Problem
Manual review of patient health declarations is time-consuming, inconsistent, and risks missing critical red flags.
How to automate this process using Arkus
This workflow standardizes the evaluation of patient-reported data by applying clinical logic and guideline-based rules. It ensures consistent risk assessment, early detection of red flags, and clear, explainable triage outcomes.
Input
A new health declaration:
- Free-text or structured patient data
- Symptoms, medical history, medications, allergies, and vitals.
- Other relevant case information
AI Processing
- Extracts and structures clinical information
- Performs guideline-based risk assessment
- Detects red flags
- Classifies severity level
Output
A structured report:
- Risk score (low/moderate /high)
- Triage recommendation (self-care, GP, specialist, emergency)
- Transparent reasoning summary
How to customize it for your needs
- Plug in local clinical guidelines
- Customize triage logic
- Add specialty-specific modules
- Adjust risk thresholds
- Enable multilingual support
Example Scenario
Patient reports:
- Chest tightness
- Shortness of breath
- History of hypertension
AI Processing
Structured report:
- High cardiovascular risk flag
- Immediate emergency referral
- Explanation of detected red flags