Clinical research is a cornerstone of our global healthcare ecosystem. More than ever, the public relies on advances in research to fuel therapies for diseases, both new and old. And—as the current pandemic has highlighted—when it comes to clinical trials, speed matters.
Fortunately, the industry has made some significant strides in recent years. To name just a few: the FDA has been more efficient at reviewing and approving drugs, digitization and availability of real-world evidence show significant promise in personalized medicine, and investments in technology have fostered a more patient-centric approach to designing and running clinical trials.
However, we still need to see major gains in overall clinical trial efficiency if we want to reduce costs and shorten clinical development timelines. Despite all the funds poured into clinical trial innovation, the largest source of clinical development delays—patient recruitment and enrollment—continues to stall the development of potentially effective new therapies.
of all clinical trials fail to meet their patient enrollment objectives
of research sites enroll one or fewer patients for a given trial
Actual enrollment timelines are nearly twice as long as planned timelines
Our industry has spent decades and many billions of dollars developing solutions to do something about these eye-popping statistics. Pharmaceutical sponsors have invested more in patient recruitment strategies that cast wider nets or leverage social, behavioral, and demographic data to target more patients; there are a number of companies that utilize increasingly sophisticated algorithms to engage and refer potential patients to sites; and several companies are beginning to leverage EHRs and AI to identify potential patients already connected to research sites. These solutions have been effective in solving parts of the problem, but we as an industry still have work to do to enroll the majority of trials rapidly and predictably.
To do that work, we need to start focusing on a piece of the puzzle that is just as critical as (and maybe more critical than) patient identification, but has been historically ignored.
When you take a look at the entire patient recruitment and patient enrollment funnel, several key activities—from patient identification, to intake, to pre-screening and screening—rely on research sites and research coordinators to carry them out. Yet these sites, and the research staff therein, have not been given the proper tools or technology to manage and track recruitment efficiently. In fact, our research shows that nearly 90% of clinical research sites still rely on paper and/or spreadsheets to manage this process. Only when patients approach randomization and enrollment do sites have access to tools and tech that aid in process management and data capture. (see fig. 1)
This asymmetry results in gaps in transparency, lost data, and—ultimately—a massive blind spot in clinical research: what’s happening with patients prior to randomization? This is exactly the type of problem we at Reify Health are beginning to solve—we are starting to shine a light on this blind spot. In doing so, we have unveiled some surprising insights and some encouraging opportunities across patient recruitment and enrollment.
The vast majority of potential candidates considered for clinical trials (well over 90 percent) never make it to enrollment. While many of those patients who fall out do so for legitimate reasons (e.g. they have a comorbidity or drug allergy that excludes them from participating), our data show that a meaningful percentage of them could effectively enroll in studies, but are lost due to inefficiencies in how we manage trial operations. In other words, there is a significant amount of “avoidable loss” throughout patient recruitment and enrollment that, if addressed, can have a substantial impact on the success of trials.
If we, as an industry, can better understand where patients are falling out and why, we can meaningfully improve enrollment efficiency and truly improve the speed of clinical trials.
We will investigate where our industry identifies potential patients, how sites are managing potential patients across those various channels, and challenges sites face in engaging patients at the top of the patient recruitment funnel.
We will look at the methods sites use to pre-screen patients, types of questions asked during pre-screening, and major causes for pre-screen failures.
We will dig into why we see drop off between patients who have been successfully screened and patients who actually make it to enrollment.
While the industry spends more than $44 billion on clinical trials, 90% of potential patients are lost before enrollment. This signals a huge opportunity to drive more effective processes.
Let’s dive into the top of the recruitment funnel—an aspect of clinical trials significantly affected by unnecessary operational and logistical problems.
In this chapter, we’ll discuss:
Today, a staggering 80% of all clinical trials fail to meet enrollment objectives, with both sites and sponsors trapped in the inertia of inefficiency. Sites get stuck with administrative work that prevents them from successfully moving candidates through the recruitment and enrollment process. Meanwhile, sponsors invest heavily to find qualified candidates for their clinical trials but have little or no visibility into which referral sources result in enrolled patients.
So where does it go wrong? At the beginning of a clinical trial, sites and sponsors start the process of identifying and sourcing candidates. A common misconception is that there’s a lack of patients available for clinical trials. While this is true in some cases, such as rare disease trials, the primary challenge is that the process of managing identified candidates and moving them towards enrollment is inefficient, scattered, and unnecessarily cumbersome.
of all clinical trials fail to meet enrollment objectives
Many trial participants come from pools of patients that have interacted with sites for previous trials or for routine care. Sites often sift through their own EMR/EHR systems, charts, and patient records to find these candidates.
Providers who stay informed of potential trial opportunities for their patients both within their own site and across broader professional networks often make valuable referrals. In fact, our data suggest that candidates referred by providers within or outside of the research site enroll at the highest rates.
Sites themselves support local ad campaigns to reach potential candidates (bus ads, for example) throughout the general population.
A variety of sources available to sponsors, including:
While possible, this is rare, considering that 75% of people are unaware of clinical studies as a treatment option
The variety of referral sources creates a major administrative challenge as sites enter the patient intake and pre-screening phases (the second stage in the timeline below). Nurses and site coordinators have to track numerous candidates across disparate systems—from email reports to Excel exports to loose-leaf paper with handwritten notes scribbled in the margins.
Beyond managing the massive number of inbound leads, clinical staff have to figure out which candidates are a match and begin pre-screening, a process that can become a juggling act. Sites contact potential and new patients individually to walk them through the clinical trial process and the trial’s procedures, determine if they’re a fit, follow up and make sure they’re feeling okay, schedule visits, ensure informed consent is complete, complete lab draws—all while simultaneously caring for patients, which includes more follow-up calls and scheduling visits. Given this inefficient referral system and the administrative fatigue it creates, it’s not surprising that between 40-50% of potential patients are lost in this initial stage of recruitment and enrollment.
Optimizing recruitment and enrollment at the top of the funnel allows both sites and sponsors to identify potential patients early on, create a system of visibility for all parties, and successfully and efficiently reach enrollment goals for clinical trials.
By nature, clinical trials are at the forefront of therapeutic innovation and discovery, yet the process lags behind from a digital transformation standpoint. As illustrated below, a wealth of information from multiple sources comes together at the trial site, but traditional tracking methods lack efficiency and visibility, limiting the utility of the data.
Instead of manually tracking enrollment, cloud-based dashboards streamline the process and provide visibility for sites, sponsors, and partners to know what’s working and what’s not. This visibility helps clinical researchers make adjustments in near real-time while trials are enrolling.
Some insights coming from these data include:
Sponsors and sites also benefit when they have a central database for future reference with longitudinal site data to inform relevant clinical trials. Reify Health is committed to solving these specific problems through technology, as you can see in this case study.
More than half of recruited patients that are potentially eligible for a trial never get contacted or receive a follow-up from site staff; the patients are simply lost in the maze of recruitment work, according to analysis by Reify Health. However, sites that use sponsor-connected enrollment applications move more than 60% of eligible patients through the recruitment and enrollment funnel.
Managing patient identification and engagement is just part of the top of the funnel, but it impacts the entire process and creates significant blind spots and pitfalls for the following stages of clinical trial development.
Small considerations in managing top-of-funnel subject recruitment can make big differences for clinical trial performance. While there are many available (and growing) channels for patient recruitment, up to 90 percent of clinical trials still face delays due to low enrollment rates and inefficient processes.
So how can you continue to efficiently leverage recruitment channels to get eligible trial candidates to successful study enrollment? Here we’ll explore:
To maximize enrollment efficiency means to maximize the ratio of recruited subjects to enrolled subjects. While a robust patient pipeline is great, it doesn’t do much good if these candidates are a poor fit for the trial or if participation isn’t feasible. Integrating pre-screening questions earlier in the recruitment process is an easy way to minimize wasted time and effort for both site staff and trial candidates.
For referrals made from broader pools, such as those from recruitment vendors or through patient self-identification, this can be particularly crucial. Including pre-screening questions regarding a patient’s geographic distance from the trial site, especially for trials involving many onsite visits, can be an effective way to filter out candidates who would be physically unable to make it to clinical visits. Conversely, in the case of a decentralized or hybrid trial, expanding geographical boundaries on your recruitment efforts could be a huge benefit. Site location and accessibility is obviously an important issue to consider in trial design and site selection (which we will explore further in Part 4), but filtering candidates by location is worth considering during the recruitment phase in the interest of feasibility.
Providers can be a great source of patient referrals, and—because of their medical expertise—they’re particularly well-suited to deliver candidates that are a likely therapeutic match for a trial. Educating providers who make referrals on some of the higher-level eligibility criteria can refine their referrals even further, essentially completing some pre-screening for you.
Integrating pre-screening questions that lack sufficient detail will likely generate leads that aren’t suitable for a trial, but an excess of specification could deter interested potential patients early in the recruitment funnel.
Creating a more thoughtful process of pre-screening patients from the top of the recruitment and enrollment funnel can promise a clearer future. If you were the VP of sales at a company but only knew about deals that closed successfully, you don’t have much of an opportunity to gauge success and improve your processes. Making sure that the candidates who are contacted and scheduled for screening visits are likely to be both eligible and able to participate will save valuable time for sites and patients alike.
On the opposite end of the spectrum, some multisite trials may allot only a few patient slots per site at a given time. In these cases, candidate interest and eligibility may outpace availability for a spot on the trial, making a waitlist necessary for managing recruitment and enrollment. Managing trial waitlists can be a major stumbling block for coordinators and other site staff—without a unified, transparent system of tracking patients and sharing information with sponsors, waitlist management is often left to sticky notes, emails, voicemails, and other disorganized pieces.
This waitlist dilemma is another great opportunity for a digital recruitment and enrollment solution to dramatically improve efficiency. High-demand clinical trials often need to reach patients as soon as possible, so organization is not just a matter of convenience. A quick summary of the patient’s information built into the waitlist gives site staff instant visibility into eligibility, and transparency for the sponsor saves coordinators time in calls or emails to update the waitlist.
Additionally, this improved waitlist provides a central place for tracking if and when patients were contacted and if a patient is ineligible or uninterested in participating, so that the next waitlisted candidate can be contacted immediately to begin screening and enrollment. For patients relying on a clinical trial as a potential care option, even a few unnecessary days of waiting can be precious time lost.
So far, we’ve discussed how increasing visibility into the recruitment and enrollment funnel and making thoughtful adjustments to this process can optimize enrollment success. While we know these strategies can increase the number of eligible trial participants and improve workflows for sites, our goal, of course, is to get patients to Day 1 of the clinical trial. However, Reify Health data suggest that one third of patients who could be eligible for a study ultimately fail to enroll.
Over the past three chapters on blind spots in clinical trial enrollment, we’ve discussed inefficiencies in patient recruitment and enrollment and solutions for optimizing recruitment of eligible trial participants. As we mentioned in our last part, one third of eligible study participants ultimately fail to enroll. So, what goes wrong, and what can we do to improve the experience for subjects and staff alike?
Moving forward, we’ll discuss:
While clinical trial subjects are often receiving care they need, they are ultimately providing a necessary service along the way. Sometimes it seems they’re asked to put in just as much time and effort as study staff. For example, a study of oncology trial participants showed that enrolled patients were traveling a median distance of 25.8 miles each way for trial participation. If we consider a study protocol that may have multiple trial-related visits each month—or even each week—this represents a major commitment of both time and money.
The first experience potential subjects have in a clinical trial is during the recruitment and enrollment process, making this a critical time to maximize efficiency and organization—not only to ensure data integrity, but also to show patients that trial participation will be worth their while. We’ve discussed how a transparent and comprehensive look into recruitment and screening data plays a role in guiding recruitment approaches. It also provides useful insight into changes that might make study participation more feasible for participants and maximize the number of potential candidates that ultimately enroll.
Inclusion/exclusion criteria are essential for enrolling a participant population that maximizes data integrity and patient safety. These guidelines are aimed at creating a study group that statistically matches the general patient population, but some criteria can create unforeseen limits in recruitment and ultimately favor a younger, healthier study sample (which has led a growing community of researchers to rethink the issue).
A comprehensive look at screening and enrollment data from subjects throughout a trial’s recruitment process can reveal restrictive eligibility criteria that may be holding eligible many patients back from enrollment. Some examples:
Lab tests are a foundational part of understanding patient health and monitoring safety in a trial. Most drug trials require lab values within a specific range at the time of screening in order to participate, but protocol specifications could overlook differences in ranges that exist between populations or with common conditions that may not interfere with the trial.
Many studies restrict current smokers from participation and may also extend that restriction to former smokers within a certain window of quitting. While strict criteria around the habit are valuable for some studies, others could be positioned to be flexible if this is consistently limiting patient enrollment. For example, a trial that excludes subjects who were ever regular smokers may be able to extend to a quit time of 5 years prior or look carefully at their criteria for “regular smoking” without compromising study data.
While it is obviously unwise to open a drug trial to a subject that is allergic to the drug, some trials may exclude potential participants based on allergies to supportive care drugs noted in the protocol (such as a specific antibiotic recommendation). If this is a significant barrier to enrollment, examine the possibility of using alternative (but equally safe and effective) supportive therapies for patients with allergies.
Even when potential subjects meet a trial’s eligibility criteria, they still may choose not to enroll for various reasons. As we mentioned earlier in this chapter, many study activities place significant demands of time and energy on participants. For a protocol with frequent in-person study visits, it’s easy to imagine how the combination of travel costs and scheduling demands could easily render participation unfeasible for a potential subject.
Additionally, potential patients may lack a solid awareness or understanding of what a trial entails, creating hesitancy to participate. Here patient education efforts make a real difference. Providing clear, jargon-free literature that lays out the background, goals, and larger impact of a clinical trial, as well as providing opportunities to ask questions, can help patients feel secure in the decision to participate in a trial (and potentially encourage friends and family to do the same).
If they are comfortable providing it, collecting data on potential subjects’ reasons for declining to participate can inform solutions to overcome these issues in future recruitment efforts. For example, a more flexible visit schedule or a stipend for transportation to and from the clinical site could help patients who would otherwise be unable to participate. Overall, collecting and using this information is a valuable step in reaching the larger goal of making clinical trials accessible to the broadest population possible.
Maximizing diversity and inclusion in the clinical trial sphere is a growing priority of scientific agencies, as summarized in this 2020 announcement by the Food & Drug Administration. After all, the goal of developing any drug or medical device is to improve lives, and creating a product that is as safe and effective for the entire population it aims to reach is key.
Unfortunately, many of the barriers to study participation mentioned above also overlap with disparities in clinical trial representation. Remember that statistic about travel distances we cited earlier? The same study also found that patients from lower-income areas faced a significantly greater travel burden for trial visits (58.3 miles) than patients from higher-income areas (17.8 miles). When we consider the cost of traveling, as well as limitations related to work duties, caregiving responsibilities, or access to transportation, it’s easy to imagine how these disparities can be magnified.
Making trials more accessible for the widest patient population possible will take some effort and change. Integrating technology to collect and leverage data insights from recruitment and enrollment can illuminate barriers in your trial, and the growth of decentralized clinical trial technology will also play a major role in bridging these gaps.
In our previous chapters, we’ve discussed the administrative burdens placed on site staff that let patient referrals fall through the cracks. We know that supporting site staff workflows with better tools can increase trial performance, but it’s also worth considering how an empowered site staff can empower patient participation in turn. Clinical trial participation is often a complex and medically significant decision, so it’s easy to imagine how a stressed, harried, and overworked site workforce might shake patients’ confidence in the trial experience. Empowering site staff and minimizing their administrative burden can give them more time and energy to put focus where it matters—on quality of patient care.
As we reach the end of our four-part ebook on the blind spots facing clinical trial recruitment and enrollment, let’s take a quick look back on what we’ve discussed.
First, we framed the issue as a whole: the patient recruitment and enrollment funnel is an overlooked pain point in clinical research, and the many inefficiencies we see in this stage present great opportunities for improvement.
Next, we reviewed challenges in managing top-of-funnel patient recruitment. While 80% of trials fail to meet enrollment goals, a lack of patients isn’t the issue—it’s the inefficient and cumbersome workflows used to manage the recruitment process.
In our third chapter, we walked through the benefits of increased transparency in the recruitment and enrollment process, specifically once potential subjects are identified and ready to be prescreened. Here, optimizing site staff workflows and increasing data transparency can also make a difference in identifying possible bottlenecks before it’s too late.
Finally, we shifted our focus to the patients involved in clinical trials and some of the barriers to trial participation they face. There’s a lot of work to be done in addressing disparities in clinical research and expanding accessibility of trials, and reflecting on data insights from clinical trials can inform these efforts. Again, an improved clinical trial workflow doesn’t just benefit sponsors and site staff—it empowers more patients to participate in trials, which benefits all of us.
Screening potential clinical trial participants for health-related and demographic eligibility is a core foundation for success in trial enrollment.Read Now →
Below we outline five potential issues to watch for in the first 90 days of a trial and describe how an established partnership between sites and sponsors can make these stumbling blocks easy to identify.Read Now →