positive impact on costs. An additional benefit may be increased trial participation by members of underrepresented groups (e.g., rural, elderly, low income) with historically low participation rates.

More Effective Trial Execution

Mobile technology can be a major factor in effectively managing data obtained throughout the study. Clinical trials involve many people, many locations in multiple countries, and, often, multiple companies and partners. Despite significant variation among sponsors, contract research organizations (CROs), sites, and patient popu­lations, the processes to capture, check, correct, analyze, and file the relevant data remain inefficient and error-prone due to frequent human interaction points. The use of mobile tools, while increasing, is still in its early stages and offers significant upside for companies: more data (volume), higher-quality data (fewer human touchpoints), and faster processing of data (quicker time to submission may mean faster time to market). Realizing this upside will require appropriate systems, appropriate data governance, appropriate processes, and appropriate ways of effectively and securely working and sharing with all relevant parties.

Successful Adoption Requires Alignment of Multiple Stakeholders

The adoption, integration, and implementation of an mHealth model in clinical trials require significant efforts from various stakeholders in the healthcare ecosystem. Patients may need to expend less effort, but other stakeholders will need to put systems, processes, and governance in place to share, receive, interpret, analyze, and protect data and information, as well as develop the capability in their workforce to work with the data and information.

Patients

Patients are important stakeholders if mHealth is to become a major factor in delivering clinical trials. Technological solutions (e.g., apps, wearables) need to be designed with the patient in mind, whether the technology is used for any type of data capture or to limit the number of patient visits to the clinic. Mobile equipment may mean that instead of patients visiting the clinic, the clinic is visiting them. In addition to patients’ benefiting from the mobility afforded by mHealth, the technology must offer patients ease of operation and provide security measures. A wearable that records data passively is, of course, different from electronic patient-reported outcomes (ePRO) solutions, where patients actively provide data (which introduces a subjective element), and from having an HCP visit the patient with mobile equipment to perform dosing or assessment.

Sponsors and CROs

We treat sponsors and CROs as a single stakeholder category because both can potentially perform all activities involved in an end-to-end trial. The following describes the major phases of a clinical trial (with no intention of being exhaustive):

• Study design. Developing the appropriate protocol to integrate the selected mHealth aspects into a study is key. This requires a deep understanding of what the patient will need, what data will be captured, how the data will be processed and analyzed, and how the regulator will react. One pharmaceutical executive recently noted that the volume of data generated from wearables in one trial was so high that a major upgrade in capacity and capability would be required to be able to process and use all the data.

• Study startup. Many components are in play at this trial stage. Can mHealth be a component in site activation; for example, in the training of site staff? Can we deploy mHealth tools to manage informed consent in a more effective way? Can patients find and register for clinical trials on their phones?

• Study conduct. Clinical monitoring, both remote and virtual variants, obviously comes to mind here. Patient interactions may occur offsite, whether patients interact through their phones, are constantly monitored through a smart patch or wearable, or have an HCP visit to do assessments using mobile equipment.

Investigators and Sites  

The impact of mHealth on clinical sites and investigators will vary. Sites that struggle with resources may welcome mHealth, as it may reduce resource needs. On the other hand, a perceived limitation of interaction with patients might be resisted. mHealth provides the potential for improved patient and investigator interaction and may allow real-time remote patient monitoring. However, concerns exist that investigators are now more removed from patients and cannot be in full control of the study procedure and patient safety. What is certain is that sponsors will need to invest in bringing sites along with them on their journey toward implementing mHealth in their clinical trials.

Technology/Digital Health Players

The pandemic has put telehealth firmly on many agendas, and mHealth is very much part of the discussion. While healthcare systems, pharmaceutical companies, and patient organizations are obvious participants in these discussions, the big technology companies are also significant players. Apple, Google, and Amazon all produce wearables. These companies control the app environment through their operating platforms and are very active in developing capabilities (mostly through M&As) in this space. Apple and Microsoft have acted as the lead sponsors for a few trials, but, in general, they seek to work in partner­ship with pharmaceutical companies to deploy their technology and other capabilities into clinical trials.

Continued innovation in mobile app, sensor, and device functionalities will enable full adoption of mHealth into clinical trials. While connectivity between devices and apps and the Internet of (medical) Things continues to improve, there is much progress still to be made in seamless connectivity with, and integration into, provider healthcare systems and sponsor systems. The ability to connect with HCPs is important for clinical trials because it makes the use of real-world data possible. The integration of mHealth with electronic medical records (EMRs) is complex and presents many implementation challenges.

Regulatory Agencies

The first thing to consider when we talk about the regulatory environment for mHealth is that mHealth is not just the purview of the health authorities. Taking the US as an example, in addition to the Food and Drug Administration (FDA), other federal agencies that have a stake in the regulation of mHealth are the Federal Communications Commission (FCC) and the Federal Trade Commission (FTC). The Office for Civil Rights (OCR), within the US Department of Health & Human Services (HHS), governs the Health Insurance Portability and Accountability Act (HIPAA) and will also be involved. Still other agencies and committees have mandates that give them a seat at the table for any mHealth discussion. The involvement of so many regulatory agencies does not make the governance of mHealth easy, and, at this point, one reason why companies are reluctant to get out in front and invest heavily is that many questions remain unanswered, meaning that the goalposts are still moving.

This fluid landscape poses risks to developers, pro­viders, patients, and the public. Creating regulatory standards for mobile apps, wearables, and cloud adoption will be challenging but is not optional. Regulators must ensure strict and robust regulatory oversight but in a way that is both conducive to technological advancement and the protection of patient data.

Barriers and Challenges

Organizations face many barriers and challenges in bringing mHealth into their clinical trials. The main challenges are: (1) data integrity, privacy, and security; (2) changing company culture in a fairly traditional space; (3) an evolving regulatory environment; and (4) lack of empirical evidence to support the value-add of mHealth for the various stakeholders involved.

Data Integrity, Privacy, and Security

Significant challenges exist for health data privacy, security, validation, and governance. This is partly because data policies of most mHealth apps are not clear and the mechanisms to protect data integrity and privacy have not kept pace with advances in mHealth technology. A report by UC San Diego¹⁸ outlined examples of malicious attacks associated with wireless connectivity and communication in mHealth applications, including resource depletion, replay,¹⁹ and external device mis-bonding attacks. These threats interfere with the operating system of the device, which may lead to data manipulation and fraud.

Company Culture Shift and Change Management

The operation of clinical trials is a traditional space in many ways. Although there has been significant innovation in trial design, companies have been reluctant and risk averse in innovating in operations. For example, despite statements of interest in new approaches to recruitment or monitoring, few people want to apply those new approaches to their trial. Failing while using the tried-and-tested approach is perceived as not being as bad as failing while try­ing something innovative. The pandemic (again) has shifted this perception, as companies have been forced to move outside their normal processes because external circum­stances have put trials and patients at risk. The pandemic has effectively given companies a free pass to try something new. While not all changes will stick, innovations in patient enrollment, monitoring, and home visits (a major component of the virtual trial) are here to stay.

This forced change will reverberate across the clinical development space, including sponsors, CROs, hospital systems, regulators, investigators, patient organizations, and, of course, the technology and mHealth companies that have shifted their innovation into high gear. The ramifications of change will, in turn, require new capabilities in terms of data handling and analysis, governance, processes, and systems infrastructure. Forced change does not mean that everyone will automatically adapt, so organizations will need to make the effort to have change seriously stick. It means that companies will need to deliberately manage change, involve key stakeholders and impacted people so that they can understand what will change and why, and adapt accordingly, to ensure any change is lasting and perceived as positive.

Lack of Regulatory Clarity and Support

In 2017, the FDA introduced the “Digital Health Innovation Action Plan”²⁰ to foster digital health innovation. In April 2018, the agency outlined its guidance and plan for digital health, and in September 2019 updated its guidance and launched its digital health software precertification pilot program (“Pre-Cert”).²¹ Other health authorities have similar ongoing initiatives. As mentioned, health authorities are not the only interested regulatory agencies, which complicates the prediction of outcomes. Another complicating factor is that the US, EU, and China, while quite collaborative where health authorities are concerned, are not neces­sarily on the same page regarding data privacy, mobile technology, and intellectual property. This makes for a fascinating, yet difficult to navigate, landscape.

Lack of Empirical Evidence to Support Value-Add of mHealth

Rigorous investigation is needed to understand the full spectrum of mHealth value-add across clinical trials. To date, few studies have assessed mHealth from a quality and value-add perspective. Health app functionality and consumer/patient adoption, behavior, and usage are some of the critical aspects not yet well understood.

How Companies Can Best Use mHealth in the Future

There is no doubt that mHealth will be an important enabler for clinical trial design and delivery. Innovation is accelerating and while the regulatory landscape is fluid, it seems certain that mHealth will be a major factor in clinical development. Organizations need to adapt and be in the right place at the right time. To prepare for this imminent change, companies must:

• Develop capabilities to take advantage of opportunities by:

  • Partnering with mHealth and digital health players.

  • Building data capabilities and infrastructure.

  • Recruiting people with multiple skill sets and domains of experience and expertise (e.g., in both a digital environment and the clinical operations space).

  • Investing in resources to identify trends and intersections with respect to regulations, data and technology, and clinical trial innovation.

• Understand how attitudes to risk across the organization impact innovation.

• Develop the infrastructure to prepare for a dynamic future:

  • Cloud-based solutions are gaining prominence for easy access and storage of data and the upload of EHRs directly from sensors.

  • 5G will bring more extensive computing capabilities and enable a health-specific Internet of Things.

• Last but not least, focus on the patient. Patients are at the center of the drive for more accessible trials, with the aim of lowering the patient burden and making the trials about them, rather than focusing on commercial or scientific interests.

References

¹Christiansen, Clayton M., Jerome H. Grossman, and Jason Hwang. The Innovator's Prescription: A Disruptive Solution for Health Care. McGraw-Hill Education, 2009.

²World Health Organization (WHO). “mHealth: New Horizons for Health Through Mobile Technologies.” Global Observatory for eHealth Series, Vol. 3, 2011.

³Pathak, Devika. “Trending: Virtual Clinical Trials Market 2020.” Weekly Wall, 10 August 2020.

⁴“Mobile Health (mHealth) App Market — Industry Trends, Opportunities, and Forecasts to 2023.” Knowledge Sourcing Intelligence LLP, November, 2017.

⁵“mHealth App Developer Economics 2016: The Current Status and Trends of the mHealth App Market.” Research 2 Guidance (R2G), October 2016.

⁶van Velthoven, Michelle H., John Powell, and Georgina Powell. “Problematic Smartphone Use: Digital Approaches to an Emerging Public Health Problem.” Digital Health, Vol. 4, January-December 2018.

⁷Kao, Cheng-Kai, and David M. Liebovitz. “Consumer Mobile Health Apps: Current State, Barriers, and Future Directions.” Clinical Informatics in Physiatry, Vol. 9, No. 55, 18 May 2017.

⁸“Patient Adoption of mHealth: Use, Evidence, and Remaining Barriers to Mainstream Acceptance.” IMS Institute for Healthcare Informatics, September 2015.

⁹Vaghefi, Isaac, and Bengisu Tulu. “The Continued Use of Mobile Health Apps: Insights from a Longitudinal Study.” JMIR mHealth and uHealth, Vol. 7, No. 8, August 2019.

¹⁰Vaghefi and Tulu (see 9).

¹¹Kaiser Associates. “Enterprise-Purchased Wearables and Consumer Health Data Platform.“ In “AI and Wearables Bring New Data and Analytics to Clinical Trials.” Intel, May 2016.

¹²“Wearable Healthcare Devices Market by Type: Diagnostic (ECG, Heart, Pulse, BP, Sleep), Therapeutic (Pain, Insulin), Application (Fitness, RPM), Product (Smartwatch, Patch), Grade (Consumer, Clinical), Channel (Pharmacy, Online) — Global Forecast to 2025.” MarketsandMarkets Research, 2020.

¹³“Abilify MyCite.” Otsuka America Pharmaceutical, Inc., 2020.

¹⁴Reuter, Elise. “Proteus Files for Bankruptcy: Where Did It Falter?” MedCityNews, 16 June 2020.

¹⁵“COVID-19 Pulse: Delivering Regular Insights on the Pandemic from a 150,000+ Person Connected Cohort.” Evidation, 18 March 2020.

¹⁶“Scripps Research Invites Public to Join App-Based DETECT Study, Leveraging Wearable Data to Potentially Flag Onset of Viral Illnesses.” Scripps Research, 25 March 2020.

¹⁷Anandwala, Riya. “Major Health, Tech Leaders Join CTA’s New Initiative to Respond to Future Pandemics.” Consumer Technology Association (CTA), 27 July 2020.

¹⁸Ohno-Machado, Lucila, et al. “Privacy, Security, and Machine Learning for Mobile Health Applications.” American Association for the Advancement of Science (AAAS), 2014.

¹⁹A replay attack is “a category of network attack in which an attacker detects a data transmission and fraudulently has it delayed or repeated.... Replay attacks help attackers gain access to a network, gain information which would not have been easily accessible, or complete a duplicate transaction” (Techopedia, 2020).

²⁰“Digital Health Innovation Action Plan.” US Food & Drug Administration (FDA), July 2017.

²¹Abernethy, Amy. “Statement on New Steps to Advance Digital Health Policies that Encourage Innovation and Enable Efficient and Modern Regulatory Oversight.” US Food & Drug Administration (FDA), 26 September 2019.