Accelerating Clinical Trial Site Feasibility Data Collection with Formize Web Forms

Clinical research teams spend a disproportionate amount of time gathering, validating, and consolidating site feasibility information. Traditional spreadsheets and email threads create bottlenecks, errors, and delays that push study start dates farther out. Formize Web Forms offers a modern, low‑code solution that transforms the feasibility workflow into a fast, auditable, and collaborative process.

In this article we explore why site feasibility is a critical path activity, how Formize eliminates the pain points of legacy methods, and step‑by‑step guidance for building a production‑ready feasibility form that complies with GCP and data‑privacy regulations. We also dive into analytics, integration options, and a realistic ROI model that demonstrates measurable time‑to‑site benefits.

Why Site Feasibility is a Bottleneck

A typical feasibility cycle can stretch from 4 to 12 weeks. Each week of delay translates to lost patient enrollment potential and higher operational costs. Automation is no longer optional – it is a competitive advantage for sponsors and Contract Research Organizations (CROs) alike.

How Formize Web Forms Solves the Problem

Formize’s web‑based form builder provides:

• Conditional logic – show or hide fields based on prior answers (e.g., only request IRB documentation if the site reports a vulnerable population).
• Real‑time response analytics – dashboards that display completion rates, missing data flags, and trend charts.
• Secure data handling – TLS encryption, role‑based access, and GDPR‑ready (GDPR) data retention settings.
• One‑click PDF export – generate a consolidated feasibility report that matches sponsor templates.
• API and Zapier connectors – feed data into Clinical Trial Management Systems (CTMS) or data‑warehouse platforms without custom code.

These capabilities turn a fragmented email‑and‑Excel process into a single, auditable, and scalable workflow.

Designing the Ideal Feasibility Form

Below is a recommended section layout. Adjust wording to match therapeutic area specifics.

1. Site Identification
   Site name, ID, address, and contact person.
2. Infrastructure Overview
   Number of beds, ICU capacity, imaging equipment, pharmacy capabilities.
3. Staffing & Experience
   Principal Investigator (PI) CV upload, number of research nurses, prior trial experience.
4. Patient Population
   Estimated eligible patients per month, disease prevalence, recruitment channels.
5. Regulatory Status
   IRB/EC approval status, pending submissions, past audit findings.
6. Budget & Costs
   Standard per‑patient fees, overhead rates, availability of grant funding.
7. Risk Assessment
   Potential barriers (e.g., competing studies, supply chain limitations).

Conditional Logic in Action

  flowchart TD
    A["Start Form"] --> B["Site Identification"]
    B --> C["Infrastructure Overview"]
    C --> D["Staffing & Experience"]
    D --> E{"Does site have PI CV?"}
    E -- Yes --> F["Upload PI CV"]
    E -- No --> G["Provide reason for missing CV"]
    F --> H["Patient Population"]
    G --> H
    H --> I["Regulatory Status"]
    I --> J{"IRB approved?"}
    J -- Yes --> K["Upload IRB approval letter"]
    J -- No --> L["Enter expected approval date"]
    K --> M["Budget & Costs"]
    L --> M
    M --> N["Risk Assessment"]
    N --> O["Submit"]

The diagram above illustrates a typical branch where the form dynamically requests a PI CV only if the user indicates that it is available. Such logic reduces friction and improves completion rates.

Implementation Blueprint

Sample API Payload (JSON)

{
  "site_id": "US-0045",
  "pi_name": "Dr. Jane Smith",
  "beds": 250,
  "icr_capacity": 20,
  "eligible_patients_per_month": 15,
  "irb_status": "Pending",
  "expected_irb_approval": "2025-04-15",
  "budget_per_patient": 1450,
  "risk_flags": ["Competing trial", "Limited pharmacy"]
}

Sending this payload to your CTMS endpoint (https://ctms.example.com/api/feasibility) can be achieved with Formize’s native webhook configuration—no additional middleware required.

Ensuring Data Quality and Security

• Field validation – numeric ranges for bed counts, email format checks for contact fields, mandatory file types (PDF, DOCX) for CVs.
• Duplicate detection – enable “Unique field” on site ID to prevent multiple submissions from the same location.
• Access control – grant “Viewer” rights to sponsor analysts, “Editor” rights to site coordinators, and “Admin” rights to the feasibility manager.
• Encryption at rest – Formize stores all uploaded files in AES‑256 encrypted buckets; encryption keys rotate every 90 days.
• Audit trail – every change (field edit, status update) creates an immutable log entry searchable by date, user, and action type.

Measuring ROI

Assuming an average labor cost of $60 / hour, the direct cost saving per study is $5,100. When multiplied across a portfolio of 20 studies per year, the annual net benefit exceeds $100 k, well beyond the subscription cost for Formize Business tier.

Best Practices & Tips

1. Start small – pilot with a single therapeutic area before scaling.
2. Use pre‑filled reference data – pull country‑specific regulatory codes via API to reduce manual entry.
3. Leverage conditional PDFs – auto‑generate a one‑page executive summary for senior sponsors.
4. Set up automated reminders – Formize can send SMS or email nudges after 7 days of inactivity.
5. Regularly review analytics – adjust question wording if a particular field shows a high drop‑off rate.

Future Enhancements

• AI‑driven field suggestions – integrate a language model to suggest realistic patient recruitment numbers based on historical data.
• Embedded e‑signatures – allow sites to sign regulatory attestations directly within the form.
• Multilingual support – auto‑translate the form interface while preserving field logic.

By continuously iterating on these capabilities, sponsors can keep their feasibility pipelines agile and future‑proof.

See Also

• Formize Web Forms Documentation – official builder guide and API reference.
• NIH Guidance on Clinical Trial Site Selection – regulatory considerations for feasibility studies.
• GCP Overview – FDA – Good Clinical Practice standards and audit expectations.