Reading a Protocol for the Recruitment Problems It Will Cause

Protocol complexity isn't an abstract scientific-design issue. It shows up at your site as a screen failure rate you didn't forecast, a consent visit that runs three hours, and a referral pipeline that looks healthy on paper and produces almost nothing.

The gap between "we can get patients interested" and "we can get patients enrolled" is usually a protocol problem, not a marketing problem. Here's how to see it early and plan around it.

Read the protocol like a recruiter, not a scientist

Before you commit to an enrollment target, pull three things out of the protocol and put them in front of whoever owns recruitment.

Eligibility arithmetic. Count the inclusion and exclusion criteria, then flag every one that is a rate limiter rather than a safety screen. Washout periods, narrow lab windows, specific prior-therapy sequences, and imaging-confirmed diagnoses all shrink the funnel multiplicatively. A protocol with four hard rate limiters doesn't have four times the difficulty — it has something closer to a compounding effect, and sites commonly find their actual qualified population is a fraction of what the chart pull suggested.

Participant burden. Add up visit count, total hours on site, number of needle sticks, overnight stays, diaries, device wear time, and travel distance. Then ask: would a reasonable person with this condition and a job say yes?

Site burden. Count the procedures that require staff you don't have on every shift — ECG-trained personnel, pharmacy, imaging slots, a phlebotomist for a timed PK series. Anything that requires coordination with an outside department becomes a scheduling bottleneck and a real constraint on how many participants you can run in parallel.

Translate complexity into your enrollment projection

The honest move is to project enrollment from the narrowest criterion, not the broadest. If a protocol requires a treatment-naive population in an indication where most of your patients have already been treated, that single criterion sets your ceiling. Build the number from there, and say so during feasibility.

Sites that commit to sponsor-suggested targets without doing this arithmetic end up in monthly calls explaining underperformance that was predictable at startup.

Redesign your workflow around the hard parts

Once you know where the complexity lives, you can engineer around it.

• Pre-screen against the rate limiters first. Put the two or three disqualifying criteria at the top of your phone script, not at the end. Nobody should answer twelve questions before being screened out on medication history.
• Split consent from screening. For high-burden protocols, let candidates take the consent home and schedule screening separately. It slows the funnel and raises the conversion rate.
• Make the burden visible early. Tell people the visit count and hour total in the first conversation. Consented participants who are surprised at visit three become dropouts.
• Pre-book the bottleneck. If imaging slots or a PK day constrain throughput, reserve them before you enroll, and let that reservation calendar set your enrollment pace.
• Track screen-fail reasons by criterion. After ten failures you'll know which criterion is doing the damage, and that's the evidence you need to request a protocol amendment or a clarifying memo.

Push back with data, not opinions

Sponsors respond poorly to "this protocol is too hard" and well to "of 40 charts reviewed, 31 failed on the 90-day washout; here is the medication distribution." Specific, counted feedback during feasibility — or in the first six weeks — is when amendments are still realistic. Six months in, you're just reporting a miss.