Feasibility Assessments: The Case for Honest Numbers

Every site knows the temptation: the feasibility questionnaire asks how many eligible patients you can enroll, the honest answer is eight, and twenty wins the study. Industry-wide, the result is that a large fraction of sites under-deliver on their commitments — and sponsors know it, which is why they over-select sites and watch startup metrics like hawks.

The real cost of the inflated yes

A site that commits to twenty and delivers eight doesn't just strain one relationship. It lands on the wrong side of sponsor site-selection databases that increasingly track historical enroll-to-commitment ratios. The short-term win becomes a long-term filter working against you. Meanwhile the study itself suffers: under-enrolling sites trigger rescue campaigns, protocol amendments, and timeline extensions that burn everyone.

Building projections you can defend

Query, don't estimate. Run the actual inclusion criteria against your database and registry. "We have 214 patients matching age, diagnosis, and medication criteria, of whom roughly 30% historically convert" is a projection. "We see a lot of diabetics" is a vibe.

Discount honestly. Apply your real historical rates: contact rate, pre-screen pass rate, consent rate, screen-fail rate. Every site has these numbers, even if they've never been assembled.

Model the competition. Two concurrent studies drawing on the same population split the yield. Say so.

Show your work. A feasibility response that includes the funnel math reads as competence. Sponsors trust sites that treat projections as engineering rather than sales.

When the honest number is small

Sometimes the right response is "six enrollments, and here's exactly how" — or declining the study. Sites with the discipline to pass on poor fits keep their metrics clean, their coordinators sane, and their credibility compounding. In a relationship business, being the site whose numbers mean something is the durable advantage.