Feasibility Questionnaires and Validating What Sites Claim

Part of Clinical Research Associate (CRA) Training: Site Identification and Feasibility.

About 5 minutes. Free, in your language, no account needed.

Why this matters

Feasibility questionnaires are answered by people who want the study. That is not dishonesty; it is optimism, and optimism is systematic.

Your job is not to catch sites out. It is to convert optimistic answers into numbers a sponsor can plan with.

What the questionnaire covers

A feasibility questionnaire, sometimes shortened to FQ, is sent to candidate sites and normally asks about:

• Patient population size and characteristics for this indication.
• Estimated enrollment, and over what period.
• Investigator and staff experience.
• Facilities, equipment and storage.
• Laboratory capability and accreditation.
• Competing trials in the same population.
• Systems experience.
• Ethics committee arrangements and typical timelines.
• Specialized capabilities the protocol needs, such as particular imaging, biopsies or infusions.

Its purpose is filtering. It is a first pass, not evidence.

Reading the answers critically

Three questions to hold while you read.

Is the enrollment number derived or asserted? A derived number can be shown: patients seen last year, minus those failing the main eligibility criteria, times a realistic consent rate. An asserted number is just a number.

Does the claim match the site's own history? A site claiming 30 participants that enrolled 6 in a comparable study needs to explain what changed.

Does the claim match the disease? Compare the claimed patient volume against what is plausible for the local population and prevalence. A site claiming a patient volume far above what its catchment could support is claiming something that needs explaining.

Validation: what you actually check

Validation converts claims into evidence. For each significant claim, get something concrete.

• Patient numbers. Ask how they arrived at the figure. Ask for the underlying count: clinic attendances, database query results, diagnosis codes. A site that cannot produce the arithmetic is guessing.
• Procedures. Are the imaging, laboratory or procedural capabilities actually on site, or referred elsewhere? If referred, what is the turnaround, and does it fit the protocol's windows?
• Investigator experience. Check what the investigator did in previous trials rather than what they were listed as. Being a sub-investigator on four studies is different from having run one.
• Workload. List every trial the site is running and who works on each. Then ask what will change when this study starts.
• Ethics timelines. Ask for actual dates from their last two submissions rather than a general estimate.
• Laboratory accreditation. Confirm current certification and that it covers the tests the protocol requires.

Do this by telephone or video with the coordinator as well as the investigator. Coordinators answer capacity questions more accurately than investigators do, because they are the capacity.

Red flags

• Very high claimed patient volumes with no supporting evidence.
• An investigator listing heavy clinical duties and no protected research time.
• Feasibility answers that contradict the site's historical performance.
• Answers that arrive fully completed within an hour of the request.
• No mention of any competing trial when registry data shows several.
• Reluctance to let you speak to the coordinator.
• An enrollment estimate that is a round number with no arithmetic behind it.

None of these is proof of anything. Each is a reason to ask one more question.

Documenting validation

Keep a feasibility validation record for each site: what was claimed, what you checked, what you found, and any follow-up requested. This record does three things — it supports the selection recommendation, it gives the sponsor a documented basis for its decision, and it gives you a baseline to compare against when the site is running.

Emails and call notes belong with it. If a site later performs very differently from its claims, this record is how the sponsor learns something for the next trial.

In practice

A candidate site for VT-301 claims 500 patients with type 2 diabetes and estimates 40 participants over twelve months.

Leah asks how the 40 was reached. The coordinator explains it is roughly ten percent of the database, "which is what we usually get".

Leah works through it with her instead. Of the 500, the protocol's age range and the exclusion for a common co-existing condition remove about half. Of the remaining 250, the site sees perhaps 120 in a twelve-month window. A realistic consent rate for a study with monthly visits is well under half. Another diabetes trial at the site is already recruiting from the same list.

Together they arrive at 15 to 18. The coordinator agrees it is more realistic and is visibly relieved to say so.

Leah records the revised estimate, the arithmetic, and the competing trial. The site is selected with a target of 16. It enrolls 17 and is regarded as a strong performer.

The same site, held to 40, would have been regarded as a failure at 17.

Key takeaways

• Feasibility questionnaires filter candidates; they are not evidence, because they are answered by people who want the study.
• A usable enrollment estimate is derived and can be shown as arithmetic: patients seen, minus eligibility losses, times a realistic consent rate.
• Validate claims against the site's own history and against what the local population can plausibly support, and ask what changed if the two disagree.
• Speak to the coordinator as well as the investigator, because coordinators answer capacity questions more accurately.
• Keep a documented feasibility validation record, which supports the selection decision and gives a baseline for judging the site's later performance.