During a global pandemic—one that has limited mobility and face-to-face interaction—there is no time like the present to develop and implement digital solutions. We are seeing it in how we shop for groceries, how we visit the doctor and how we communicate with colleagues and loved ones. The pandemic has affected nearly every aspect of our day-to-day lives.
For researchers conducting clinical studies and their patients, this has been no exception. The challenges of operating traditional, site-based clinical trials are unlike anything we have ever experienced. The opportunity to move in a digital direction is no longer an interesting alternative to consider—it has become an imperative. Fortunately, we have newer research models to turn to in the form of hybrid and decentralized studies, which allow for the continuation of data collection and discovery at a distance.
To help clinical researchers get the guidance they need, we have constructed this white paper, which offers considerations and recommendations to consider when designing and implementing hybrid and decentralized studies. Our hope is that this can be a handy resource that makes getting a decentralized study up and running feel accessible and within reach. And once the study is on the ground, we offer direction on how to make your trial as effective as possible.
As in other arenas of life, the global pandemic has shown us that with innovation, remote methods for connection and efficiency are possible. We are seeing the adoption of technology at a pace we may have previously thought unimaginable.
At the end of the day, the success of a clinical study hinges on consistent patient participation and engagement. While digital alternatives are not a perfect substitute, we now have greater confidence that digital tools can enable trust and meaningful human connection.
A future with far-reaching use and acceptance of digital technology in clinical research is bright. The time to move is now and we are here to help.
The global pandemic has changed the imperative, acceptance and funding of digital medicine and therapeutics. Simultaneously, the design, execution and expectations of clinical studies may have forever changed, thanks in large part to the global health crisis. Before this year, the notion of hybrid and fully decentralized studies was a curiosity that was slowly gaining traction and appeal. Today, there is not a researcher or clinical professional who isn't asking how they can use digital technology to meet their workflow and protocol needs.
To help health professionals get the guidance they need, ZS invited a select number of professionals from the United States and Europe to reflect on the challenges commonly experienced and provide practical considerations when applying digital health solutions to decentralized clinical studies. ZS hosted virtual workshops in September and October of 2020 with global leaders in life sciences. We asked a simple question: What are the new and emerging real-world issues that practitioners need to consider as they plan, design and operationalize clinical studies? The virtual workshop, “Decentralized clinical studies: A time for transformation,” was a wide-ranging conversation that allowed for an open discussion to distill themes and practices useful to product developers, researchers, study coordinators and clinical practitioners in the growing world employing digital health tools. The themes that emerged from the workshops fell into two broad categories.
The first category, studies for digital medicine, offers considerations and recommendations for planning and executing an evidence generation roadmap toward the validation of digital products that will garner acceptance by clinical and payer incumbents. These recommendations are relevant to organizations working to improve the research and validation of digital therapeutics.
The second category, digital practices for decentralized clinical studies, pulls together the myriad recommendations and conversations regarding best practices for using digital tools, approaches and solutions to support decentralized clinical studies.
A few notes about this white paper: First, by no means is this meant as a comprehensive treatise on the issues and considerations that need to be addressed through the clinical study planning and execution process. That scope would fill two textbooks. Instead, the work here is presented simply as a lens into real practitioners’ issues in this pivotal time. The individuals who contributed to this work represent a broad array of organizations, with leading responsibilities in designing and running clinical studies for a diverse set of clinical and therapeutic areas. Their roles are also broad, focusing on clinical study design, clinical outcomes, clinical study technologies, data analytics, regulatory practices, data privacy and security.
The workshops focused on two major geographic areas: The September workshop brought together leaders from the U.S., while the October workshop involved practitioners from Europe. While we didn't seek to establish consensus between the two geographic groups in terms of themes, issues and considerations, there was far more agreement about what was important to consider than divergence of opinion.
When comparing the circumstances of the two geographic groups, there are differences in the covered markets, particularly related to the organization and role of payers. There are also differences with respect to how regulatory bodies are viewing digital. In some European markets, certain physicians are playing catch-up to the U.S. regarding digital acceptance. These differences are by no means universal. If anything, we appreciate that there is no such thing as a single view of Europe regarding digital health. Each country in the European Union has its own digital health adoption and diffusion profile. And like the rest of the world, things are changing rapidly.
Most of the contributors to this white paper recognize that digital health is at a watershed moment. COVID-19 has opened a door, but this is hopefully only a beginning to making clinical studies more inclusive and patient-centric. It is worth noting that the so-called “revolution in telehealth usage” touted through 2020 reached only a tiny percentage of the potential population. The shift toward the acceptance and use of digital health was built and structured based on changes that have been years in the making. It appears the rocket has launched.
Part 1 - Studies for digital medicine
Studies organized to test and validate digital products intended for diagnostic or therapeutic purposes.
- Make early decisions about product risk class.
- Plan with multiple stakeholders at the table.
- Plan for regulatory and commercial acceptance.
- Use standard methods, metrics and processes, as possible.
Part 2 - Digital practices for decentralized clinical studies
Using digital tools, approaches and solutions in decentralized clinical studies.
- Configure clinical study platforms for success.
- Design studies for decentralized enablement.
- Plan for clinical study endpoints.
- Spend adequate time on pre-study activities.
- Prepare for decentralized enrollment.
- Have a thoughtful engagement strategy.
- Involve clinical and study staff as part of the digital experience.
This first section examines the issues that emerged through the workshop relevant to designing and delivering studies organized to test and validate digital products intended for diagnostic or therapeutic purposes. The arena for testing digital medicine and therapeutic products is changing rapidly, with a growing focus on the quality of the evidence.
This change is being fueled by more stringent requirements from sponsors, payers, providers and regulatory agencies. For digital therapeutics to be acceptable, they must be tested, applying the same rigor used with traditional medications and therapies, showing them to be safe and effective. Also, sponsors need to invest in ongoing collection and analysis of product performance data and real-world evidence.
Digital health is a relatively new field and some startups have made missteps, spending money on studies that did not achieve their commercial goals. A lack of proper and holistic planning—not considering the end-to-end evidence strategy—hindered their ability to bring digital solutions to the market effectively.
Early in the evidence generation process, product innovators need to make critically important decisions that will affect how they move ahead with their evidence strategy. Determination about the risk class in which the digital health product is likely to be categorized ties to evidence strategy. Digital therapeutics and diagnostics require a much more intensive technical validation process than simpler digital health solutions.
Things to consider:
- Take a conservative approach
Is the software solution a medical device? And if so, in which class should it be placed? Digital medicine and therapeutic companies still in startup mode may believe that if their product is classified as a non-device or a low-risk device, it will be more suitable for commercial launch. But this belief may be shortsighted. Regulatory tripwires may slow adoption by providers and payers and may be a speed bump on the way to eventual commercialization.
Software and clinical decision support
FDA recognizes that the term “clinical decision support” or “CDS” is used broadly and in different ways, depending on the context. The FDA issued a draft guidance covering device CDS functions intended for patients, caregivers or HCPs that inform clinical management for serious and critical health care situations or conditions.
- Prepare for rigor
Regulators are actively working to improve how medical software solutions are classified per their safety and risk. At the same time, they are evolving the research requirements associated with different risk class products. There will likely be more stringent requirements in the coming years for validation research. Manufacturers who plan for the global deployment of solutions need to be prepared to meet the strictest requirements across geographies.
- Consider compliance and controls for evolving product platform components
Digital technologies that use algorithms pose interesting challenges for regulatory compliance and governance. These platform components may evolve and hopefully improve their performance over time, but as they do, it is incumbent upon regulators and developers to understand the impact on validation or revalidation of regulated software. It is expected that over the coming years, FDA and EU MDR guidance will evolve and clarify. Maintaining a continuous lens on regulatory bodies and decision-making is critical during this evolution.
Digital health solutions can’t be designed and developed in a vacuum, and neither can the planning for validation and efficacy testing. The strategy for validation needs to have upfront input from the clinicians and patients who will play a role in the commercial success of the product. You need to be selective about who to listen to, when to get their input and what questions to ask regarding the study and its design.
In Germany, on October 5, 2020, the Digital Healthcare Act (DVG) officially granted doctors in Germany permission to prescribe apps to their patients for the first time.
The DVG regulates that medical apps that are CE-marked as Class 1 and 2a low-risk medical devices can apply for “fast track” market entry in Germany. Digital health can now be prescribed by physicians and reimbursed by the statutory health insurance (GKV).
The DGV also regulates online video consultations. The information on an online video consultation can now also be given online during the video consultation itself—not prior to the appointment, as was previously the case.
Things to consider
- Identify the right stakeholders early on
Selecting and working with the appropriate subject-matter experts and key opinion leaders (KOLs) will help identify the critical factors needed to close gaps in the evidence-generation process. The voices of patients and advocates need to be included. This will allow for a more comprehensive and intentional approach to collecting the requisite evidence to demonstrate product success. Neglecting to include critical stakeholders upfront may result in misidentified endpoints, misaligned objectives or even rejected study results.
- Articulate a clear and focused value proposition
Key opinion leaders, subject-matter experts, patients and stakeholders are your sources for ensuring that the digital medicine solution and its intended value are clear and address the issues that are most important to users. This articulation of a value proposition should flow seamlessly between the users, the product, the study endpoints and the overall study design. Identifying misalignments early allows for time to pivot or to redesign parts of the approach without the cost and impact of late-stage realignment.
Types of stakeholders and questions to consider when
|Is the proposed digital medicine study…|
|End-users of a digital medicine solution (patients, physicians, other providers such as nurses, RDs, coaches)||
|Health economics and clinical outcomes: (key clinical experts, medical directors and regulatory experts)||
|Study operations and deployment (medical directors, hospital administrators, practitioners, clinical trial operations)||
|Risk and safety: (regulators, KOLs, clinicians, patients advocates)||
|Commercial viability: (payer organizations, sponsors and health systems)||
Unlike clinical trials to evaluate a drug, study plans for evaluating digital medicine solutions follow a research pattern from quality, safety and effectiveness, to real-world performance. Planning these studies can be tricky because they need to address usability, clinical effectiveness, safety and efficacy in real use. In developing a roadmap and strategy for these studies, planners need to consider what product claims will be necessary to garner clinicians’ attention and what product claims will be expected by information regulators and payers.
Things to consider:
1. Don't rush into research
Instead of rushing to start a scientific study, you should spend more time in the planning stage to ensure that the selected outcome measures are appropriate and acceptable. Additionally, you should take the time to plan how evidence will be used after it is generated. Ask yourself, “Where should evidence be published and what are the next steps that the organization should take following publication?” The organization must answer the question of how the evidence generated will lead to market acceptance and a commercial launch.
2. Involve governing bodies early on
With novel digital medicine solutions, it is crucial to begin laying the groundwork with regulators early to allow them to become familiar with the development program. Consider engaging them early and often to ask:
- What type and sources of data are needed?
- How much time is needed for intervention follow-up?
- What are the expectations for data collection, format and security?
Reaching out early to consult on questions in the “gray zone” can significantly affect timelines and therefore costs, as you develop digital solutions in support of clinical studies.
The FDA is supportive of the International Medical Device Regulators Forum (IMDRF), which sets forth a Medical Device Single AuditPilot Program to guide the industry with frameworks and processes for the use of digital solutions with wellness and medical purpose.
3. Work toward a focused reimbursement strategy
The studies supporting a digital medicine product need to be aligned with the collection of relevant data that payers care about. Otherwise, the solution will not scale appropriately or be accepted onto a preferred list for reimbursement. It is critical to focus on this strategy during the planning phase to ensure that the study aligns with the overall reimbursement strategy.
4. Plan for real-world evidence
Although you may achieve clinical efficacy evidence in a randomized clinical trial (RCT), only real-world evidence studies can unlock digital medicine’s actual value. Given the nature of digital products, actual engagement in real-world usage could vary enormously from a highly structured clinical trial. Therefore, generating real-world evidence becomes essential to help drive a digital medicine solution’s adoption and scalability.
Research on digital health products is changing rapidly, as the focus grows to ensure that there are standards for establishing endpoints and evidence-generation processes. Researchers, regulators and payers require quality standards to improve research integrity and interoperability across products.
Things to consider
1. Leverage existing standards whenever possible
Digital health is quickly evolving. There are often inconsistencies in how evidence is generated, even for solutions that are focusing on the same clinical area. It can be challenging to establish a comparative gold standard that will meet the acceptance criteria. Also, the endpoints acceptable to regulators may be different from what payers or patients care about. While there is an inclination to reinvent the wheel due to a lack of universally agreed upon standards in a given clinical field, it is incumbent upon researchers to fall back on accepted standards whenever possible.
2. Work toward new standards (in the absence of existing ones)
Leaders at our workshops expressed a strong interest in establishing new standards for improving the quality of digital health research and standardizing measures. Similar to how ISO standards have been adopted and used, new digital health standards can generate quality, replicable and repeatable approaches that can extend beyond geographic borders.
Participants at the workshop talked about possibilities: Using existing organizations in the digital health arena or creating a new entity that would bring together members from a consortium of organizations from across healthcare. The body might have a loose or tightly defined governance structure that would promulgate new standards and assume the ownership and authority to raise thresholds for evidence generation and validation.
3. Establish measures for engagement and expectations
It states the obvious, but patients’ engagement with digital medicine solutions is critical to successful validation and real-world adoption. Unlike pharmacokinetics, where dosing and mechanism of action (MOA) are built into the clinical study expectations, an equivalent notion is largely missing in digital therapeutics.
- Explore and establish standards for expected engagement.
- Establish acceptable outcome measures for success.
This section looks at the themes that emerged through the workshops relevant to using digital tools, approaches and solutions in decentralized clinical studies. Here we posit that COVID-19 has accelerated both the consideration for using digital health and telemedicine tools to support clinical studies and the acceptance of digital tools as a viable source for evidence collection.
As the COVID-19 pandemic has changed the healthcare research landscape, the acceptance and operationalization of hybrid and decentralized studies has gained an enormous amount of attention. Fundamental to successfully deploying a hybrid or fully decentralized clinical study is the use of telehealth tools. Patients participating in clinical studies, who are providing their patient-reported outcomes (PRO) and complying with medication-related protocols at home, need new communication channels to connect to clinical studies’ sites. Also, hybrid and decentralized clinical studies open the doors for collecting new biomarkers through wearable and companion devices that were not considered practical or fundamental to clinical studies when all interaction was site-based. In conjunction with mobile nursing, clinical studies powered with telemedicine can establish clinical study endpoints that were not possible before.
Of considerable interest across geographies is how digital tools are used to support clinical research during COVID-19. For many participants, particularly those considered at high risk of exposure, appearing in person at a clinical site for evidence collection proves nearly impossible. Decentralized monitoring of symptoms using telehealth applications can provide enough support for many studies to launch and continue, despite the limitations the pandemic has presented.
Throughout our discussions and across regions, we see a greater acceptance and willingness to use digital tools to support clinical research. For patients using a tool to check in and track symptoms and side effects (either actively or passively through a connected device), the digital space has offered accessibility and the opportunity to engage that may not have been otherwise available to them. For clinical study administrators, the digital space has enabled flexibility in recruitment, enrollment and data collection, leading to more comprehensive ranges of inclusion and reduced dropout rates.
Many participants of the workshops were eager to talk about how digital opportunities were affecting their current and future clinical study design and deployment.
As digital medicine solutions become more sophisticated, the primary and secondary endpoints collected will become more diverse. Also, real-world evidence on digital health products may involve the use of unstructured data—or data that needs to be transformed with artificial intelligence (AI), machine learning and data mining tools. These products and the platforms that collect and assemble data for research purposes need to support an ever-growing volume and diversity of data. A proper evaluation, selection and configuration of an evidence collection platform is paramount for the success of the study.
Things to consider
1. Distinguish clinical study data from digital medicine data
Everyone involved in clinical studies for digital medicine products must decide how to discriminate between data types. It is often necessary to pull the data apart in terms of separating a digital medicine application database from a clinical study database, as well as to think about how and when data is collected throughout a clinical study.
Consider how we make the intervention and control arm experience equivalent for participants within the primary and secondary endpoint collection experience.
2. Ensure clinical studies’ platforms comply with 21 CFR Part 11
The FDA’s regulation for electronic documentation and electronic signatures is foundational not only to the data architecture of a digital medicine product, but also to the collection of data used in trials for clinical research with those digital medicine solutions. Ensure that the vendor technologies you are using have been validated for 21 CFR Part 11, assuring sponsors and regulatory agencies that electronic records and signatures are being maintained in a manner that supports data integrity, security and compliance to all applicable regulations.
Clinical studies exist along a continuum ranging from 100% decentralized studies, requiring no clinical site activities or visits (allowing the patient to participate entirely from home), to those that are hybrid, still requiring some face-to-face interaction with a clinician or technician. The appropriate design of decentralized clinical studies should consider the population’s needs and limitations, the requirements for the clinical study (what data needs to be collected and how) and the available technologies. While it may be optimal for patients to participate in a fully decentralized clinical study, it may not be practical. However, hybrid clinical studies that can include some central site activity can be designed to allow patients to participate and engage in new ways—for example, through e-diaries, wearables and telemedicine visits. The technologies and expectations you select and enable from the outset will determine how well the trial meets the engagement goals and compliance requirements. For this reason, we suggest taking a holistic approach to decentralized clinical study design, considering the fit between people, goals and technology.
Things to consider
1. Understand the clinical study’s target population
In hybrid and decentralized clinical studies, digital technologies will be more readily accepted and used for specific populations than others. For this reason, it is vital to have a solid understanding of the needs, expectations and limitations of patients and determine how the technology can work for them. Digital technology allows for improved accessibility and less effort than in in-person collection. This is particularly true for patients who live long distances away, have busy lives or experience social anxiety.
- Work with patients and advocates to understand their needs, how their experience can be improved and how the stress of participation can be reduced through digital technology.
- Interpret findings from the conversations with patients and advocates and educating all stakeholders on what works and doesn’t work with the digital technology at hand.
2. Perform a holistic review of the study design
The “best” and “right” design and approach to a decentralized clinical study will differ by study. Decentralized studies offer more dimensions and optionality than traditional centralized ones. A holistic review of the clinical study design and assessment of risks and options is necessary before finalizing study plans to find the best fit for the goals you are trying to achieve. Consider technologies that can make the clinical study work for different patients who have different requirements, limitations and expectations.
3. Choose technologies that easily integrate with pre-existing routines
Technology used in digital health studies may be a source of disconnection between people. In these cases, the problem may be that the technology chosen is not designed to encourage and amplify the human experience and connection. The wrong technology can lead to a lost opportunity to engage the patient, retain them for the study duration and collect the needed evidence to complete the study.
- Choose clinical study technologies that excite people and that they want to use.
- Select telemedicine technologies that are simple to use and ready to go “out of the box.”
- Assemble technologies that allow patients to more faithfully and seamlessly provide meaningful input on the things that matter to them.
4. Leverage known standards and frameworks across regulatory bodies
In this fast-moving space, digital devices’ regulations and standards are evolving as rapidly as the software is being developed. With rules of classification in flux, keeping up to date with existing tools used to validate data generated during clinical studies is vital to maintaining the integrity, privacy and validity of data.
Clinical studies shine a spotlight on an area of people’s lives that they often do not want to emphasize: their illness or condition. In decentralized clinical studies, researchers need to consider how they will collect data in a way that minimizes undesired disruption of the patient’s daily habits. Some primary study endpoints are required, non-negotiable and not easily acquired through low-burden alternatives. Radiographic evaluations, biopsies, tumor measurements and the like are traditionally performed at brick-and-mortar sites. Clinical study planners need to carefully consider if there are realistic alternatives that can reduce patient burden.
Yet decentralized studies also offer exciting opportunities to employ tools that collect novel data that shine light on aspects of living with a condition. Carefully curated sensor devices can collect new and larger quantities of data for studies over an extended period, as patients go about their lives outside of the clinic. When deployed to all, this data can provide important self-care guidance to patients.
Things to consider
1. Consider new tools to capture new endpoints of interest
The ability to use new digital tools in clinical studies has opened the door for identifying novel endpoints. Digital biomarkers are objective, quantifiable and measurable when collected through digital devices such as wearables and sensors. The increasing availability of digital medicine solutions and clinically validated medical devices has also introduced new digital endpoints for consideration in clinical studies.
- Consider the growing landscape of medical-grade sensors and devices that can collect previously unavailable data.
- Consider the collective use of data to identify trends in behavior, progression and adoption to inform the future application.
2. Select novel endpoints that are meaningful to all stakeholders
In selecting the right endpoints for a clinical study, researchers will need to engage with regulatory and commercial stakeholders. When a study uses connected digital and sensor technologies, the selection process may not be straightforward. Endpoints that clinical experts, for example, ask for, may pose challenges for the patient population. Moving forward, striking a balance in choosing the right endpoints will be a challenge to overcome.
3. Know the local regulatory requirements to inform your clinical study design
Regulatory rules and requirements are central to any clinical study. The differences between geographies indicate that this space will continue to evolve to define acceptable evidence collection practices. There is more burden in the U.S. than ever to meet FDA and MDR regulatory requirements, including whether data sources themselves will meet regulatory restrictions.
Even after proper planning for success, there are some critical issues to consider before launching a clinical study using digital medicine technology.
Things to consider
1. Pre-test the technologies to use in the clinical study
Technologies that are going to be deployed in a study should be tested with smaller, healthier populations in pilot tests before being deployed to larger populations. With new technology, there are always unexpected issues. This is particularly true when dealing with populations that aren’t familiar with the technology. The cost of dealing with issues while a study is in progress is much higher than addressing those issues before the study starts.
2. Cover basic clinical study logistics
It may sound obvious, but basic study mechanics, such as planning for how a patient will be paid, ensuring that they are paid on time and providing simple and clear instructions about participation expectations throughout the study are fundamental to study operations and success.
- Work with contract research organizations (CROs) that have systems, playbooks, processes and approaches for managing clinical study operations, data transfer and an audit trail by adapting those systems for decentralized clinical studies.
- Use an operational checklist and pre-test when possible to address all operational constraints before engaging patients.
3. Focus on clinical study data integrity and privacy
Guidance from regulators on good clinical practice (GCP) for oversight and data integrity assessment in clinical studies is not new. With the advent of decentralized clinical studies, which rely on an ever-growing number of platforms and networked technologies for data collection and transmission, there is a new focus and added burden on sponsors.
Regulatory agencies have limited resources and are being asked to work under accelerated timelines to review applications. Adding to this, decentralized clinical studies often result in more sites over a broader geography, sometimes crossing between regulatory borders.
The challenge of ensuring appropriate audit trails, blinding and data management is complex. Sponsors need to work closely with vendors to validate their management practices and processes.
- Assess whether technology vendors meet standard requirements for information security and data privacy and protection processes.
- Focus on potential points of failure that have concerned regulators, including deficiencies with audit trails; poor data management leading to unintended unblinding; and concerns with the integrity, adequate privacy and security of data sourced from electronic health records (EHRs) or other sources.
Enrollment in any clinical study is often fraught with difficulty, making adequate and appropriate preparation critical. On a positive note, many researchers conducted studies that were organized for decentralized recruitment and enrollment during the COVID-19 pandemic. They found that by using email, SMS and web-based study portals as the preferred methods for enrollment in a study during the pandemic, they were able to expedite the arduous study enrollment process.
Things to consider
1. Build and maintain patient trust
Patients typically trust their physicians. During decentralized clinical studies, where face-to-face engagement with a clinician is less frequent, the bond of trust may weaken. The study coordinator maintains a critical role in providing a patient connection.
- Plan to have a specific study coordinator who is ideally an empathetic “people person” assigned to patients.
- At the start of a study using digital technologies, have the patient and personnel “field test” the technologies to build the experience of using the technology and engaging with a study coordinator at a distance.
2. Incorporate members of the care team
Studies are too often designed without considering the people in a patient’s support system and the roles they play in a patient’s medical journey. Study personnel may come and go, but other people in a patient’s care team may be constants. This support system might include the patient’s primary care provider, nurses and professional caregivers, in addition to family and other loved ones.
- Look for study engagement tools that allow for care team involvement.
- As patients enter the study, ask them to identify and formally invite their care team to be involved.
- Throughout the study, use engagement strategies and tactics to build on the strength of the care team.
3. Make clear how data is protected
The concern for how data will be collected, stored and used may or may not be top of mind for patients as they enroll in a clinical study, but any breach will harm the patient’s relationship with this and future studies.
- Be clear and upfront with patients about what data is being collected and how it’s being used in the study.
- Ensure that study personnel are trained and clear about the use of data and how to reinforce practices to maintain its privacy and protection.
- Choose study platforms that offer tools and approaches that increase transparency about data collection and privacy.
Decentralized clinical studies are designed so patients can participate and engage in the study outside of the traditional clinical site. This often means using e-diaries, wearables or complying with expected biomarker collection. Telemedicine tools have proven to be valuable for improving patient engagement and compliance with clinical study protocols and expectations. The technologies and expectations designed from the outset will determine how well the study does at meeting engagement, ensuring compliance and reducing dropout rates.
Things to consider
1. Build flexible engagement strategies
In any patient population, you will need to consider differences in demographics, technology literacy, health literacy and accessibility. Also, individual disease states impose limitations on patients’ ability to engage quickly in a decentralized clinical study from a distance. These differences require a flexible approach to ensuring that all patients, regardless of limitations, continue to engage in the study.
- Work with patients and advocacy groups during the development of the protocol to understand the range of patient needs and limitations to consider.
- Build a variety of engagement strategies that cover both the base case and potential limitations.
- Have a pre-testing pilot prior to a full-scale study launch to uncover issues and build in contingencies.
2. Consider patients’ changing needs
Patients who enter clinical studies are often challenged and buffeted by changes in their health, their functional limitations and issues in their social and personal lives. One fundamental difference in a human-centered approach to clinical studies is that it sees participants not just as “subjects in an experiment” but as human beings who need to be seen, heard and understood through the course of the study. They need to be offered accommodations and practical support as their lives and priorities shift. Without this support and accommodation, patients may feel unappreciated and become disengaged or at odds with the study.
- Leverage the advantages of hybrid designs to reduce the effort for patients. For example, consider constraints and potential solutions for making necessary site visits easier (closer to home, arranging transportation, etc.).
- Leverage in-person clinical staff as additional channels for patients. Have study personnel check in frequently with patients to determine whether there are needs, concerns or limitations that have changed.
In decentralized clinical studies, technology should not be a substitute for human involvement and connection. When designing digital studies, it is essential that patients come before the technology and the study’s design supports the patients’ variety of needs.
Things to consider
1. Maintain the human connection
In decentralized clinical studies, it’s vitally important to have someone in a key role who the patient knows and trusts. Giving patients the ability to easily contact the site administrator or study personnel is necessary to maintain the level of personal touch, empathy and connection that patients need and often feel in traditional clinical studies. Digital technology should support and enhance that human connection, allowing for on-demand and video connection between patients and people they know from the study.
- Deploy study technology that allows patients to contact and connect with study personnel assigned to them.
- Design for the human touch by building expectations into the protocol, expectations with the contract research organization (CRO) and training of study personnel.
- Based on the output from decentralized expert sessions, conducted in September and October 2020.
- Twenty-five industry experts and key opinion leaders contributed to the productions of this document.
- The views expressed in these written materials do not imply the endorsement of experts, speakers, moderators or names associated with brands or businesses.
- There were no monetary or in-kind incentives paid to the participating experts to produce and review these recommendations.
- All recommendations in this document will be publicly available. Use of the recommendations is encouraged with appropriate citation.