White Paper

Clinical Trials & Research
October 6, 2022


Empowering study teams to complete high-impact work with more complete data


The traditional process for clinical trials and research—centralized study designs with episodic data collection—is historically time-consuming and often results in underpowered studies. Challenges in this process include inefficiencies in conventional methods of recruitment and screening, which limit the availability of potential participant populations and result in high attrition rates. Additionally, traditional laborious participant engagement and retention practices are immensely taxing on staff resources, and often yield data that lack the breadth and accessibility required to meaningfully impact study results. 

These recruitment, engagement, and data collection challenges ultimately lead to higher failure rates of clinical trials and research. Digital clinical trial and research (DCTR) platforms help alleviate these hurdles to success through enabling decentralized study models and interacting with participants during their daily routines. By removing geographic barriers to participation, streamlining project workflows, and increasing the breadth of the real-world data, DCTR technology allows study teams to achieve higher quality, higher impact results from every project.


Conventional clinical trials are long, inefficient, and burdensome
Traditional clinical study designs centralized around physical, brick-and-mortar trial sites typically have episodic, static, and often in-clinic data collection that is burdensome for participants and study staff. As a result, these conventional methods have high rates of failure to collect sufficient evidence. A 2016 evaluation of phase II clinical trial success rates found that 70% of trials are unsuccessful, despite 50% of those failed trials being considered “confirmatory”—that is, trials that confirm how well a new treatment works. [9] Frequently cited obstacles to clinical trials and research include lengthy durations, challenges in participant recruitment and retention, and overall burden on staff. [3]

participants and dataAdministrative staff duties as part of traditional clinical study designs include a myriad of activities, most notably participant recruitment, screening, scheduling, engagement, and follow-up. As a result, the burden largely falls on study staff to escort a participant throughout their journey. A high-touch approach—where staff and participants have frequent personal interactions—can be beneficial for cultivating a positive participant experience. However, this approach is time-consuming, difficult to scale, and potentially limited in the scope and specificity of recruitment.

Digital clinical trial and research (DCTR) platforms as a solution
DCTR platforms alleviate many of the conventional challenges associated with participant recruitment and data collection. Removing the need to rely on specific clinic research sites, for example, allows for a marked expansion of the participant pool. Expanding the participant pool facilitates reaching recruitment targets and lessens the need for staff to over-enroll.

Digital solutions also enable the collection of more complete, contextual data in a decentralized and adaptive clinical study design. Reliable collection of real-world data through these solutions can be accomplished by surveys and various digital health technologies. DCTR platforms easily enable connection to wearable devices and electronic health records, which are robust datasets frequently inaccessible in conventional clinical study designs. [8]

DCTR platforms can further alleviate challenges in conventional clinical studies by reinforcing compliance of study tasks through targeted automated reminders. In general, the technology platform can automate many of the activities traditionally completed by study staff, allowing reallocation of personnel time to higher-value activities. [5]

Ultimately, employing DCTR technology provides more complete data while enabling study staff to conduct high-value activities, resulting in higher quality, more impactful research.

Improving recruitment and screening

Participant recruitment and screening for eligibility are traditionally inefficient processes that require a significant amount of time. Trial failures are often attributed to recruitment and screening issues—90% of studies end up doubling their recruitment timelines after launch to reach their enrollment targets, and 50% of trials aren’t completed as a result of insufficient enrollment. [3, 10, 13] To illustrate the impact of these issues, Advarra recently summarized the results of a “leaky pipe” analysis performed by Clinical Performance Partners, Inc.

The analysis demonstrates that for an average study, of all known and available potential participants:


of people are pre-screen qualified


of those qualified are consented and further screened


of those further screened are randomized for the study


of those randomized will drop out

Ultimately, this leaky pipe yields only 7% of known and available potential participants that complete a study, where the majority of the “leakiness” occurs prior to participant randomization, in the recruitment and screening phase. [11]

CommutingReduce participant travel burden
Perceived participant burden, including travel and financial cost to participate, contributes to screening failures and loss of potential participants. This results in extended trial timelines and often requires staff to over-recruit in anticipation of high attrition rates. In particular, burden related to travel has a large impact on study sample diversity.

A recent investigation by Sanofi found that 70% of potential participants live at least two hours away from their nearest study site. [12]. In addition, clinical trial and research sites are frequently selected based on investigator location (e.g., affiliation with local academic medical center) rather than communities that suffer disproportionately and would benefit the most.

DCTR platforms enable low lift, web-based recruitment and screening methods that not only reduce staff burden but further support an “anyone, anywhere” model of participation. With a decentralized study design, access to a breadth of outreach methods—social media posts, automated email campaigns, QR codes posted in popular community locations, public websites, and more—expand the reach of a clinical research study.

By removing location barriers and performing multi-channel outreach, studies may achieve more diverse participant populations and more generalizable results while reducing recruitment time. Automated, electronic screening methods also free up staff time by enabling participants to complete screening surveys remotely on their own time.

Screening screenEnhance recruitment efficiency and decrease screening failures
Further, these screening methods increase recruitment efficiency and limit screening failures with sophisticated branching logic implemented in the surveys that maximizes identification of eligible participants. This branching logic also enables powerful precision recruitment which makes it significantly easier to target very specific cohorts of patients, especially in multi-arm studies. Alleviating the burden on staff to perform more repetitive tasks like pre-screening ultimately allows their efforts to be redirected toward more complex tasks.

Increasing participant engagement and retention

Beyond recruitment and screening, participant follow-up and engagement is consistently noted as a substantial burden on clinical trial and research professionals. Scientifically rigorous analysis of clinical data requires the data to be as complete and representative of all protocol elements as possible. To achieve this, study staff spend large amounts of resources on ensuring that participants complete all study tasks and reliably adhere to the study design. Whether completing follow-up visits, phone calls, or other outreach activities, engagement and retention activities monopolize staff time, particularly during longitudinal studies.

Save time with automations and notificationsAutomation screen
DCTR platforms can increase efficiencies in time allocation and prioritization. Specifically, this technology can relieve a significant portion of the participant engagement and retention burden on staff through automation of survey delivery and adherence notifications.

Automations and notifications can have a profound impact on study staff time. Using a robust rules engine, DCTR platforms can increase task completion without requiring any interaction with staff. These rules engines, using the status of a task (i.e., completed/not completed), can send SMS, push notifications, or email reminders to participants in the absence of trial personnel monitoring individual participant journeys.

Motivate participants with dashboards & gamification
Personalized participant dashboards and reward systems further enhance engagement and retention practices by providing motivation to the participant. Dashboards can help participants reach particular goals, either self-identified or predetermined. Those dashboards that track a participant’s progress can facilitate gamification of the participant experience and increase understanding of study expectations.

In addition, DCTR technology can facilitate more tangible encouragement to participants by automatically triggering delivery of appropriate incentives based on designated thresholds. Return of information is one such form of tangible benefit. Examples of these benefits could include:

  • permission to keep a smartwatch or fitness tracker provided for the study,
  • returning the results of a participant’s genetic ancestry report for studies collecting biosamples for DNA, and
  • providing educational resources for their participants.

Ultimately, providing incentives, returning results, or sharing resources with participants encourages them to stay involved with the study.

Overall, through automation of task reminders and personalized engagement with dashboards, staff are able to redirect their efforts to participants that may need extra assistance or to other components of the study protocol.

Obtaining real-world data (ePROs, wearables, EHR)

Traditional clinical study designs are limited to episodic data collection that lacks breadth. In many cases, valuable data from wearable devices, electronic health records (EHR), and contextualized patient-reported outcomes (PROs) are altogether inaccessible in conventional study models or limited to information acquired through expensive contracting with payers, providers, or other organizations. This conventional, confined dataset ultimately limits data analysis and the potential impact of the study results.

Access novel, broader datasetsData
DCTR technology unlocks a broader set of data that can be participant-mediated and efficiently accessed throughout the duration of a study. EHR and wearable devices each provide a particularly robust set of clinical data that results in a more holistic digital phenotype.

Information additionally shared through electronic collections of PROs (ePROs) help fill in gaps allowing for a multi-modal approach in data collection. Participants can login and connect their wearable devices and EHR to the DCTR platform—providing data from multiple sources—and submit their data to the study. Collating these data in the DCTR platform allows it to serve as a personal health record, which can also facilitate participant retention.

Improve data accuracy with digitally collected EMAs
ePROS can also enhance a study’s dataset by providing temporal context to the information, commonly assessed through ecological momentary assessments (EMAs). Participant responses to EMAs are impacted less by recall bias than conventionally collected answers, as they are evaluated in the moment and can be contextualized by supplemental data like that derived from wearable devices.

Gain immediate access to actionable data
The value of ePROs, in addition to data from wearable devices and EHR, is further increased by the accessibility of the data. Traditional episodic data collection delays the accessibility of the information, often relying on transcription of the data or integration steps before it becomes available to the study team for use.

The wealth of data collected through DCTR technology is immediately accessible, however, and the participant can elect to share data from a multitude of sources through a decentralized study model. These result in the potential for the data to inform the study as it progresses rather than solely being available for analysis at the end of the study.

Eliminate the need for source data verification
Beyond breadth and accessibility of data, traditional clinical study designs require extensive source data verification (SDV). This process is typically conducted during periodic site monitoring visits, in which data for analysis is confirmed to accurately reflect the data collected at the clinic site. Site monitoring visits to accomplish this process require significant dedicated staff time to complete. [3, 10]

DCTR platforms collect ready-to-analyze participant-provided information directly from the source, thereby greatly reducing or eliminating the need for SDV. This direct-from-the-source data collection method improves data quality by reducing inefficiencies and inaccuracies associated with transcription of data from paper to electronic records.

Ultimately, DCTR technology provides more complete real-world data while enabling study staff to direct their efforts toward high-value activities.


Conventional clinical trials and research studies that rely on traditional, isolated recruitment and data collection methods are plagued by long timelines, inefficient recruitment and screening procedures, time-consuming participant follow-up and engagement, and incomplete datasets. DCTR platforms alleviate these obstacles to study success by enabling a decentralized clinical study design.

Digital recruitment and automated screening methods are efficient and low-lift for staff, and expand the reach of a study to a larger potential participant population. DCTR platforms also relieve staff from spending excessive amounts of time on participant follow-up and engagement by automating participant nudges and facilitating engagement with dashboards and rewards. Finally, with efficient, easily enabled real-world data collection, DCTR platforms increase the quality of datasets and reduce the need for SDV. These advantages ultimately enable study teams to accomplish high impact, high value research with more complete data.


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  2. Dorsey ER, Kluger B, Lipset CH. “The New Normal in Clinical Trials: Decentralized Studies.” Ann Neurol. 2020; 88(5):863-866.

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