Use of Digital Health Technologies for Real-World Data Collection

The use of mHealth apps for real-world data collection can be traced back to the introduction of the first iPhone by Apple in 2007, Crouthamel said. This breakthrough catalyzed the development of more than 2 million iOS apps in the years since. The 2015 launch of the Apple ResearchKit as a joint collaboration between Apple and academic institutions was an effort that laid the groundwork for the possibility of a fully digitized clinical trial. In 2016 GlaxoSmithKline began to explore and test this open-source platform, which led to the first industry-sponsored real-world study using the Apple ResearchKit: the Patient Rheumatoid Arthritis Data From the Real World study. Almost 400 people living with rheumatoid arthritis were recruited in just 30 days. Investigators were able to collect electronic consent forms, disease insights, and sensor data directly from the participants' smartphones. Through this effort, the investigators were also able to develop a novel digital measure of functionality called wrist range of motion, which enabled them to capture information about participants' pain at a more granular level (Crouthamel et al., 2018).

One advantage of the ResearchKit is that it can provide easy access to clinical trials, Crouthamel said, but it can be challenging to authenticate the potential participants. To address this challenge, particularly in the context of PMRs and PMCs, she suggested incorporating telehealth visits, creating study-specific access codes, and using facial recognition and fingerprints for authentication. Another benefit offered by ResearchKit is the capability to crowd-source patient insight in a cost-effective way. However, to avoid platform bias from a sampling perspective, it is helpful to use both ResearchKit for iOS and ResearchStack for Android to collect insights from a broader range of participants. Although using a virtual platform can enable the rapid recruitment of participants, a high dropout rate is a known disadvantage of this type of digital engagement. For longitudinal PMR and PMC studies, Crouthamel suggested creating incentives for participants, such as financial compensation, sharing data, and even providing medical benefits. Integrating human interactions into the study design is critical for participants who may be in a vulnerable state, she added. Through the ResearchKit platform, iPhone sensors can be used to create novel endpoints. While this is a powerful tool, it can be challenging to control for variability across users and how they provide their data. She emphasized that for industry developers, “good data [are] more important than big data.” Analyzing large volumes of unlabeled data can be difficult; however, including clear instructions and providing supervised training can substantially improve the quality of data collected. The most recent version of FDA's MyStudies² app largely addresses some of these challenges, and Crouthamel urged sponsors to adopt this platform to help standardize data collection and facilitate easier data review.

Integrating Digital Health Technologies into Post-Market Study Design

Integrating DHTs into post-marketing study design can enable surveillance and the monitoring of product safety among different subtypes of the study population, Crouthamel said. A hypothetical product for rheumatoid arthritis would have several subtypes of patients—such as males, females, and different age groups—that each have distinct needs. An advantage of DHTs is their potential to measure individual participants' baselines and better understand the degrees of improvement in clinical outcome. However, this capacity has not yet been realized because study design is largely still constrained by the traditional focus on using control groups and homogeneous study populations that may not accurately reflect the real world. Shifting the focus toward individuals and using digital technologies to capture personalized measurements would be a breakthrough for the field, she said.

Case Example: Digital Pregnancy Registry for Post-Marketing Research

Post-marketing research has become an active space for trials supported by DHTs, offering sponsors an opportunity to use their platforms to re-design traditional PMR, PMC, and real-world studies and collect higher-quality data in more efficient ways, Crouthamel said. To illustrate, she described how a digital platform could be used to re-design a post-marketing research and pregnancy registry study. The potential impact that a medication or other intervention can have on a pregnancy—such as miscarriage or birth defect—underscores the value of rapidly collecting and disseminating this type of data to patients and stakeholders. If such an effort were carried out with a traditional clinical trial design, it might take up to a decade to collect results, which would risk losing important data. For example, a patient who is prescribed a new medicine might become pregnant in the future, at which point she might go back to the same physician, who may or may not remember that there is a pregnancy registry available for this patient to be enrolled in and monitored by. The application of DHTs has the potential to sharply curtail the time it takes to collect results in a pregnancy registry by maximizing the clinical touch points digitally, she said. A DHT can remind patients who become pregnant about the registry and provide a channel for the patient to engage with the registry study coordinator. The coordinator can then encourage the patient to download the dedicated study app, which allows them to virtually engage with the investigator. The patient is engaged and does not have to travel while pregnant, and investigators can collect high-quality data.

Use of Digital Tools to Illuminate the Patient Experience

DHTs can be used to help illuminate the patient experience, Okun said. She described a hypothetical patient–clinician scenario in which the clinician is focused on the positive impact of a treatment based on certain indicators. In contrast, the patient is more concerned with—but does not express—other consequences of the treatment. Perhaps the patient is having trouble sleeping, is unable to exercise, and no longer enjoys food as much. All of those unexpressed factors will affect the patient's adherence to the drug or even the patient's interest in taking the drug at all. An open dialogue between the patient and clinician might be easier and more effective if the patient used a wearable device that was collecting data longitudinally about sleep cycles and other types of biometric measures, she said. This could also enable the visit with the clinician to take place virtually. Furthermore, if the biometric data were streamed to the clinician in advance of the virtual visit, it would free up more time for the clinician to discuss the patient's concerns in ways that are more concrete and engaging for the patient as an active participant.

Collaborating with Patients to Optimize Digital Solutions

DHTs also provide opportunities for working with patients to explore ways to optimize their use of digital tools. For example, by helping patients identify variables that interfere with their interest in or ability to maintain treatment, DHTs can provide new solutions to familiar problems. A recent qualitative study by Herrmann et al. (2020) investigated digital competencies and attitudes toward digital adherence solutions among elderly patients treated with novel anticoagulants. The study demonstrated that gaining a better understanding of the reasons for non-adherence can help inform possible digital solutions as well as improve understanding of the digital competencies that particular populations may need to take advantage of these digital tools. In collecting information during the post-marketing period, digital tools have value in helping to identify factors that may put a patient at risk of not using the medication as prescribed or otherwise compromising his or her health and safety.

Developing Patient-Informed Principles

Across the drug development cycle, information should be gathered from the patients themselves about the things that matter to them, Okun said. This is even more critical during the post-marketing period, she said, when patients are generally left to manage their daily lives with drugs and other products as part of their experience. During that stage, there is an opportunity to collect information from patients to better understand what motivates them to participate in a certain type of data collection model. In her experience, Okun said, patients value being seen as a whole person and desire opportunities to feel in control by contributing in an active way to the data being collected—for example, by prioritizing the things that matter most to them. Applying patient-informed measurement and design principles can provide guidance in this respect (see Box 6-1).

BOX 6-1

Patient-Informed Measurement and Design Principles.

Harnessing Existing Systems to Maximize Patient-Generated Health Data

To maximize the value of patient-generated health data, Okun suggested harnessing existing systems and bringing in information to address gaps not currently being filled by other data sources. For example, the comprehensive Sentinel Initiative launched by FDA in 2008 recently expanded its capacity beyond its data partners' environments by establishing a coordinating center, an innovation center, and a community-building and outreach center.³ If patients were broadly empowered to directly generate their own data in the post-marketing arena—through developers and apps deemed trustworthy—then patients themselves would become new data partners within the Sentinel system. Repurposing FDA's MyStudies app for the post-marketing arena as a MyTreatment app could provide an opportunity for clinicians and researchers to gather information about the patient experience, she said. If such an app were pre-populated with a patient's prescription(s), then they could easily input information about their experiences and potentially connect to other sensor data already being collected from them.

Using Digital Health Technologies to Inform Patient-Focused Drug Development

DHTs have the potential to exponentially amplify the voice of patients and bring patient-focused product development full circle, Okun said. There are existing funding mechanisms, such as the Prescription Drug User Fee Act, that could be used to support FDA's patient-focused drug development initiative (FDA, 2020b). Expanding this mechanism by using digital tools from trustworthy sources could help illuminate what daily life is really like for patients, she said. This body of data could offer valuable continuous learning opportunities about patients' real-life experiences in real time. This type of information could offer new insights and ways to better assess safety and tolerability, including relevant measures for outcomes that matter most to patients. By learning from patients and sharing that information broadly across systems, clinicians and researchers collecting this information could also benefit stakeholders who are not directly engaging with digital tools but would benefit from the insights gained from those who are.

Okun said that efforts to capture real-time data from people using digital tools during the post-market surveillance period benefit from considering the types of patients who would typically be using the tool for its intended purposes, how they will use the tools, and how mechanisms within the tool will address the specific needs of certain subpopulations of patients, such as those who speak a different language or those with digital literacy issues. For example, Herrmann et al. (2020) highlighted an opportunity to consider how the potential tools are fit-for-purpose, whether for regulatory decision making or for gathering data for point-of-care decision making.

Digital tools might also be used to further enhance or expand patient–provider communication, while also minimizing or being mindful of the burden on providers. The successful adoption of digital tools depends on obtaining and applying feedback from patients, Okun said. If the digital tools are to be used at the point of care, incorporating feedback from providers will also be helpful in gaining their buy-in and maintaining their interest in using the tools. For example, a study of veterans with epilepsy who were engaged with the platform PatientsLikeMe asked the participants' neurologists about information the neurologists would be interested in learning at the point of care about their patients' epilepsy experiences (Hixson et al., 2015). Three priorities emerged: the frequency of a patient's seizures, whether the patient lost consciousness during the episode, and whether there had been any triggers. Using this feedback, the digital tool was updated to include these questions and capture the patients' responses; this enabled the clinicians at the point of care to obtain the information they felt was most important. In addition to providing value to the clinicians, the patients demonstrated significant increases in self-management and self-efficacy within just 6 weeks.

Digital Health Technologies to Understand Drug Effectiveness in Real-World Settings

When clinicians consider a drug's effectiveness in the post-market context, Robinson said, a primary concern is whether the drug will work for their own patient population, which may include individuals who are older, sicker, more diverse, and affected by more comorbidities than the population that participated in clinical research. Another question that clinicians often have is whether a new drug is better than the current standard of care, particularly given that new treatments are frequently more costly. DHTs provide several opportunities to help answer these types of questions about effectiveness, Robinson said. For example, endpoint monitoring can be facilitated by digital technologies for activity tracking and for capturing physiological measurements (e.g., heart rate, blood pressure, pulse oximetry). Depending on a patient's disease state and the intervention, digital technologies can also facilitate remote monitoring of the endpoint that a specific intervention should be improving, such as continuous blood glucose monitoring. Conducting surveys about symptom improvements or quality of life can be facilitated online, via a smartphone app, text messaging, or even through voice recognition modalities. Opportunities now exist to use a combination of digital approaches to evaluate effectiveness, he said. For example, a new intervention for rheumatoid arthritis could be monitored using a combination of an activity tracker and a voice-administered quality-of-life survey. This could contribute to a practical and comprehensive understanding of whether the treatment is achieving the types of results that actually matter to a specific patient population compared with the current standard of care.

Digital Health Technologies to Assess Safety and Tolerability

Given that new treatments may have associated safety and tolerability issues that are more or less pronounced in special populations, Robinson said, it can be difficult for a clinician to determine which of these issues are more relevant than others for patient populations that are not typically included in clinical trials (e.g., older adults or people with comorbidities). A more nuanced understanding of a drug's toxicity profile should be developed during the post-marketing period in order to begin refining the patient population for whom that particular intervention is better suited, he added. Another common consideration for clinicians is whether the side effects of a treatment are impairing a patient's quality of life. The risk–benefit ratio may need to be reconsidered, particularly in patients dealing with difficult conditions, to determine if the incremental gains offered by the new treatment over the standard of care are worth managing the new side effect profile.

Opportunities for DHTs to help answer these types of questions about tolerability include digital survey modalities to evaluate side effects and quality of life, while DHTs for activity tracking, physiological measurements, and remote monitoring can be used to look at side effect endpoints. The increasing use of oncological immunotherapies has created a need to monitor the significant neurological side effects associated with immunotherapy, such as delirium. DHTs provide an opportunity to better understand how those side effects manifest in different populations, such as in older patients. For example, voice-analysis technology could be used to screen for delirium potentially caused by an intervention. Another opportunity is to use gamification, he suggested. Developing a mobile or online game with an endpoint linked to a prize or some other type of strategy to engage the user could also allow for measuring the user's ability to engage over time at sequential points. There may be some benefit to understanding how people navigate through a game, he said, which could be correlated with the neurological side effects from an intervention such as immunotherapy.

Digital Health Technologies to Improve Patient Adherence

One concern from a clinician perspective, Robinson said, is patient adherence to a treatment regimen. Adherence may vary by patient population, as the drivers of adherence are complex and may be shaped by social determinants and other factors. Robinson suggested that DHTs may help clinicians better understand how an intervention varies with respect to adherence as well as how patient adherence could be improved. Opportunities in this domain could include digital reminders and engagement with patients through apps and wearables. For example, digitally enabled medication dispensers and the use of “digital pills” that can track medication ingestion could be used in place of directly observed therapy to track the number of times that a patient dispenses a medication, Robinson suggested. This type of application could be helpful for supporting adherence for high-risk medications that patients need to take consistently (e.g., anti-tuberculosis medication). Additionally, Robinson suggested that a medication adherence strategy could apply gamification—extracting game design elements and game principles and using them to drive adherence—along with digital monitoring approaches.