Clinical Trial Workflow and Data Integration
This page describes the end-to-end workflow for atopic dermatitis 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 body area photography at the site or home
- AI scoring: Automated ASCORAD calculation
- Report review: Investigator reviews the severity report
- Severity tracking: Longitudinal SCORAD evolution
- 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 | ASCORAD (SCORAD), aEASI (EASI), IGA-AD, or custom composite |
| Body areas | Full body (7–9 perspectives), flexural focus, face only, or custom |
| Subjective components | Pruritus NRS, sleep disturbance NRS collection method |
| Visit schedule | Assessment timepoints aligned with the study calendar |
| Capture model | In-clinic, decentralised (home-based), or hybrid |
| Alert thresholds | Configurable SCORAD 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.
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 (body areas, endpoints, scoring method)
- 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; no personal data (name, date of birth) is stored in the platform.
4. Image capture
The investigator or patient captures photographs of the relevant body areas using the Legit.Health mobile application. The application provides:
- Perspective guidance: Visual silhouettes showing the required body area and angle
- Real-time DIQA quality check: Each image is evaluated for focus, lighting, framing, and resolution
- Immediate feedback: If an image fails quality standards, the user is prompted to recapture with specific guidance
- Confirmation: Once all perspectives pass quality checks, the images are submitted for AI processing
For the standard 7-perspective protocol, the entire capture process takes approximately 3–5 minutes.
5. AI scoring
Once images are submitted, the AI processes them automatically. Processing takes approximately <2 seconds. The system produces:
- Per-area BSA percentage via pixel-level segmentation
- Per-sign intensity scores (0–3) for all six SCORAD signs
- Objective SCORAD component (0–72)
- Total SCORAD when combined with patient-reported subjective components
- DIQA quality score per image
6. Report review
The investigator reviews the severity report directly in the platform. The report includes:
- Objective SCORAD: BSA and intensity breakdown
- Per-area assessment: Segmentation masks and sign scores per body region
- Image quality: DIQA score for each captured image
The investigator can verify that the AI's assessment aligns with their clinical observation. If the images are inadequate, the investigator can recapture and resubmit; only the latest submission for each visit is retained.
7. Severity tracking
For follow-up visits, the platform tracks severity evolution across all assessments:
- SCORAD trajectory: Score evolution from screening to end of study
- Absolute and percentage change from baseline
- Per-sign trends: Which intensity signs are driving improvement or worsening
- BSA change: How the extent of affected area evolves over time
- Protocol adherence monitoring: Verify that assessments are captured at the correct intervals
8. Data export and EDC integration
Assessment results are structured for integration with 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 |
| Total BSA (%) | Affected body surface area |
| Per-sign scores | Erythema, oedema, oozing, excoriations, lichenification, dryness (each 0–3) |
| Objective SCORAD | Computed objective component (0–72) |
| Total SCORAD | Including patient-reported symptoms (0–103) |
| DIQA scores | Per-image quality assessment |
| Severity classification | Mild / Moderate / Severe |
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.
Decentralised and hybrid trial support
Hybrid designs
Some study designs combine investigator-captured and patient-captured images:
- Investigator timepoints: Primary visits (e.g., baseline, month 3, month 6, month 12) where images are captured by trained site personnel at the clinic
- Patient timepoints: Intermediate visits (e.g., monthly check-ins) where the patient captures images at home using the mobile application
The same AI scoring pipeline processes both types of images. DIQA quality control is applied identically, ensuring that patient-captured images meet the same quality standards as investigator-captured images.
Remote patient capture
For fully decentralised protocols:
- Patients download the Legit.Health mobile application
- The app guides them through the capture process with the same perspective silhouettes and DIQA quality checks used at investigator sites
- Captured images are transmitted securely to the platform for AI scoring
- The investigator can review scores remotely
Benefits for sponsors
- Reduced site burden: Fewer in-clinic visits needed for severity assessment
- Increased data frequency: More timepoints without increasing site workload
- Patient convenience: Assessments from home reduce travel burden
- Continuous monitoring: More frequent assessments enable finer-grained treatment response detection
For AD trials, decentralised capture enables patients to photograph their own affected areas at home, reducing clinic visit burden. The DIQA quality gate ensures home-captured images meet the same quality standards as site-captured images.