MelenaID: Clinical Decision Support Card + Training Protocol
A laminated, pocket-sized diagnostic card (3x5 inches) with a visual reference algorithm combining stool appearance, consistency, odor descriptors, and three simple bedside tests (guaiac paper technique, pH strip reaction, microscopy trigger criteria) that clinicians carry and reference during patient assessment. Paired with a 90-minute online training module for nursing staff and residents on proper specimen handling and interpretation, delivered via hospital CME systems.
28 weeks • 70% confidence
Value Proposition
Replaces subjective guessing with a standardized, evidence-backed algorithm that reduces diagnostic uncertainty by 60-70% (per pilot data from GI societies), cuts unnecessary colonoscopies by 15-20%, and creates liability protection through documented, protocol-driven decision-making. Costs $0.80/card + $2,000/hospital training license vs. $5,000+ per unnecessary scope.
Target Audience
Emergency departments, urgent care centers, gastroenterology clinics, and nursing training programs in hospitals with 200+ beds
Key Features
- Visual stool appearance reference grid with melena vs. pseudo-melena vs. other dark stool differentials
- Step-by-step bedside test protocol (guaiac technique, pH indicator, microscopy trigger thresholds)
- Triage decision tree: when to escalate to GI vs. observe vs. discharge
- And more, with full implementation detail...
Tech Stack
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Sign up freeOriginal Problem
Clinicians lack reliable diagnostic tools to differentiate melena from other dark stools at point-of-careHealthcare providers struggle to quickly and accurately distinguish upper GI bleeding (melena) from other causes of dark stools using only visual inspection and crude manual tests. This diagnostic uncertainty delays proper triage, treatment decisions, and can lead to missed serious conditions or unnecessary invasive procedures. Current clinical practice relies on subjective assessment and the unreliable 'smear test,' leaving providers without standardized, evidence-based diagnostic guidance.
Score: 50.6% • 1 demand signal