Strategizing And Implementing Your Clinical Trial Technologies
By Ellie Epperson and Laurie Stone, Clarkston Consulting

Clinical trials are becoming increasingly technologically savvy, with sponsors and sites integrating technologies such as electronic clinical outcome assessments (eCOAs), electronic patient reported outcomes (ePROs), and digital health technologies (DHTs). While each of these technologies has the capability to revolutionize both patient experience and data collection, they also present a unique set of challenges for clinical trial teams — challenges that can be mitigated with a proper implementation plan.
Below, we outline common uses and challenges of these new technologies as well as how a proper implementation strategy can eliminate some of the greater obstacles.
Benefits Of Clinical Trial Technologies
eCOAs, ePROs, and DHTs offer several key benefits to clinical trials. eCOAs and ePROs have increasingly been the standard for clinical outcome assessments over the past decade as the benefits are hard to ignore. They offer improved data accuracy, reduced errors in data collection, and an overall streamlined trial flow. When smartphones, tablets, and wearable technologies became increasingly popular, eCOAs and ePROs adapted to become even more accessible and user-friendly. The shift toward patient-centric clinical trials, along with the decentralized approach, accelerated the demand for digital solutions like eCOAs and ePROs as sponsors recognized the value of real-time data capture for the clinical team and patients alike.
Today, eCOAs are no longer considered radical but rather are the widely accepted standard for collecting clinical outcome assessments. Their success has paved the way for a broader adoption of DHTs in clinical research. DHTs can include wearable devices, remote sensors, smart cardiac scales, and vital sign patches. The advantages of DHTs are similar to those of eCOAs and ePROs —improved data accuracy and volume and an overall increasing patient-centric approach to trial design. DHTs can collect unparalleled amounts of data as they are constantly collecting and tracking patient vitals and information. Furthermore, as clinical trials are becoming increasingly decentralized, DHTs can offer remote data collection to further reduce the need for site visits, enhancing the patient experience.
The benefits of these trial technologies are clear, and many sponsors understand the need to move toward a digital enterprise.1 However, they are often unsure of what to look for with a new digital platform, how to best align features with study requirements, and the necessary training and support to ensure a seamless user experience.
Often, sponsors underestimate the time and planning needed to correctly implement these new clinical technologies. Without proper management and planning, there are added risks like unexpected delays, patient dissatisfaction, staff frustration, and unnecessary costs. Luckily, a strong implementation strategy can mitigate most, if not all, of these risks.
Planning Your Digital Strategy
A digital strategy first begins with conceptual planning, as this will inform what digital health technologies are most applicable for a given trial. This includes identifying a clinical concept of interest at the participant level. The next step is to define the characteristics that the trial participant will experience and report upon, as some characteristics lend themselves to digital technologies more easily than others. For example, impairments of motor function, gait, or balance can be easily measured via body-worn sensors such as accelerometers, gyroscopes, and magnetometers.2 However, internal symptoms such as gastrointestinal symptoms may be more difficult to measure via sensor-based methodology and may be better suited for direct patient reports, such as via questionnaire or ePRO.
While DHTs offer new ways to engage with patients and clinical data, there are specific cases where usage makes sense. While these technologies can offer new forms of insights, the data is ultimately useless if the patients — or administrators — are unable to properly interact with the devices or forms. At times, the anticipated cost and burden of educating patients and staff about the devices is not worth the benefits.
Consider some of the following questions when beginning to think about incorporating digital technologies:
- Patients: Would adding DHT-derived measures increase the overall burden on a participant? What is the anticipated compliance? Is there any existing data on participant compliance with a particular device in this specific population? Can the study participants manage the technologies, including battery charging, data synchronization, and device usage?
- Clinical Team: Does the clinical team have any prior knowledge of a given technology? If not, what is the anticipated cost, both financially and timewise, to educate them?
- Data Management: What kind of statistical tools and methodologies are available? Does your data management team have any prior experience working with data sets this large?
In general, it is best practice to utilize DHTs in non-interventional trials or early phases, where it is possible to pilot on a small scale and receive regular feedback from multiple stakeholders.
Let’s consider this use case:
A biotech company partners with an academic institution to research how brain health disorders impact college students ages 18–22. They align on a clinical concept: an observational study among college students to identify baseline characteristics and digital biomarkers predictive of mood and anxiety disorder development. The data to be collected includes periodic surveys done by students as well as university-sponsored student health services data. However, they are also interested in greater quantities of data capture. This use case is a great candidate for DHTs.
A DHT, such as a smartphone-based application that collects biometric, physiological, and behavioral data, could be a great option to passively collect more information on the study for students. Additionally, the application would leverage symptom patterns using machine learning (ML) algorithms. When considering the patient population (young adults with a high working knowledge of technology), the clinical setup (an observational study), and available data management (a build-out ML algorithm), the sponsors determined this is an excellent use case for advanced DHTs and moved forward with usability testing and digital application selection.
Implementation Strategy
If you’ve decided that it is in fact useful to use digital technologies, the next step in a proper implementation strategy varies based on the type of technology. While eCOAs, ePROs, and DHTs have some similarities, the operational functionality varies widely.
While the clinical trial landscape has somewhat mastered eCOAs and ePROs, the advent of further digital health technologies brings a unique set of challenges — one that many trials may be ill-equipped to face. However, when planned for correctly, DHTs can not only make trials easier but also offer a new way to interact with trial data and patients. DHTs require a whole different level of preparation, including SOPs, tech support, experience with clinical trials, institutional review board (IRB) submissions, and data privacy issues.
Beyond learning3 the best use cases for each, the general implementation strategies for eCOAs, ePROs, and DHTs are similar. Below are the general steps.
1. Early Assessment
Early assessment is paramount to the successful implementation of all clinical technologies. It’s crucial to understand if and which clinical trial technology is correct for a given trial, but this assessment must happen early in the clinical timeline. When assessing the proper implementation, think of the population, technical and performance specifications, and any risks.
Population
To successfully implement trial technologies, consider the diverse characteristics of trial participants.4 Think of things like education levels, language preferences, age groups, and the physical conditions of participants. Additionally, consider the technical aptitude of the trial populations to ensure that participants can effectively use the chosen DHT for the trial’s intended purpose.
Specifications
Determine the minimum technical and performance specifications, including the operating system, storage capabilities, and sensors to be used in the clinical investigation. Additionally, flexibility is key in this stage of the implementation. Sponsors should stay aware and open to incorporating new models of versions of DHTs, eCOAs, and ePROs in the trial, provided they meet the established technical and performance specifications.
Risks
Identify all potential implementation risks, for example, challenges in licensing, available translations, IRB/EC requirements. For each risk, come up with a mitigation plan or strategy. Some of these will be resolved via vendor selection, while some are inherent risks of clinical work. Regardless, identifying potential obstacles early will ensure that clinical technologies do not alter clinical timelines.
2. Create an Implementation Plan
Once you have successfully thought through the target population, the technical specifications, and major risks of a given technology, it is time to create an actual implementation plan. Define the baseline project plan across service providers that will be used to govern technology steps, map out all key deliverables, and highlight key dependencies between service providers.
Tip: If you’re unsure where to begin in your implementation plan, it can be helpful to start at the end and work backward to ensure you’re always working toward your final goal of first patient in.
Use this time to define how you will track success of the given technology. How will you know it’s working as intended? You can use the planning process to define key performance indicators (KPIs). An example could be the data capture accuracy rate. This will measure the number of accurate data points over the total data points. To define success, you could say a KPI of an ePRO tool is an accuracy rate of over 95%.
Other relevant KPIs for technology in clinical trials could be system uptime/downtime, data transmission success rate, participant compliance rate, or general data timelines. Any of these ensure the technology supports the quality and efficiency of the overall clinical trial.
3. Execute the Plan
Once you have created an implementation plan, all that is left to do is execute the plan throughout the trial. If you have properly assessed and planned your technology early, the actual execution should be the easiest part of the process. Remember, any form of health technology is meant to improve the clinical trial for both the patient and the clinical team, not hinder it.
Throughout the execution, it’s important to ensure the technology is functioning correctly according to the predefined KPIs. If one of the KPIs drops, it could indicate a significant issue and could threaten the study as a whole. For example, if the data transmission success rate, or the percentage of data that is successfully sent to a central system from a device, falls to 70% (below a 97% target), that could significantly hinder a clinical trial. First, the clinical team should attempt to identify the immediate issue. Any issue could be due to software, user error, or external factors. Additionally, the team should assess the impact on the trial data, timeline, and participants.
This is where a strong plan comes into place — if planned correctly, the clinical team should have corrective action strategies to implement to restore performance of a given technology. As you move throughout the plan, it’s important to highlight pitfalls (as noted above in the implementation strategy) you should take note of, as well as their corresponding corrective and preventive actions.
Moving Forward
While the future of digital health technologies is exciting, there are still lessons to learn in the field. From compliance to training time and costs and participant burden, digital health technologies come with their fair share of burdens. However, with the correct implementation plan and partners, you can eliminate or mitigate many of these obstacles to ensure digital health technologies help to improve your clinical trial, not hinder it.
References
- Parks Murray, E. & Stone, L. (2024, April 24). Driving the Future of Clinical Research: Key Takeaways from MAGI 2024. https://clarkstonconsulting.com/insights/driving-the-future-of-clinical-research/
- FitzGerald J.J., Zhongjiao, L., Jareonsettasin, P., & Antoniades, C.A. (2018, April 10). Quantifying Motor Impairment in Movement Disorders. https://doi.org/10.3389/fnins.2018.00202
- FitzGerald J.J., Zhongjiao, L., Jareonsettasin, P., & Antoniades, C.A. (2018, April 10). Quantifying Motor Impairment in Movement Disorders. https://doi.org/10.3389/fnins.2018.00202
- Parks Murray, E. & Stone, L. (2024, January 19). Top 3 Reasons Why You Need to Incorporate DEI into Clinical Trials Today. https://clarkstonconsulting.com/insights/why-you-need-to-incorporate-dei-into-clinical-trials/
About The Authors:
Ellie Epperson, an associate consultant at Clarkston Consulting, leverages her background in public policy and political science to help life sciences clients understand and navigate the complex regulatory and geopolitical landscape of the industry.
Laurie Stone, director at Clarkston Consulting, has more than 20 years of experience in clinical operations across different stages of development, providing expertise in quality, management, and compliance in the biotech, pharma, and medical device industries.