🧠 Output-Action Pairing (OAP) Framework in Healthcare #

This guide provides real-world examples of the Output-Action Pairing (OAP) framework: aligning machine learning model outputs with concrete clinical actions to improve care.

📋 OAP Template #

✅ Real-World Examples #

1. Sepsis Prediction #

• Output: High risk of sepsis in next 6 hours
• Action: Alert care team, initiate fluids/labs/antibiotics
• Who acts: Rapid response team (nurses + physicians)
• Why it helps: Early treatment improves survival

2. Readmission Risk Score #

• Output: 30% chance of readmission within 30 days
• Action: Extra discharge planning, follow-up calls, medication check
• Who acts: Care coordinator + pharmacist
• Why it helps: Reduces avoidable readmissions

3. Pneumothorax Detection on Chest X-ray #

• Output: Pneumothorax detected
• Action: Immediate flag to radiologist and ER for review
• Who acts: Radiologist + ER team
• Why it helps: Enables life-saving chest tube intervention

4. COVID-19 Triage #

• Output: High risk of severe COVID progression
• Action: ICU evaluation, enhanced monitoring, begin treatment
• Who acts: Hospitalist or ICU triage physician
• Why it helps: Allocates ICU resources effectively

5. Fall Risk in Hospital #

• Output: High fall risk during admission
• Action: Enable fall precautions (alarms, sitter, etc.)
• Who acts: Nursing team
• Why it helps: Prevents injury and hospital complications

6. Stroke Detection via CT #

• Output: Acute stroke suspected on scan
• Action: Notify neurologist, activate stroke protocol (tPA window)
• Who acts: Radiologist + Stroke Response Team
• Why it helps: Reduces time to brain-saving treatment

🔄 Summary #

The OAP framework ensures that ML predictions translate to action, improving clinical relevance and patient safety. Every model in healthcare should answer:

• What is the output?
• What is the action?
• Who will act on it?
• How does it help the patient?