Frequent Mistakes to Avoid When Designing Feasibility Surveys

Why Survey Design Matters in Clinical Feasibility

Feasibility surveys are the first checkpoint in clinical trial execution. Sponsors, CROs, and clinical teams rely on these tools to determine which investigator sites are capable of enrolling, complying, and delivering high-quality data. However, flawed survey design can compromise this entire process—leading to site underperformance, protocol deviations, missed enrollment targets, and costly delays. Regulatory authorities like the FDA and EMA have highlighted the importance of accurate feasibility assessments in multiple inspection reports.

Designing an effective feasibility questionnaire is not just about gathering information—it’s about ensuring the **quality, clarity, and relevance** of the data collected. Poor design choices can introduce bias, reduce response rates, and provide misleading inputs, ultimately affecting trial success.

This article explores common pitfalls in feasibility survey design and provides corrective strategies to improve accuracy, efficiency, and regulatory alignment.

1. Over-Reliance on Generic Questionnaires

One of the most frequent mistakes is using generic, one-size-fits-all surveys across all therapeutic areas and trial phases. This ignores the unique requirements of different indications. For example, asking only “Do you have imaging capabilities?” in an oncology trial overlooks critical aspects like:

• Type of imaging (CT, MRI, PET)
• RECIST or iRECIST measurement familiarity
• Archiving and transfer compliance (DICOM format)

Similarly, a vaccine trial might need cold chain logistics and mass-screening capacity questions, which may be completely irrelevant to a rare disease gene therapy study. Lack of customization can cause misaligned expectations and downstream failures.

2. Ambiguous or Leading Questions

Vague phrasing leads to inconsistent interpretation and invalid data. For instance, asking “Can you enroll patients quickly?” is subjective. What qualifies as “quick” for one site may differ from another. Instead, a better version would be:

“How many patients fitting the protocol inclusion criteria did your site enroll in the last 12 months for similar Phase II studies?”

Leading questions also bias the respondent. “You have successfully conducted previous trials, correct?” might trigger social desirability bias. Neutral, fact-based phrasing is key.

3. Excessive Length and Complexity

Lengthy surveys with poor flow reduce completion rates and frustrate site staff. In multi-center trials, sites often have limited staff availability, especially during active study periods. Surveys that take over 45 minutes are less likely to be completed accurately. Issues include:

• Redundant questions across sections
• Poor section organization (e.g., mixing regulatory and infrastructure questions)
• Lack of autosave or ability to pause and resume digital forms

As a best practice, limit questionnaires to 25–30 well-structured questions for initial feasibility, followed by site-specific deep dives as needed. Use digital platforms that allow intuitive navigation and validation.

4. Lack of Data Validation or Documentation Fields

Another flaw is the absence of cross-checks or request for supporting documentation. For example, if a site claims it can enroll 100 patients over 6 months, sponsors should request either:

• Patient registry screenshots
• De-identified electronic health record reports
• Recruitment logs from similar studies

Without these, responses are based solely on memory or estimates, increasing risk of over-promising. Platforms should include fields for file uploads, comment boxes for clarification, and warning prompts for unusual entries.

5. Ignoring Historical Site Performance Data

Failing to consider a site’s previous trial history is a major oversight. Historical data helps contextualize feasibility answers and filter out consistently underperforming sites. For example:

Integrating such data-driven benchmarking within the survey design significantly improves reliability and transparency.

Transition to Solutions and Best Practices

Now that we’ve identified major pitfalls in feasibility survey design, the next part will offer regulatory-aligned solutions, practical templates, and technology integrations to improve the quality of your feasibility assessments.

6. Neglecting to Capture PI and Sub-Investigator Details

Many feasibility surveys focus primarily on site-level infrastructure while ignoring investigator qualifications. Yet, the PI’s past experience, availability, and regulatory track record are critical success factors. A well-designed survey should capture:

• Number of trials conducted in the last 5 years
• Therapeutic area alignment with the protocol
• GCP training validity and inspection history
• Ratio of PI to concurrent active trials

Neglecting to gather such details could lead to site activation delays due to regulatory rejection of PI credentials or unavailability.

7. Overlooking Regional and Regulatory Context

Global feasibility surveys often ignore country-specific regulations and operational limitations. For example:

• In India, the CDSCO has specific rules regarding ethics approvals and compensation
• In Japan, feasibility surveys must include PMDA-specific compliance sections
• In the EU, surveys must align with EU Clinical Trial Regulation (CTR) timelines and document requirements

Not including such country-specific sections can result in inaccurate site feasibility outcomes. For global trials, it’s critical to tailor questions by region or include branching logic that triggers local regulatory queries based on country selection.

8. No Mechanism to Capture Feasibility Risk Flags

A robust feasibility survey should include logic or scoring that auto-generates red flags based on site responses. For instance:

Response	Flag
PI is involved in 7 concurrent studies	Investigator overload
Site has no GCP training in last 3 years	Non-compliance risk
Startup timeline > 90 days	High activation risk

Such automated risk indicators help feasibility managers prioritize follow-ups and site visits.

9. Lack of Digital Integration and Data Traceability

Paper-based or email surveys still exist in some trials, resulting in data loss, miscommunication, and lack of audit trails. Regulatory inspectors, including from the FDA, expect version control, date/time stamps, and investigator signatures on feasibility forms.

Surveys should be integrated into platforms like Veeva CTMS, Clario Feasibility, or other compliant digital tools. This enables audit-ready documentation and seamless comparison across protocols and regions.

10. Ignoring Site Feedback for Continuous Improvement

Finally, many sponsors and CROs fail to review site feedback post-survey. Sites may provide comments such as:

• “Questions are repetitive or unclear”
• “Form is too long for busy clinics”
• “Unable to attach required documents easily”

Incorporating this feedback into subsequent versions ensures higher response rates, better data, and improved sponsor-site collaboration. Sponsors should conduct post-survey reviews or pilot testing to optimize forms continuously.

Best Practice Recommendations

• Limit initial surveys to 25–30 critical questions
• Use digital tools with conditional logic and data upload fields
• Benchmark recruitment estimates with historical performance
• Customize by therapeutic area and regulatory region
• Include risk scoring and auto-flagging mechanisms
• Maintain an audit-ready record with version control and timestamps

Tools like Clinscape, TrialHub, and Medidata can help structure and automate these best practices into scalable survey systems.

Conclusion

Feasibility surveys are the foundation of successful clinical trials. Yet, poor design introduces risk, waste, and non-compliance. Sponsors and CROs must recognize and avoid the common pitfalls outlined above—generic questions, ambiguous wording, missing validations, and absence of risk flagging. By adopting best practices, leveraging digital platforms, and integrating historical data, sponsors can build robust, regulatory-aligned feasibility tools that drive accurate site selection and successful trial execution.

Essential Questions for Designing an Effective Feasibility Questionnaire

Understanding the Role of Feasibility Questionnaires

Before selecting sites and investigators, sponsors and CROs must carefully evaluate a site’s ability to successfully execute a clinical trial. A feasibility questionnaire is one of the most important tools for this assessment. These documents collect structured information about a site’s resources, patient pool, regulatory experience, and infrastructure readiness. Regulatory agencies such as the FDA, EMA, and national authorities expect sponsors to document feasibility efforts as part of Good Clinical Practice (GCP) compliance. Without a robust feasibility process, sponsors risk delays, under-enrollment, and inspection findings during trial audits.

Feasibility questionnaires typically cover domains such as:

• Patient recruitment and retention potential
• Principal Investigator (PI) and sub-investigator experience
• Site infrastructure, including equipment and labs
• Previous performance in similar therapeutic areas
• Local regulatory and ethics committee processes

For example, in oncology studies, questionnaires often probe whether the site has access to pathology labs capable of immunohistochemistry testing, or whether genetic testing partnerships exist. In infectious disease studies, questions may focus on availability of biosafety level facilities. Thus, while core domains remain consistent, therapeutic area–specific tailoring is essential.

Critical Patient-Related Questions

Patient recruitment is one of the most common barriers to timely trial completion. Regulators, including the European Medicines Agency (EMA), emphasize that feasibility assessments should be realistic and data-driven. A questionnaire must therefore ask targeted questions about patient populations. Examples include:

Incorporating epidemiological data strengthens these questions. For example, if a site estimates 300 eligible patients annually but national disease burden data suggests fewer than 50 cases in the region, this discrepancy raises concerns about overestimation. Sponsors should cross-check questionnaire responses with external databases such as ClinicalTrials.gov to validate feasibility claims against trial recruitment histories.

Questions on Investigator and Staff Experience

A site’s human resources are equally critical. Regulators often highlight inadequate investigator oversight as a frequent finding in inspections. Questionnaires should evaluate whether the PI and supporting staff have the necessary experience. Key questions include:

• How many clinical trials has the PI conducted in the past five years, and in which therapeutic areas?
• Has the PI received any regulatory inspection findings related to GCP?
• What is the average turnover rate of study coordinators and research nurses?
• What GCP training and certification do staff currently hold?

For example, a PI with ten oncology trials completed but with multiple FDA Form 483 citations may be a higher risk compared to a less experienced PI with a clean regulatory record. Feasibility questionnaires should capture such nuances.

Infrastructure and Technology Questions

Infrastructure capability directly influences trial quality. For complex trials requiring bioanalytical testing, imaging, or cold-chain management, questionnaires must go beyond basic facilities inquiries. Sample questions include:

• Does the site have validated -80°C freezers with continuous temperature monitoring?
• Are backup power systems in place to safeguard sample integrity?
• Is the site equipped with validated software for electronic data capture (EDC)?
• Are laboratory instruments calibrated according to international standards (e.g., ISO 15189)?

Some questionnaires include sample validation parameters such as:

These details help sponsors differentiate between sites that claim readiness and those that are genuinely prepared for trial operations.

Regulatory and Ethics Questions

Finally, feasibility questionnaires must assess local regulatory and ethics environments. Delays in IRB/EC approvals are a common reason for missed trial timelines. Essential questions include:

• What is the average IRB/EC review timeline for clinical trials at your institution?
• Do you have prior experience submitting to regulatory authorities such as FDA, EMA, CDSCO, or PMDA?
• Are there institutional policies restricting enrollment of vulnerable populations?

For example, if a site reports an average of 45 days for ethics approvals, sponsors can plan activation timelines accordingly. Sites with extended timelines (e.g., >90 days) may not be suitable for fast-track studies.

Transition to Next Considerations

The above domains—patient recruitment, investigator experience, infrastructure, and regulatory landscape—form the backbone of feasibility questionnaires. However, sponsors must also evaluate validation of responses, data reliability, and strategies to prevent overpromising. These aspects will be explored in Part 2, with focus on case studies, pitfalls, and best practices for robust feasibility planning.

Validating Feasibility Questionnaire Responses

Feasibility questionnaires are only useful if responses are accurate. Regulators and sponsors increasingly emphasize data verification as part of trial oversight. Sponsors must apply validation strategies to ensure that sites are not inflating capabilities or patient pools to secure trial participation.

One approach is to cross-verify patient pool estimates with hospital records, referral databases, or national disease registries. For example, if a site reports 500 annual cases of Type 2 diabetes, but regional public health data suggests only 300 cases, the sponsor should investigate. Similarly, sponsors should request anonymized patient counts or ICD-10 code reports to substantiate claims.

Case Study: Inflated Patient Recruitment Claims

A multinational sponsor faced delays in an oncology trial when three sites overestimated recruitment potential. While questionnaires projected 50 patients per site annually, actual enrollment was less than 10. Upon review, it was found that sites included patients outside inclusion criteria. This case underscores the importance of rigorous validation, including review of electronic health records (EHRs) and prior recruitment histories from registries such as ISRCTN Registry.

Common Pitfalls in Questionnaire Design

Despite best intentions, poorly designed questionnaires often result in incomplete or misleading data. Common pitfalls include:

• Overly generic questions that do not capture therapeutic-specific nuances
• Yes/No questions without quantitative context (e.g., “Do you have lab facilities?” instead of “How many calibrated centrifuges are available?”)
• Failure to include data validation fields or request supporting documentation
• Excessive questionnaire length leading to incomplete responses

To avoid these issues, sponsors should pilot-test questionnaires with selected sites and adjust based on feedback. Regulatory authorities also recommend focusing on essential questions that directly impact trial feasibility, rather than exhaustive lists that burden sites unnecessarily.

Best Practices for Effective Questionnaires

Effective feasibility questionnaires balance comprehensiveness with clarity. Best practices include:

• Tailoring questionnaires by therapeutic area (oncology, cardiology, infectious disease)
• Using a mix of quantitative and qualitative questions
• Integrating electronic platforms to streamline completion and analysis
• Embedding mandatory data validation checks (e.g., requiring supporting documentation uploads)

Some sponsors now deploy digital feasibility tools integrated with Clinical Trial Management Systems (CTMS). These allow automated scoring, comparison across sites, and identification of red flags such as inconsistent patient data. For example, an AI-enabled feasibility tool might score sites based on patient pool adequacy, infrastructure readiness, and regulatory history, generating a composite feasibility index for decision-making.

Sample Feasibility Scoring Framework

This weighted approach ensures objective decision-making while allowing customization for specific trial needs. For instance, in rare disease studies with small populations, patient recruitment weight might increase to 60%.

Conclusion

Feasibility questionnaires are a cornerstone of site selection and clinical trial planning. By including targeted questions on patients, investigators, infrastructure, and regulatory environment—and by validating responses through data cross-checks—sponsors can mitigate risks of underperformance and regulatory non-compliance. Effective design not only accelerates trial start-up but also strengthens inspection readiness by demonstrating a structured feasibility process.