Designing Feasibility Questionnaires Using Historical Site Data

The Importance of Historical Site Data in Feasibility Planning

Feasibility questionnaires are foundational tools in clinical trial planning. They help sponsors and CROs identify and select high-performing sites based on several factors like patient pool, investigator experience, infrastructure, and regulatory track record. However, when these questionnaires are designed without historical context, they can result in overly optimistic or inaccurate site responses. That’s where leveraging historical site data becomes critical.

Historical site data includes past enrollment rates, protocol deviation frequencies, screen failure rates, regulatory inspection outcomes, and adherence to visit schedules. Sponsors that fail to incorporate this data often face recruitment delays, budget overruns, and poor site compliance. Regulatory bodies including the FDA, EMA, and MHRA emphasize the use of evidence-based feasibility strategies during sponsor inspections.

In this article, we explore how to use historical site data to design smarter, more predictive feasibility questionnaires that improve site selection and study startup efficiency.

Types of Historical Data Relevant to Questionnaire Design

Historical site data spans multiple domains. The most useful categories include:

• Enrollment History: Number of subjects enrolled in similar trials within a specific timeframe
• Protocol Adherence: Frequency of deviations and their root causes
• Screen Failure Rates: Percentage of screened patients not meeting inclusion criteria
• Site Activation Timelines: Average time from contract finalization to first patient in (FPI)
• Regulatory Inspection Outcomes: FDA 483 observations, MHRA findings, or internal QA audits

Below is an example data summary from three sites in a cardiovascular trial:

From this table, it’s evident that Site A outperformed others in all key areas. Integrating this insight into a questionnaire helps to focus future feasibility assessments on parameters that matter.

Integrating Data into Feasibility Questionnaire Logic

Feasibility tools often consist of static checklists or self-reported site capabilities. When these are integrated with historical performance data, they become much more predictive. Here’s how historical data can enhance questionnaire sections:

• Recruitment Potential Section: Pre-fill enrollment numbers from past studies and ask the site to explain any changes
• Protocol Adherence Section: Highlight deviation patterns from previous trials and assess current mitigation measures
• Timeline Commitments: Use actual past activation data to validate new timeline estimates

For example, a dynamic form might display: “In your last three trials in this therapeutic area, your average enrollment was 20 patients over 6 months. What has changed to support your estimate of 60 patients in this protocol?”

This approach discourages over-promising and helps differentiate high-performing, realistic sites from aspirational responders.

Sources of Historical Site Data

Historical site data can be gathered from several internal and public sources:

• Clinical Trial Management Systems (CTMS): Capture site-level metrics from previous studies
• Electronic Data Capture (EDC) Platforms: Document protocol adherence and visit windows
• Trial Registries: Data from Be Part of Research (NIHR) and other registries to validate enrollment timelines
• Quality Management Systems (QMS): Archive audit outcomes, CAPA timelines, and deviations

Sponsors that maintain a structured site master file with past feasibility, audit reports, and performance summaries can extract this data with minimal effort. It’s also beneficial to include CRO partner databases and publicly available performance scores (e.g., from the TransCelerate Shared Investigator Platform).

Feasibility Questionnaire Elements That Benefit from Data Integration

Not all parts of a feasibility questionnaire require historical data, but certain sections benefit significantly from it:

By designing forms with auto-filled historical fields, sponsors can reduce bias and increase transparency. Some tools even allow scoring systems based on prior performance benchmarks.

Case Study: Data-Driven Feasibility Yields Better Enrollment

In a 2023 Phase II neurology study, the sponsor used historical site performance data to filter out low-recruiting sites from a previous epilepsy trial. By incorporating metrics such as “patients enrolled per FTE” and “visit adherence rate,” they excluded 30% of sites that had previously delayed timelines. The remaining sites achieved 95% of the recruitment target three months ahead of schedule.

This outcome illustrates how applying historical metrics during feasibility tool design directly impacts enrollment, cost, and data integrity.

Tools and Platforms That Support Data-Driven Questionnaire Design

Sponsors can use various platforms to operationalize this approach:

• CTMS Platforms: Veeva Vault CTMS, Medidata RAVE
• Feasibility Tools: SiteIQ, Clinscape Feasibility Module
• Analytics Dashboards: Tableau, Power BI connected to CTMS/EDC sources
• Risk-Based Monitoring Tools: RBM dashboards that include performance trend lines

These systems allow sponsors to design adaptive questionnaires, conduct real-time validation of site claims, and score site responses against benchmarks.

Challenges and Considerations

Despite the advantages, there are challenges to using historical data:

• Data inconsistency across CROs and systems
• Lack of access to complete legacy data for global sites
• Privacy and data protection regulations (e.g., GDPR)
• Misinterpretation of context (e.g., poor performance due to protocol flaws, not site issues)

Therefore, sponsors must contextualize historical data and allow sites to provide explanations for deviations or poor performance. Data should be used to initiate dialogue, not penalize sites without cause.

Conclusion

Designing feasibility questionnaires using historical site data enables evidence-based site selection, reduces trial risk, and improves regulatory compliance. Sponsors should move away from static, self-reported surveys and adopt dynamic, data-informed tools that consider past performance. Platforms such as CTMS, QMS, and analytics dashboards can help integrate these insights into feasibility tools, creating a predictive framework for identifying high-performing, inspection-ready sites. In doing so, the industry takes a meaningful step toward smarter, faster, and more reliable clinical trial execution.

Strategies to Minimize Travel Burden in Rare Disease Clinical Trials

Why Travel Is a Barrier in Rare Disease Research

In rare disease clinical trials, eligible patients often reside far from trial sites, which are typically concentrated in major cities or academic centers. Given the small and globally dispersed patient populations, it’s not uncommon for participants to travel hundreds or even thousands of kilometers to access a site. This travel burden can discourage enrollment, increase dropout risk, and disproportionately exclude rural or low-income participants.

Moreover, many rare disease patients are children, elderly, or have mobility challenges that make long-distance travel physically, emotionally, and financially taxing. Recognizing and addressing this barrier is essential to achieving equitable and successful clinical trial participation.

Key Travel-Related Challenges in Rare Disease Trials

Participants and their caregivers may encounter several obstacles related to travel, including:

• Geographic Isolation: Trial sites may be located in only a handful of countries, requiring international travel for some participants.
• Financial Constraints: Costs associated with airfare, lodging, meals, and local transport can be prohibitive, especially for multi-visit studies.
• Medical Fragility: Many patients are immunocompromised, wheelchair-bound, or dependent on caregivers, making travel risky and complex.
• Visa and Documentation Delays: Cross-border travel introduces administrative delays that can exclude otherwise eligible patients.

Left unaddressed, these burdens compromise both trial diversity and scientific integrity.

Implementing Site-to-Patient (S2P) Trial Models

One of the most effective ways to reduce travel burden is through decentralized or hybrid trial models that bring the study to the patient. Components of S2P models include:

• Home Health Visits: Trained nurses conduct assessments, sample collection, and safety checks at the patient’s home.
• Telemedicine Visits: Video-based investigator check-ins reduce the need for in-person site visits.
• Mobile Sites: Use of vans or portable equipment for conducting local procedures in rural settings.
• Local Lab Partnerships: Leveraging nearby diagnostics facilities for routine tests and sample shipments.

These approaches can be implemented selectively based on study phase, complexity, and patient condition.

Travel Logistics and Reimbursement Programs

When travel is unavoidable, sponsors must provide comprehensive support to ensure participants can attend without financial strain. Best practices include:

• Centralized Travel Coordination: Provide patients with a dedicated travel concierge to manage booking, itineraries, and special needs (e.g., wheelchair-accessible transport).
• Advance Reimbursement: Offer pre-paid travel cards or upfront disbursements to avoid out-of-pocket expenses.
• Lodging Support: Partner with hotels near sites that accommodate patient-specific needs.
• Caregiver Stipends: Include caregiver travel costs and per diems as part of trial budgeting.

These services reduce dropout due to travel stress and demonstrate respect for patient time and resources.

Case Study: Multi-Country Trial Using Decentralized Visits

In a global rare epilepsy trial, the sponsor implemented decentralized visits for long-term follow-up. Patients in Canada, Brazil, and Eastern Europe were offered the choice between on-site and home-based visits.

Outcomes included:

• 35% of participants opted for hybrid participation (some on-site, some remote)
• Travel-related withdrawal dropped by 60% from previous trials
• Enrollment increased in rural provinces with previously zero participation

This example shows that travel flexibility leads to more diverse and engaged trial populations.

Leveraging Local Partnerships for Patient Support

Partnering with community healthcare providers, rare disease clinics, and patient organizations can help reduce the need for long-distance travel. These partners can:

• Perform routine procedures closer to the patient’s home
• Assist with medication delivery or IV administration
• Offer emotional and logistical support to caregivers
• Act as trusted liaisons between patients and trial teams

Engaging local resources can expand trial reach and reduce the site burden simultaneously.

Technology Solutions to Support Remote Participation

Digital tools help bridge the gap between sites and remote participants:

• ePRO Apps: Allow patients to submit data without site visits.
• Telehealth Platforms: Enable secure, compliant video assessments with investigators.
• Remote Monitoring Devices: Wearables collect real-time data on vitals, movement, or sleep patterns.
• Virtual Site Portals: Provide access to visit schedules, trial education materials, and direct communication with coordinators.

These tools empower patients and reduce physical demands while maintaining data quality and compliance.

Regulatory Considerations and Risk Mitigation

Reducing travel burden must be balanced with regulatory compliance and patient safety. Sponsors should:

• Submit protocol amendments when shifting to remote models
• Ensure local IRBs approve travel support and reimbursement programs
• Use Good Clinical Practice (GCP)-trained home health providers
• Maintain documentation of decentralized procedures for audits

Proper documentation and oversight are essential to ensure decentralization enhances rather than compromises trial quality.

Conclusion: Reducing Burden, Increasing Access

Travel should never be the reason a patient misses the opportunity to participate in a potentially life-changing clinical trial—especially in the rare disease space where every participant matters. Sponsors and CROs must proactively design travel-inclusive and travel-flexible studies that empower, not exclude, patients.

By reducing physical and financial burdens, engaging local partners, and embracing decentralized tools, the rare disease community can move toward more equitable, accessible, and patient-centered clinical research.