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 clinical trial workflow consists of eight stages:
- Protocol design: Configure the study with Legit.Health
- Site setup: Deploy the platform to investigator sites
- Patient enrollment: Register patients in the platform
- Image capture: Guided anatomical region photography at the site
- AI scoring: Automated AIHS4 calculation
- Report review: Investigator reviews the lesion detection report
- Severity tracking and alerts: Longitudinal IHS4 monitoring with automated notifications
- Data export: Structured delivery to EDC systems
1. Protocol design
Before the study begins, Legit.Health works with the sponsor or CRO to configure the study protocol:
| Configuration | Options |
|---|---|
| Scoring system | AIHS4 (IHS4), IGA-HS, Hurley staging, or custom composite |
| Anatomical regions | Full anatomical, axillary focus, or custom region set |
| Visit schedule | Assessment timepoints aligned with the study calendar |
| Alert thresholds | Configurable IHS4 change thresholds for automated notifications |
| Anonymization | Region-aware anonymization for sensitive body areas |
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.
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 (anatomical regions, endpoints, alert thresholds)
- Investigator manual (digital, accessible from the platform)
- Training resources and knowledge test
No hardware installation is required; investigators use their existing smartphones for image capture.
3. Patient enrollment
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.
4. Image capture
The investigator captures close-up photographs of each affected anatomical region using the Legit.Health mobile application. The application provides:
- Region guidance: Visual silhouettes showing the required capture angle for each anatomical area
- Real-time DIQA quality check: Each image is evaluated for focus, lighting, and framing
- Immediate feedback: If an image fails quality standards, the investigator is prompted to recapture
- Confirmation: Once all required regions pass quality checks, the images are submitted for AI processing
5. AI scoring
Once images are submitted, the AI processes them automatically. Processing takes approximately <2 seconds. The system produces:
- Per-region lesion counts: Papules/nodules, abscesses, fistulae per anatomical area
- Per-region IHS4 contribution: Weighted lesion score per region
- Global AIHS4 score: Sum across all submitted regions
- Hurley stage estimate: Derived from lesion distribution
- Annotated images: Each photograph with colour-coded bounding boxes around detected lesions
- DIQA quality score: Per image
6. Report review
The investigator reviews the lesion detection report directly in the platform. The report includes:
- Global AIHS4 score with severity classification (Mild / Moderate / Severe)
- Per-region breakdown: Lesion counts by type and weighted IHS4 contribution per anatomical area
- Annotated images: Colour-coded bounding boxes distinguishing papules/nodules, abscesses, and fistulae
- Image quality: DIQA score for each captured image
The investigator can verify that the AI's detections align with their clinical observation. If images are inadequate, the investigator can recapture and resubmit.
7. Severity tracking and automated alerts
For follow-up visits, the platform tracks severity evolution across all assessments:
Longitudinal tracking
- AIHS4 score evolution over time with visual comparison to baseline
- Absolute and percentage change from baseline at each visit
- Per-lesion-type trends: How nodule, abscess, and fistula counts change over time
- Severity classification changes: Transitions between Mild / Moderate / Severe
Automated alert system
The system can be configured to trigger automated email notifications:
| Setting | Detail |
|---|---|
| Trigger | IHS4 increase above configurable threshold from baseline |
| Recipient | Site investigator email |
| Response | Investigator confirms finding clinically; escalates per protocol |
8. Data export and EDC integration
Assessment results are structured for export to the sponsor's EDC system.
Exported data fields
| Field | Description |
|---|---|
| Patient ID | Pseudonymised study identifier |
| Visit ID | Visit number or scheduled timepoint |
| Timestamp | UTC timestamp of capture and processing |
| Nodule count | Total papules/nodules detected |
| Abscess count | Total abscesses detected |
| Fistula count | Total draining fistulae detected |
| Global AIHS4 score | Weighted composite (N×1 + A×2 + F×4) |
| Severity classification | Mild / Moderate / Severe |
| Hurley stage | I / II / III estimate |
| DIQA scores | Per-image quality assessment |
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 (Medidata Rave, Veeva Vault CDMS, Oracle InForm, etc.).
The integration is API-based and system-agnostic; it works with any EDC system (Medidata Rave, Oracle InForm, Veeva Vault EDC, and others). Export formats include RESTful API, CSV/Excel, and structured JSON.