The Feasibility Gap: Why High-Quality Sites Miss Study Opportunities

A site can run a clean feasibility process, staff an experienced coordinator team, and still watch its enrollment numbers land below what its own track record would predict. That is not a contradiction. It is a documented pattern in the industry: capable, experienced sites complete feasibility, get engaged by a sponsor, and then watch a study move forward while attention and allocation go to sites that go on to struggle with activation or enrollment (Applied Clinical Trials Online). The site did nothing wrong on paper. The gap sits somewhere between what a site can actually deliver and what the selection and allocation process actually rewards.

The gap a feasibility questionnaire never measures

A feasibility questionnaire is built to score capability at a single point in time: patient population size, staff headcount, prior protocol experience, IRB turnaround. All of that is real information, and a site that answers honestly gives a sponsor an accurate read on whether it could enroll the study.

What the questionnaire does not score is what happens after it gets submitted. Two sites can pass feasibility with nearly identical numbers and end up with completely different outcomes. One gets activated in week two and receives a full patient allocation. The other gets activated in week nine, after three faster sites have already worked through the easiest patients in the shared referral pool.

Passing feasibility measures whether a site could enroll a study. It says nothing about whether a site will actually get the timing and allocation it needs to prove it.

Reason 1: Activation speed decides who reaches the population first

Every multi-site study pulls from an overlapping patient pool in a given region, especially in higher-prevalence indications. The sites that get their contract executed, IRB approval finalized, and site initiation visit completed first are the ones that see that pool while it is still full.

A site that is fully capable on paper but slow to activate is not competing against its own feasibility number. It is competing against every faster site pulling from the same population in the same window. By the time a slower site is ready to screen, the easiest-to-find patients are already consented somewhere else.

None of this shows up on the feasibility questionnaire, because activation speed is an operational variable, not a capability one. A site with strong capability and a six-week contract turnaround will lose ground every time to a site with average capability and a two-week turnaround.

Enrollment shortfalls blamed on “the population wasn’t there” are frequently activation-timing shortfalls wearing a different explanation.

Reason 2: Allocation defaults to relationship history, not the current readiness signal

Sponsors and CROs manage risk by leaning on sites they already know. A site with three prior studies for the same sponsor gets first access to a new protocol’s allocation, even when a newer site’s current feasibility answer is objectively stronger for that specific patient population.

This is not a judgment on the newer site’s capability. It is a structural bias toward familiarity, and it means a strong feasibility answer from a site without a deep sponsor history routinely gets a smaller initial allocation than an average answer from a site with one.

The result: a capable site’s enrollment number looks disappointing next to its own feasibility projection, when the real explanation is that the number was capped by allocation before the site ever started screening.

Reason 3: No feedback loop means the same gap repeats at the next study

When a site is passed over, given a small allocation, or comes up short against projection, the sponsor rarely explains why. Survey research cited by Advarra found that nearly one in five sites never receive feedback on a selection decision at all, and another 34% say they very rarely receive it. Even when feedback is given, 51% of sites describe it as not useful or helpful.

Without that signal, a site cannot tell whether a thin allocation was a capability problem, a relationship problem, or an activation-timing problem, and it cannot fix what it cannot diagnose. The structural gap that quietly capped this study’s number is free to repeat itself at the next one.

A site that never gets real feedback is stuck re-running the same feasibility process and landing the same capped result, study after study.

Why this is a different problem than a stalled enrollment number

Our guide on clinical trial enrollment challenges covers the execution side of a shortfall: screen fail rate, consent friction, coordinator bandwidth, referral pipeline gaps. Those are real, and they explain a large share of underperformance once a site has already been activated with a real allocation.

The feasibility gap described here happens earlier and is invisible to a site’s own operations team, because it is not caused by anything the site did during the study. A site can run flawless execution against a small, late allocation and still land well under its historical enrollment rate, simply because the allocation and timing it was handed made the number unreachable regardless of execution quality.

Confusing the two leads to the wrong fix. A site diagnosing an allocation problem as an execution problem adds coordinator hours to a process that was never going to hit its number, no matter how well it ran.

Closing the gap: what a site actually controls

Capability, activation speed relative to competing sites, and sponsor familiarity are not equally within a site’s control. But four things are, and they are the difference between absorbing the gap indefinitely and closing it.

If you are weighing whether your next study is even a fit for outside recruitment support, check whether your study qualifies before the next allocation conversation.

Where a recruitment partner closes what feasibility alone cannot

A strong feasibility answer, a documented track record, and a fast activation timeline improve a site’s odds. They do not eliminate the earlier problem: sponsors size initial allocation around their own internal patient pipeline, and that pipeline is capped by whatever the sponsor’s own outreach is producing that month.

A recruitment partner works around that ceiling by bringing an independent, additive patient pipeline, one that does not depend on where the sponsor’s default allocation sent screening volume first. That is why sites working with a dedicated partner routinely enroll patients beyond what the sponsor’s organic allocation alone would have produced, even at sites that already had a strong feasibility profile.

Capability was never the whole equation

Activation speed relative to competing sites, allocation history, and whether a sponsor ever explains a decision have always sat mostly outside a site’s control. What a site can control is how it documents its own conversion data, how consistently it pushes for real feedback, and whether it brings in a partner that adds patients independent of the sponsor’s internal pipeline.

Clinical Enroll has delivered randomization across 30+ indications by closing exactly that gap: bringing sites a patient pipeline that does not depend on where a sponsor’s own allocation happened to land this quarter.