Winning More Studies by Fixing Your Feasibility Answers

Feasibility questionnaires are the single most common place sites lose studies they could have run well. Not because the site lacked capability, but because the answers were vague, optimistic, or clearly copy-pasted from the last one. Sponsors and CROs read hundreds of these. The ones that stand out are specific and internally consistent.

What sponsors are actually testing

A feasibility form looks like a capability survey. It functions as a credibility test. The reviewer is asking three questions:

1. Does this site understand the protocol they're being asked about?
2. Are their numbers plausible given their stated patient population?
3. If we enroll behind schedule, will this site be part of the fix or part of the problem?

Every answer you give should serve one of those. "We have a large diabetes population" serves none of them. "Our EHR query for adults with A1c between 7.5 and 10 on metformin monotherapy, seen in the last 18 months, returns roughly 340 charts; applying our historical eligibility rate for similar trials leaves an addressable pool near 60" serves all three.

Build the query before you need it

The sites that answer feasibility well are not smarter. They did the work earlier. Standing capability worth building:

• A reusable chart query library. One saved query per therapeutic area you work in, parameterized by age, key labs, medication class, and last-visit recency. When a form arrives, you adjust parameters instead of starting cold.
• Documented eligibility yield by indication. For each completed study, record charts identified, pre-screened, screened, and randomized. Over a handful of studies this gives you a defensible conversion assumption rather than a guess.
• Screen-fail reason coding. Knowing that half your failures in a past cardiology trial came from a washout requirement lets you flag the same risk in a new protocol — and that flag is exactly what makes a reviewer trust your enrollment estimate.
• Referral source performance. Which studies came from your own database, which from physician referral, which from paid outreach. Sponsors discount sites that depend entirely on ad spend.

Answer with ranges and reasoning

A single confident number invites skepticism. A range with stated assumptions invites conversation. Try: "We project 8 to 12 randomized over 9 months. The low end assumes we rely on our existing registry only; the upper end assumes we can activate two referring endocrinology practices, which we've done for two prior trials in this indication."

This does two things. It shows your arithmetic, and it tells the sponsor what they can do to move you toward the high end. Sites that show their work get follow-up calls.

Say no out loud

Declining a study, with a reason, is one of the strongest credibility signals available. "We'd be a poor fit — the protocol requires 6-hour PK days and our infusion space is committed Tuesdays and Thursdays" is remembered. In most site datasets, a stated no is followed by more invitations, not fewer, because the sponsor now believes your yeses.

Close the loop

After each study, compare projection to actual and write down the gap and its cause. Two sentences is enough. Do this for a year and your next feasibility response stops being a sales document and becomes a forecast — which is what sponsors have been asking for all along.