Introduction

There are many hurdles to overcome when identifying, enrolling, and retaining study participants in clinical research. These hurdles are associated with numerous factors, including patient access and willingness to participate; protocol demands and eligibility constraints; and physician willingness to refer and facilitate participation. Although 85% of people are willing to participate in clinical trials, for example, only a fraction do [1]. It has been estimated that less than 10% of eligible adult cancer patients participate in clinical trials [2]. In a typical phase III clinical trial, more than one-third (37%) of clinical research sites under-enroll, and 11% fail to enroll even a single participant [3]. Moreover, due to dropout rates—on average estimated as high as 30% [4]—participant retention can compromise study results and carry significant financial consequences. In fact, the average cost per patient has risen by 70% in the past 3 years [5]. Further, recruitment and retention problems can delay clinical trial completion, costing sponsors up to $8 million daily [6] in lost drug sales.

In conventional clinical trials, participants visit investigational sites, often located in large medical facilities in metropolitan areas. The centralization of operations in such locations far away from where potential participants live may hinder participation [7]. To illustrate, 70% of potential participants in the U.S. live more than 2 h away from the nearest study center [8]. A 2019 study assessing patient engagement in clinical trials with more than 12,000 respondents identified travel to and from sites as the top study participation burden, with 29% indicating that it was “somewhat” or “very burdensome” [9]. In addition, these geographical constraints disproportionately affect underprivileged groups (e.g., people from lower socioeconomic groups may not be able to take time off work or afford to travel long distances for trial visits), particularly those with intersecting identities (e.g., racial minority women) [10]. This barrier may contribute to the lack of representation in clinical trials, jeopardizing external validity and generalizability of results and ultimately resulting in ineffective or even harmful drugs among certain demographic groups [11].

Clinical trial complexity has also grown significantly during the past decade, placing a substantial burden on investigative sites. Since 2010, for example, the average number of endpoints in phase II and III protocols has increased 27%, and the average number of procedures performed per patient visit has increased 22% [12, 13]. However, this complexity has run counter to patient expectations of greater convenience of care [14]. Moreover, growing interest in real-world evidence (RWE) in clinical trial data generation has called for data collection from the point of routine care in addition to locations outside the brick-and-mortar boundaries of the healthcare system [7].

The COVID-19 pandemic exposed the vulnerabilities of the conventional, site-centric clinical trial design in several ways [15]. First, the redirection of healthcare resources and staff to care for COVID-19 patients led to staff shortages, which were exacerbated by staff falling ill with COVID-19. Second, particularly early in the pandemic, on-site visits by clinical research associates were limited by the shift to a virtual setting due to government restrictions and regulatory guidance [16]. Access to sites was affected by geographical differences and the state of the pandemic. One survey of organizations within the sector showed that between 35 and 80% of sites were inaccessible [17]. Third, travel restrictions and stay-at-home orders prevented participants from visiting sites for regular dosing and assessment. Some contracted COVID-19, while others skipped visits out of fear. According to a poll, in May 2020, nearly half of Americans (48%) said they missed or delayed receiving medical care due to the pandemic [18], which was a key concern as missed visits and “out-of-window” visits led to protocol deviations that jeopardized data integrity. Finally, the pandemic also created shortages of ancillary supplies for clinical trials due to disruptions in the supply chain and logistical challenges involving transportation caused by lockdowns [19]. These issues affected subject enrollment, protocol adherence, trial operations, and data collection [20]. One analysis found an 80% year-on-year decrease in new patient enrollment for April 2020 [21]. Pharmaceutical decision-makers triaged trials by devoting resources to the most promising studies and those with the least risk for patients [17]. This decision ultimately led to the postponement or cancellation of planned studies and, in some cases, suspension or termination of ongoing studies [21].

To keep clinical trials going, minimize the risk of transmission of COVID-19, and preserve the continuity of care, data collection, and data integrity, many sponsors quickly deployed remote and virtual approaches (i.e., decentralized clinical trial (DCT) solutions), including eConsent, remote patient monitoring, data collection via wearable and mobile devices, and at-home assessments [22]. Consequently, DCT deployments soared during the COVID-19 pandemic. The number of clinical trials with virtual and/or decentralized elements surpassed 1000 in 2021 (a 50% increase compared with 2020), and 1300 trials were forecasted to initiate in 2022 [23].

DCT use in clinical trials promises to address a number of key drug development challenges. In addition to improving patient access and participation convenience, DCT solutions may also improve patient adherence to the protocol and may increase overall retention rates [24]. DCTs enable clinical research data to be collected more easily and faster, offering the opportunity to interrogate and draw insights from the data sooner, reduce the number of patients required, and increase statistical power [8]. The deployment of remote and virtual solutions may also offer operational efficiencies through the automation of select manual data collection tasks, more frequent communication and interaction with study volunteers, and more productive investigative site personnel [25,26,27].

Anecdotal reports and early case examples suggest that the promise of DCT use in clinical trials is being realized. Sponsors, contract research organizations (CROs), and DCT vendors have reported positive results with DCT deployments [28,29,30,31]. For example, Sarraju et al. [32] implemented a virtual study among atrial fibrillation patients, consisting of virtual recruitment via social media and virtual monitoring using a mobile application and sensors. Results showed high adherence, positive study engagement outcomes, and willingness to continue in a larger trial. Hilderbrand et al. [27] conducted a 1000-patient virtual clinical trial in just seven months at a fraction of the cost of traditional site-based recruitment, demonstrating the benefits associated with reducing recruitment cycle times, and overall improvement in patient experience as patients reported satisfaction and willingness to move forward with the study. Overall, these cases exemplify the feasibility and benefits of a decentralized approach.

With growing deployment experience, some sponsors and CROs have reported challenges introduced by DCTs, including increasing clinical trial execution complexity, longer study start-up durations, and higher costs associated with installing technologies and infrastructure, offering training to site personnel and study volunteers, and providing technical support [33].

As more is learned—both positive and negative—about DCT use in clinical trials, sponsors and their collaborative partners face great difficulty in weighing benefits and risks and anticipating operating challenges. In this paper, we apply systems thinking to guide sponsors and CROs in comprehensively considering remote and virtual solutions—their advantages, pain pointsFootnote 1 addressed and introduced, and trade-offs—in protocol design and execution planning processes.

Methods

Defining DCTs

DCTs are broadly defined as clinical trials wherein recruitment and data collection are not restricted to centralized location(s) as is typical for conventional trials. Table 1 summarizes the more common DCT solutions in use today.

Table 1 DCT Solutions

Among DCT deployments, there are two main variations: (1) DCTs that are entirely remote (full DCTs); and (2) DCTs that are partially remote (hybrid DCTs). Full and hybrid DCTs are achieved using telemedicine, digital health technologies, and approaches centralized around patient accessibility and convenience. The degree of decentralization can be assessed on two dimensions: the locality of the data capture (ranging from on-site research facilities to remote locations) and the methods for data collection (ranging through the use of intermediaries to fully virtual) [7].

Analysis that Applies Systems Thinking

We applied systems thinkingFootnote 2 to assess DCT deployment and its comprehensive interaction with the larger and complex process of clinical trial execution [36]. Systems thinking takes a holistic perspective when considering problems and their solutions [37].

A recent and relevant application of this approach is the “Engineering Better Care” systems framework that considered four interrelated perspectives (people, systems, design, and risk) to evaluate health and care design and improvement initiatives in an iterative and holistic way [38]. Importantly, the framework considers stakeholders and their needs, the system architecture, a range of possible solutions that would help meet the needs of the system, and an assessment of what could go wrong/and can be improved. Applying a similar “whole system” approach, we consider how decentralization impacts clinical development.

Since a system is defined by its interconnections, a change in one element of the system invariably impacts other area(s) of the system. Thus, when a solution is introduced to alleviate a pain point for one or more stakeholders, it may introduce new system demands and pressures for other stakeholders. The emergence and alleviation of stakeholder pain points result in an iterative process that introduces new solutions, which then may add new system demands and pressures that lead to different pain points. Figure 1 captures this iterative process for DCT deployments (and its impact on participants, sites, and sponsors). It is worth mentioning that the system may include a wide range of stakeholders, such as CROs, investigative sites, home HCPs, local care providers, regulators, institutional review boards, patient advocacy groups, payers, technology providers, couriers, and support services. The choice of focal stakeholders in the system depends on the purpose of the analysis and the goals one is striving to achieve.

Figure 1
figure 1

A Systems View of Pain Points for Participants, Sites, and Sponsors

This analysis helps to identify the appropriateness of DCT use in different settings based on the system's characteristics, such as the characteristics of the patient population, the disease, and the capacity and infrastructure availability. Various factors make certain studies or indications prime candidates for incorporating DCT solutions, which we will discuss in more detail.

Results

Figure 2 presents the results of our assessment on the impact of DCT solutions using a systems thinking approach applied to a single stakeholder, the study participant. Based on literature review and industry reports, we aim to cover many first-order effects.Footnote 3

Figure 2
figure 2

The Process of Emergence and Alleviation of Pain Points for Clinical Trial Participants

Table 2 supplements the analysis by providing key advantages, disadvantages, and considerations for DCT elements that may serve as solutions to stakeholder pain points in this reiterative process.

Table 2 DCT Solutions—Advantages and Challenges Mapping
Steps 1–3:

The emergence of pain points. Clinical trial participants have individual attributes such as their state of health, demographics, and personal preferences, as well as constraints such as work, familial, and other commitments. Participation in a traditional site-centric clinical trial requires them to travel to sites for visits and develop an understanding of the trial (i.e., their role in the trial and the associated risks and relevant terminology). Moreover, participants have roles and responsibilities such as remembering and attending visits, undergoing assessments, and filling out patient diaries, to name a few. Resulting from the system design/architecture, these system demands and pressures may conflict with participants’ attributes and constraints. For instance, consider a working single parent who may need to travel long distances to reach a site. Travel demands conflict with the participant’s work and familial commitments, leading to a pain point. Furthermore, this pain point can be particularly pronounced for participants from certain demographics (e.g., low socioeconomic status and those living in rural areas).

Step 4:

Possible solutions to alleviate pain points. There are many alternative solutions to alleviate stakeholder pain points. For example, financial compensation can be provided for missed work, reimbursements and stipends can be offered for travel costs incurred, and special travel can be arranged for participants with mobility issues. However, many of the pain points specified in Fig. 2 can be alleviated through DCT elements (i.e., home visits and mobile clinics, virtual visits, eConsent, ePROs, and digital health technologies).

Step 5:

Introduction of new system demands and pressures. Many DCT solutions—including the use of mobile devices and home-based assessments—transfer execution responsibility away from what was historically handled by site personnel to the participants themselves. If this demand conflicts with participants’ attributes (i.e., digital literacy, demographics) and/or preferences, this may lead to the emergence of pain points. In turn, new solutions may need to be introduced to address emerging pain points (e.g., discomfort with technology can be alleviated through participant training, round-the-clock support, etc.). Successive solutions present new demands and pressures, leading to new pain points.

Iterative steps: Minimization and management of pain points. By repeating Steps 2–5 multiple times, decision-makers can evaluate the emergence and alleviation of pain points in applying various solutions.

The resulting analysis and insights can allow decision-makers to identify ways to minimize or mitigate stakeholder pain points so that, ultimately, more value can be created from implementing DCT solutions.

DCT solutions identified for the participant analysis in Fig. 2 also address and alleviate pain points faced by sites (e.g., administrative burden and paperwork, errors from manual data entry, the workload associated with menial tasks stemming from site visits, etc.) and sponsors (large investigator grant payments, recruitment and retention issues, among others). However, by the systems view approach, such solutions may also introduce new demands and pressures onto stakeholders. Demands and pressures should again be assessed alongside all stakeholders’ attributes and constraints, and a similar process to the one illustrated in Fig. 2 should be performed for all key stakeholders.

Table 3Footnote 4 provides a sample of the new demands and pressures experienced by participants, investigative sites, and sponsors from the introduction of various DCT solutions. DCT deployments require the use of new technologies, new stakeholders and new stakeholder roles in the provision of care, and data collection outside of traditional investigative sites. Thus, demands and pressures arise from the two dimensions of decentralization (digitalization and locality) [7] introduced earlier, and can be broadly grouped into four categories: the introduction of new technology, reliance on staff outside of sites, a greater reliance on the participants themselves, and changes to the supply chain.

Table 3 A Sample of the New Demands and Pressures Introduced by DCT Solutions and Resulting Pain Points Faced by Sponsors, Sites, and Participants

Multiple detailed and holistic iterations designed to alleviate stakeholder pain points culminate insight into primary advantages such as a reduction in site burden, enhanced access and increased diversity, improved external validity of findings, and possible cost savings. However, the demands and pressures imposed by DCT solutions on clinical trial systems also amount to several overarching challenges, including potential inequalities, privacy and data protection issues, and complex operational requirements.Footnote 5 Despite these challenges, enablers (such as growing regulatory agency commitment and digital advances) moderate the degree to which the new demands and pressures actualize into pain points and, therefore, continue to spur demand for DCT solutions. A detailed discussion on the advantages, disadvantages, obstacles, and enablers associated with DCTs can be found in the Appendix.

Discussion

What becomes apparent through systems thinking analysis is that the appropriateness of DCT use differs depending on system characteristics. Various factors make certain studies or indications prime candidates for incorporating DCT solutions. Discomfort and unfamiliarity with technology is a participant pain point associated with the digitalization component of DCTs. For sites and sponsors, important considerations include constraints relating to the specifics of the study (e.g., the therapeutic area, the phase of the trial, the incidence and prevalence of disease, etc.), national and international regulatory environment, existing resources and infrastructure (e.g., staff, equipment, technology, competencies, procedures, etc.), and the budgets for clinical trial conduct.

Clinical Trials Arena has tracked the distribution of different DCT categories by therapy area [40]. The analysis finds that telemedicine and remote monitoring are the most widely accepted DCT components across therapy areas. Telemedicine has been used the most in infectious disease and oncology trials, while, perhaps not surprisingly, remote monitoring (using sensors, device, and trackers) has been prominent in cardiovascular, central nervous system, and metabolic disorder trials. Moreover, due to the regulatory and operational requirements brought about by the COVID-19 pandemic, COVID-19 drug trials were the most likely to use remote drug delivery and remote nursing [41]. The research finds that dermatology and women’s health trials have most often incorporated ePROs, eCOAs, or eConsent. It is noted that the complexity of disease may limit the uptake of such components in oncology trials. Furthermore, data from eCOA may be less important for certain therapy areas, such as cardiovascular and metabolic disorders, that are more concerned with physiological measurements as key endpoints rather than reported outcomes [40]. This highlights a key point alluding to the quote “just because you can, doesn’t mean you should.” Even though a DCT element may be easily incorporated into a trial, the appropriateness to do so depends on the value it creates for the system.

Demands and pressures imposed by DCT solutions may be more aligned with certain attributes, thus leading to fewer (and less pronounced) pain points. For example, the therapeutic area and the types of assessments required for the trial are two critical constraints. Degenerative conditions whereby travel for even short distances is especially burdensome [42] or areas such as stroke management, where patients can manage their disease condition relatively easily, and dermatology, in which telemedicine (and video consultation) is suitable and already well-utilized [39], may be most appropriate for DCT solutions. Similarly, sleep studies conducted at home can provide more informative data and better facilitate patient preferences [43]. Such studies may be good candidates for the early adoption of most DCT elements. They can also pave the way for other indications by exemplifying the implementation processes and lessons learned.

Clinical trials in oncology and infectious diseases, on the other hand, in which the safety of the investigational drug is not well characterized and require tests that can only be performed in medical facilities (e.g., magnetic resonance imaging) [44] are unfavorable candidates for completeFootnote 6 decentralization. In these cases, DCTs should be treated as one of the many resources that drug development stakeholders can add to their toolbox, and the decisions in choosing the right DCT elements for a hybrid trial approach become paramount.

Sites and sponsors will also consider the operational requirements of the study (e.g., dosing frequency, method of administration, investigational drug storage requirements, to name a few) as well as whether there exists appropriate and validated technology and if the infrastructure is (or can easily be) established. Moreover, the regulatory environments in which DCTs will take place must be carefully evaluated. Different geographies may have different laws and regulations regarding telemedicine and direct-to-patient shipping of IMP and be more or less receptive to trial decentralization.

In thinking about how to scale and ensure the longevity of DCTs, it is crucial that appropriate solutions are deliberately selected and tailored to align with the specifics of the system prior to implementation. This contrasts the early phases of DCT use in the pandemic where, to a certain extent, solutions were “shoehorned” into existing systems [45]. A key aspect of this is a consideration of the partner ecosystem. Looking across the system, tensions may appear when the costs and benefits stemming from DCT implementation are not shared equally. One question that arises is whether the industry is stretched in two directions: offering patient choice versus the pursuit of operational excellence (i.e., executing trials faster and cheaper) [46]. The greater the alignment between such conflicting factors, the easier it is to ensure the sustainability of DCTs. This may necessitate building certain capabilities causing stakeholder roles to shift (e.g., consider, for example, the rising industry demand for data scientists) [45].

It is important to recognize that to minimize implementation challenges, trade-offs and pain points need to be recognized and mitigated. The systems approach presented in the paper offers stakeholders a way of holistically examining the impact of DCTs on the system: the implications for themselves and as well as on their partners. Each stakeholder needs to ask themselves a series of questions: (i) What problem do we want to solve?; e.g., increase participation in a clinical trial, reduce costs, speed up data collection, etc. (ii) Who are the stakeholders and partners? Which organizations could we approach? (iii) Why do we approach this problem using a DCT?; e.g., disease profile, patient profile, etc. (iv) How can we overcome the challenges? What are we good at, and what do we need to improve?

Conclusion

Although the many possibilities offered by DCTs underscore strong industry interest in trial decentralization, without detracting from the promise of DCTs, we urge caution in the widespread application of DCT solutions absent a thorough systems-oriented consideration of their impact on the clinical trial operating environment.

The current operating environments calls for heightened awareness and demand for solutions that can simplify the clinical development process for staff and patients. There is no doubt that DCTs will be a part of that effort. A recent survey found that most biopharma respondents viewed DCTs favorably [47]. However, how DCTs are implemented and incorporated into existing clinical research paradigms remains to be seen. At the current state of DCT adoption, many organizations, surveys, and roundtables reveal that customized hybrid trials are thought to be the most viable option [27, 32]. We believe a “one-size-fits-all” approach is inappropriate even as DCT adoption reaches maturity. As seen through the systems thinking framework, any such incorporation has wide-ranging impacts on key stakeholders and should be carefully considered. DCT solutions should be treated as one of the many tools that drug development stakeholders can add to their arsenal as they look for ways to make clinical research more relevant and accessible to a larger and more diverseFootnote 7 patient population.

To ensure that decentralization can enable diversity in clinical research, DCT solutions (and the resulting demands they place onto a diverse participant population) should be assessed to confirm that patients from diverse backgrounds are being included. Moreover, digital elements should be coupled with high-quality support and training to increase participants’ comfort and willingness to use technology. Importantly, clinical trials need to be designed to include accommodating options that meet a variety of patient preferences (and factor in various considerations such as participants’ socio-economic status). The resulting downstream impact (e.g., effect on data collection and data quality) of this level of customization should also be evaluated. Reinforced by a recent push from regulators [50, 51] to increase diversity in clinical testing, well-designed studies incorporating DCT solutions may offer a way to address under-representation in clinical research by removing some of the barriers associated with traditional clinical trials [10].

Systems thinking can assist decision-makers in assessing the system effects of DCTs. In choosing the best candidates and elements for DCT implementation, the framework may reveal different insights for different systems corresponding to their unique characteristics and, importantly, can be used to shed light on the appropriateness of DCT use and where there may be shortfalls. If a DCT solution leads to the emergence of more non-actionable pain points than the number of pain points it alleviates, one should be cautious in its steadfast acceptance and implementation. This approach can help the industry adopt solutions with higher chances of success and create best practices for implementation early on. This will pave the way for introducing potentially more complex elements and solutions by solving any technology and infrastructure-related issues upfront.

Recent trends indicate growing regulators’ commitment toward DCTs, laying the groundwork for regulatory guidance and oversight on the adoption of DCT [22]. Indeed, the COVID-19 pandemic has resulted in increased and quickly evolving regulatory acceptance of decentralized interventions. Furthermore, the pandemic has helped improve attitudes toward digital health solutions and has heightened stakeholder comfort levels with digital technologies, which can undoubtedly reinforce the continued adoption of DCTs where appropriate.

In conclusion, despite the enthusiasm surrounding the adoption of DCTs in clinical research, more robust research is needed to quantify the impact of DCTs empirically. The systems thinking framework provides a systematic and reiterative way to identify pain points and assess possible solutions through DCT implementation. A natural subsequent step is to devise new research that quantifies the impact of introducing DCT elements to various systems by considering the value generated for different stakeholders. To that end, we encourage and invite opportunities to collaborate with industry stakeholders to investigate a range of topics, ranging from mapping the types of operational models related to drug distribution and management, developing a scoring tool to systematically apply DCT elements and solutions to clinical trials for various conditions, to classifying the different types of devices used and examining their impact on patient experience.