Clinical Trial Workflow and Data Integration
This page describes the end-to-end workflow for hidradenitis suppurativa severity assessment in a clinical trial using the Legit.Health platform, from protocol design through to EDC data delivery.
Workflow overview
The workflow has two phases: a one-time study setup, and a per-visit cycle that repeats at every assessment.
Study setup (once per study)
- Protocol design: Configure the study with Legit.Health
- Site setup: Deploy the platform to investigator sites
Per-visit cycle (each assessment)
- Patient enrolment: Register the patient in the platform
- Image capture: Photography of the affected regions at the site by the study staff, with real-time DIQA quality control
- AI screening and investigator review: The AI detects the lesions and gives a preliminary IHS4, the investigator reviews it after examining the patient, and IHS4 and HiSCR are recalculated from the investigator's annotations
- Data export: Structured delivery to the EDC system
1. Protocol design
Before the study begins, Legit.Health works with the sponsor or CRO to configure the study protocol:
| Configuration | Options |
|---|---|
| Scoring system | Automated IHS4, lesion counts by type (inflammatory nodules, abscesses, draining tunnels), or both |
| Response endpoint | HiSCR against the patient's baseline visit |
| Capture scope | Affected regions only; see the imaging protocol |
| Capture device | Clinical camera or smartphone |
| Visit schedule | Assessment timepoints aligned with the study calendar |
| Alert thresholds | Configurable IHS4 change thresholds for automated notifications |
A study-specific investigator manual is generated for each trial, providing site personnel with step-by-step instructions, example images, and a knowledge test to confirm training.
The scoring model version is locked at study initiation. No mid-study model updates occur, so every patient is scored by the same validated model and endpoint integrity is preserved across the trial. Any model update requires full re-validation before deployment.
2. Site setup
The Legit.Health clinical trials platform is deployed as a web application accessible from any browser. Each investigator site receives:
- Login credentials for all study personnel
- Pre-configured protocol (capture scope, endpoints, scoring method)
- Investigator manual (digital, accessible from the platform)
- Training resources and knowledge test
No dedicated hardware is required: sites capture with a clinical camera or with a smartphone, according to the imaging quality the protocol specifies.
3. Patient enrolment
After enrolling a patient in the study per the clinical protocol, the investigator creates the patient record in the Legit.Health platform. Each patient is identified by a study-specific pseudonymised identifier; no personal data (name, date of birth) is stored in the platform.
4. Image capture
Images are always taken at the investigator site by a physician or study nurse, never by the patient. Hidradenitis suppurativa affects intimate areas such as the axillae, the groin and the perianal region, and the disease needs an in-person clinical examination, so capture is part of the site visit.
Only the regions with active lesions are photographed. There is no full-body capture set: a region without lesions at a visit is not photographed at that visit. The regions, framing and capture sequence are set out in the imaging protocol. The application provides:
- Region guidance: the anatomical region and angle to capture for each affected area
- Real-time quality control: the DIQA quality gate checks each image at capture and flags substandard images for immediate recapture, so only adequate images proceed to scoring
Photographs are anonymised before they are stored or exported, so no re-identifiable data leaves the site. See anonymization.
5. AI screening and investigator review
Once images are submitted, the AI analyses them in seconds and shows the investigator its detections and a preliminary IHS4 at the visit, with no central reader.
The investigator then reviews the detections after examining the patient, and the IHS4 and HiSCR are recalculated from the annotations; see investigator review. Once the investigator confirms the assessment, the report contains:
- Lesion counts by type: inflammatory nodules, abscesses and draining tunnels, as confirmed by the investigator
- IHS4 score with its severity category (mild, moderate or severe)
- Annotated images: each photograph with colour-coded bounding boxes around the confirmed lesions
- DIQA quality score per image
If any image is inadequate, the investigator can recapture and resubmit; only the latest submission for each visit is retained.
From the follow-up visits onward, the same report tracks how severity evolves across the study.
The platform stores the baseline counts and computes HiSCR automatically at every follow-up visit, from the same confirmed counts that produce the IHS4, so there is no reconciliation step between the raw counts and the response derivation.
6. Data export and EDC integration
Where the in-platform report (step 5) is the investigator's human-readable view, the export is a structured, analysis-ready dataset built to load straight into the sponsor's EDC. Each assessment is delivered as column-level records, not a re-rendering of the report.
Exported data fields
Field names below are representative; the exact schema is agreed during study setup.
| Group | Fields |
|---|---|
| Identifiers | study_code, site_code, subject_code, visit_code, diagnostic_report_id, timestamp, condition_code |
| Source images | Original image path and annotated detection image path for every capture, so each count is traceable to the source photograph |
| Lesion counts | Inflammatory nodules, abscesses and draining tunnels, per visit |
| Scores | IHS4 (nodules × 1 + abscesses × 2 + draining tunnels × 4) and severity category, plus the per-image quality score |
| Response | HiSCR achievement per visit, with the change in abscess and inflammatory nodule count from baseline |
Every field is delivered per visit, so the same structure supports both single-visit analysis and longitudinal review.
Integration methods
- API-based: Automated data flow from the Legit.Health platform to the sponsor’s EDC system via RESTful API
- CSV export: Structured CSV files for manual import into EDC systems
- CRF field mapping: Data fields pre-mapped to the sponsor’s Case Report Form structure, configured during protocol design
- QuantifiCare platform integration: For studies using the combined QuantifiCare + Legit.Health solution, scoring data flows through QuantifiCare’s platform to the sponsor’s data management system
All exported data is structured for direct mapping to CRF fields in standard EDC systems.
The integration is API-based and system-agnostic; it works with any major EDC system. Export formats include RESTful API, CSV/Excel, and structured JSON.