Clinical Researcher—August 2023 (Volume 37, Issue 4)

TRIALS & TECHNOLOGY

Lauren Sutton, MBA; Ivy Altomare, MD; Sharifa Abubaker

Clinical research is the foundation of evidence-based medicine. Prospective clinical trials are the gold standard by which clinicians, medical centers, and life science companies assess the safety and efficacy of new interventions and treatments, expand their body of knowledge, and improve healthcare for millions of people.

However, for academic health centers, private health systems, and community clinics, the infrastructure needed to participate in clinical research is far from trivial. Identifying eligible patients, obtaining consent, executing the study, capturing data, and complying with all reporting and regulatory obligations take time and vital resources away from other important responsibilities at the site.

That’s where new clinical research technology comes in. It has the potential to radically simplify the way clinical trials are run, automate data collection, improve data accuracy and completeness, and facilitate essential monitoring functions. With the right processes, success measures, and feedback loops in place, technology can substantially reduce the operational burden associated with running a clinical trial.

As Dame Sally Davies, former Chief Medical Officer and Chief Scientific Adviser at the U.K. Department of Health, noted in a recent interview, “We’ve got to make sure that everyone around the world has access to the health benefits of data and digital technology.”{1}

To accelerate that transition, we propose an implementation framework based on years of hands-on experience that sites of all sizes can use to evaluate and integrate new clinical research technology into their workflows.

Why Now?

Selecting the right tech to assist and streamline operations is a top priority for busy clinical research sites, but it’s become more critical today for three key reasons:

Volume of Studies—The number of new clinical trials grows every year. ClinicalTrials.gov, the online database run by the National Institutes of Health (NIH) in the U.S., listed twice as many new studies in 2022 as it did 10 years earlier.{2} As of July 2023, it showed 60,000 trials in active recruitment (nearly 20,000 in oncology alone), more than a third of which were set in the U.S. To provide more therapeutic options to their patients, some sites today are participating in dozens, even hundreds of clinical trials at a time. Managing so many concurrent studies without the right technology is time consuming, costly, and prone to errors.

Increased Complexity—Not only are clinical trials growing in volume, they’re growing in complexity. According to the Tufts Center for the Study of Drug Development (CSDD), a typical late-stage trial involves more than 100 sites and the collection of 3.5 million datapoints—three times more than 10 years ago.{3} According to CSDD director Ken Getz, “What we’re seeing is the consequence of biopharma companies engaging in more ambitious and customized drug development activity that targets a growing number of rare diseases, stratifies participant subgroups using biomarker and genetic data, and relies on more structured and unstructured patient data from a larger number of sources.”

High Staff Turnover—The “Great Resignation” hasn’t spared the clinical research sector. Healthcare workers are quitting in record numbers—especially workers with clinical trial experience—and it can take a full year to get new staff up to speed.{4} Sites are forced to learn new technologies while simultaneously trying to recruit and maintain qualified, high-performing talent. This is incredibly hard to do. In a recent WCG survey of 500 research sites, staff retention was cited as a top concern by 63% of respondents, well ahead of patient recruitment and enrollment (48%).{5}

These forces contribute to major inefficiencies in the site-sponsor relationship. Despite the widespread use of electronic data capture (EDC) systems, study data entry remains cumbersome and time-consuming. According to a recent survey of clinical operations professionals, 75% still wrestle with manual processes and 58% with speed, visibility, and study oversight.{6}

Technology can alleviate these problems, but sites today are often bombarded with pitches from multiple software providers, and the solutions they sometimes rush to install aren’t always a good fit. In its 2022 State of Healthcare survey, HIMSS noted that a third of clinicians struggle with a lack of proper training and clear communication about the tools they’re asked to use, and for 37% of them, those tools don’t fit their existing clinical workflow.{7}

Criteria to Consider Before Adopting New Trial Technology

There’s a shift in the industry toward empowering sites to make their own tech investment decisions. “It’s time for [contract research organizations] and other sponsor organizations to stop imposing their view on the data and embrace technologies that are in sync with the way sites are generating data—whether it gets created in a device, a lab, or through manual entry,” says Hugh Levaux, former CEO/co-founder of Protocol First and current vice president for clinical research at Flatiron Health.

That’s good news for sites currently juggling with dozens of sponsor-specific applications, but now that they’re in the driver’s seat, how should they go about vetting the new tech options available to them?

We’ve identified five key areas that site leaders should focus on as they consider adopting a new tech solution (see Table 1). Each criterium comes with a set of questions for the technology provider or sponsor making the solution available at the site.

Table 1: Technology Adoption Criteria and Relevant Questions for Study Site Leaders

Technology Adoption Criteria	Relevant Questions
Performance	What specific gains will the new solution unlock at our site? How does it compare to competitors’ solutions, and how viable is the company offering it? Will it benefit one study or multiple studies? One or multiple sponsors? What’s the solution’s expected return on investment? What’s the basis for that calculation?
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Reliability	What’s the solution’s uptime, and how well does it scale? How well is it supported, how often is it updated, and what’s involved in those updates? What data quality monitoring and validation options are offered? Does it involve data streams outside the site’s control? How recent are those data, and how often are they refreshed?
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Compatibility	How does the solution fit with our existing tech stack? How does it integrate with our existing workflow? Does it help our site connect with sponsors more efficiently? Does it produce data in Study Data Tabulation Model format?
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Compliance	What are our remote monitoring obligations? Does the solution offer secure remote document exchange? Is it compliant with HIPAA, GDPR, Title 21 CFR Part 11, and other regulations? Are there other compliance risks involved, both in the U.S. and elsewhere?
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Training	How easy is it to use the solution? What steps are involved in installing it? Who needs to be trained on the new technology? How long does the training take, and what ongoing support will we get from the vendor and sponsor?

Asking the right questions up front can save a lot of aggravation down the road.

From Adoption to Implementation

Selecting the right technology is crucial, but it’s only a portion of the battle. It still needs to be installed, endorsed by leadership, and embraced by users. Anyone who’s ever lived through a corporate-mandated cloud migration will attest to how difficult change can be if it’s not carefully orchestrated.

There are many different ways to accomplish change management effectively, from Kotter’s 8-Steps to McKinsey’s 7-S model. ACMP and Prosci are excellent resources for change management strategies and techniques in general, and ACRP offers great insights for clinical research coordinators (CRCs) and other research professionals looking for best practices in the clinical research sector.

In our experience at Flatiron Health, we’ve noticed that successful site implementations tend to excel in a variety of areas (see Table 2):

Table 2: Change Management Steps and Why They are Crucial

Change Management Step	Why it’s Crucial	Example
Scope Definition	What specific functions is the new technology going to replace and/or impact? It’s absolutely crucial to manage expectations, and that means sizing up the project and defining its boundaries first.	Let’s take a hypothetical example: A practice is considering the deployment of a new electronic health record (EHR)-to-EDC connector to replace manual data entry for certain study data elements related to oncology studies at the site, starting in January 2024.
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Disruption Assessment	How is the new tool going to affect existing workflows? You need to map the new workflow against the old to quantify the impact and identify potential workflow gaps.	The new tool will save time by facilitating capture of unstructured data via EHR-embedded study specific forms, but it will require changes to the existing workflow of adverse event entry for study patients at the point of care.
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Benefits Communication	What breakthroughs are you expecting with the new tool? Communicate benefits early and in a language that all stakeholders can easily understand.	The site expects significant reductions in data entry time and 100% elimination of transcription errors thanks to automated EHR-to-EDC data transfer.
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Staff Training and Support	What will it take to train the staff and get them to embrace the new tool? Develop a pathway that makes sense, with clear timelines and full support from internal and external power users.	Training, robust knowledge management content, and comprehensive onboarding support will be provided by the vendor to the site’s CRCs and designated power users for the first six months. Other staff training to take place on a rolling basis and by therapeutic specialty.
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Tiered Deployment	What pilot study would best demonstrate the tool’s potential? Reach for small, quick victories to prove value and ease concerns.	The site will first implement the new EHR-to-EDC tool for half of subjects on one Phase I study.
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Success Messaging	What are the results of the pilot study, and what will the next steps be? Broadcast your success early and often to secure continued internal funding and support for the next phase in the tool’s deployment.	The site reduced the number of queries and met all data entry deadlines without the need for staff overtime. The next phase over the next six months will be to deploy the tool across all possible studies and expand training to five partner sites.

Onward and Upward

Clinical research sites have relied on technology for years to deliver optimal care to their patients, including digital tools that have been instrumental to help them manage their clinical research programs. However, many site leaders find it difficult to balance the growing needs of their clinical research operations with the disruptions associated with the introduction of new technology into their existing workflows.

We hope the implementation framework discussed in this article can guide clinical research teams and other stakeholders in their technology selection, adoption, and deployment processes in order to fully leverage the immense benefits offered by modern innovations.