AI Patient Request Routing for Nurse Workload Segmentation
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Solution Overview
Problem
Existing patient request systems in medical facilities lack efficient allocation of personnel to non-medical requests, leading to nurse burnout and potential delays in addressing genuine emergencies due to the lack of intelligent routing and customization.
Innovation Solution
An AI-based system that analyzes patient requests and routes them to appropriate support team members based on location, urgency, request type, and sender, while allowing for customization and bundling of commands to optimize workflows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If nurses handle all patient requests including non-medical requests, then patient service coverage is comprehensive, but nurse burnout increases and response time to emergencies deteriorates
Solution Approach 1:
The system segments patient requests into different categories (medical vs. non-medical) and routes them to different personnel. Non-medical requests are directed to support staff while medical requests go to nurses, enabling specialized handling and preventing nurse burnout from routine tasks.
Solution Approach 2:
An AI-based request management system acts as an intermediary between patients and staff. The system automatically analyzes requests, determines urgency and type, and routes them to appropriate personnel, eliminating the need for nurses to manually triage every request.
2Device complexity
If simple indication systems are used for patient requests, then system complexity is low, but intelligent routing and customization capabilities are insufficient
Solution Approach 1:
The system provides self-service capabilities where patients can submit various types of requests through multiple channels (voice, text, buttons). The AI system automatically processes these requests without requiring complex manual intervention, achieving intelligent routing through automated analysis.
Solution Approach 2:
The system changes parameters such as request type, urgency level, and sender identity to determine routing decisions. By analyzing multiple parameters of each request, the system achieves intelligent routing while maintaining manageable complexity through structured parameter evaluation.
3Productivity
If nurses are diverted to handle non-medical requests, then support for routine tasks is improved, but availability for genuine medical emergencies deteriorates
Solution Approach 1:
The system segments tasks by medical priority, ensuring that only genuine medical emergencies are routed to nurses. Non-medical and routine requests are handled by support staff, maintaining nurse availability for critical situations while improving overall routine task productivity.
Solution Approach 2:
The system provides feedback mechanisms where support staff can escalate requests that require medical attention back to nurses. This ensures that nurses remain available for emergencies while still benefiting from support staff handling routine tasks, with automatic feedback loops maintaining appropriate care levels.
Data Source
AI summary
A system for managing requests and workflows for patients in a medical facility includes receiving requests from different patients through voice commands or through selection via a computer application. An artificial intelligence module automatically interprets the requests from each patient and routes the requests to appropriate personnel depending on the contents of the request. The system is able to utilize profiles of support team members in the medical facility noting particularly talent, expertise, and time for each support team member in order to route requests and build teams for particular purposes. The system is also able to include a financial incentive system for encouraging personnel to complete particular requests for patients and includes gamification elements including leaderboard functionality.