AI Interruption Handling for Radiology Workstations
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Solution Overview
Problem
Radiologists face frequent interruptions during radiology readings, which disrupt their concentration and productivity, affecting accuracy and throughput, and ultimately impacting patient wait times and health outcomes.
Innovation Solution
A radiology request monitoring system that intercepts communication requests, classifies them, and routes them to appropriate agent queues or AI-enabled dialog systems for automated resolution, minimizing interruptions and prioritizing requests based on modality, type, and urgency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radiologists handle communication requests directly, then patient care and clinical support are maintained, but radiologist productivity and reading accuracy deteriorate due to frequent interruptions
Solution Approach 1:
The patent introduces an AI-powered virtual assistant as an intermediary between clinicians and radiologists. This assistant intercepts communication requests, performs initial triage using natural language processing, and routes appropriate requests to radiologists while filtering out routine inquiries. The system maintains reliable patient care support while shielding radiologists from disruptive interruptions during reading sessions.
Solution Approach 2:
The system enables self-service through automated request handling where the AI assistant independently manages communication triage, scheduling, and routing without requiring radiologist intervention for each request. The radiologist's workstation automatically receives only the most critical notifications, allowing radiologists to serve themselves by minimizing exposure to non-urgent communications while maintaining comprehensive patient care coverage.
2Ease of operation
If radiologists remain continuously available for communications, then clinical support responsiveness is improved, but reading concentration and diagnostic accuracy worsen
Solution Approach 1:
The AI assistant performs preliminary actions by pre-processing all communication requests before they reach the radiologist. It conducts initial assessments, categorizes requests by urgency and type, and prepares summarized notifications. This preliminary triage ensures that when radiologists do engage with communications, they receive pre-filtered, high-value information that requires minimal cognitive switching, thereby maintaining both responsiveness and diagnostic accuracy.
Solution Approach 2:
The system implements periodic action by batching communication notifications and presenting them to radiologists at scheduled intervals rather than requiring immediate response to each interruption. The AI assistant monitors incoming requests and groups them into periodic update cycles, allowing radiologists to maintain concentration while still receiving regular, organized communication updates that preserve clinical support responsiveness.
3Adaptability or versatility
If all communication requests are routed to radiologists, then comprehensive request resolution is achieved, but system complexity and radiologist workload increase
Solution Approach 1:
The patent applies segmentation by dividing the communication request handling system into distinct functional modules: an AI-powered virtual assistant for initial interception and natural language processing, a triage engine for categorization, a routing system for distribution, and a radiologist workstation for final resolution of critical requests. This segmented architecture achieves comprehensive request resolution while distributing system complexity across multiple specialized components rather than concentrating all functions at the radiologist level.
Data Source
AI summary
A non-transitory computer readable medium (26) stores instructions executable by at least one electronic processor (20) to perform a request resolution method (100). The method includes: intercepting (102) communication requests (31) directed to a radiology department; classifying (104) the communication requests; assigning (106) the communication requests to agent queues of a plurality of agent queues (40) based on at least the classifications of the communication requests; and routing (108) the communication requests assigned to each agent queue to a request resolution agent (50) corresponding to the agent queue.