Adaptive Hanging Protocol System for Radiology Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing hanging protocols in Picture Archiving and Communication Systems (PACS) are static and unable to adapt to user preferences, leading to inefficiencies in radiologists' image review processes, as they do not account for individual productivity and efficiency variations among users.
Innovation Solution
A method to monitor usage information and determine productivity factors for hanging protocols, recommending protocol changes or selections based on the efficiency of more productive users to enhance the reading efficiency of less efficient users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If static hanging protocols are used, then system simplicity is maintained, but user productivity and efficiency deteriorate due to inability to adapt to individual preferences
Solution Approach 1:
The patent implements dynamic hanging protocols that automatically adapt to individual radiologist preferences and behaviors. The system monitors user interactions with image displays, tracks which layouts and configurations are most frequently used, and dynamically adjusts protocol recommendations to match individual working styles, thereby improving productivity without requiring manual configuration
Solution Approach 2:
The system performs self-configuration by automatically analyzing usage patterns and generating optimized hanging protocol recommendations without requiring manual input from radiologists. The system serves itself by learning from collective user behavior data and autonomously adapting to individual preferences, eliminating the need for complex manual setup while maintaining simplicity
2Ease of operation
If individualized protocol customization is enabled, then user efficiency improves, but system complexity and difficulty of operation increase
Solution Approach 1:
The system continuously monitors and tracks radiologist interactions with hanging protocols, collecting data on which layouts, image arrangements, and display configurations are most effective. This feedback loop enables the system to learn from actual usage patterns and provide personalized protocol recommendations that naturally align with user preferences, making customization effortless rather than complex
Solution Approach 2:
The system automatically adjusts hanging protocol parameters such as image layout, display orientation, and sequence based on aggregated usage data. By dynamically changing these parameters in response to observed behavior patterns, the system provides personalized optimization without requiring users to manually configure complex settings, thereby maintaining ease of operation
3Adaptability or versatility
If static hanging protocols are used, then implementation simplicity is maintained, but adaptability to user preferences and productivity variations deteriorates
Solution Approach 1:
The system serves multiple functions within a unified framework: it monitors user behavior, analyzes collective patterns, generates personalized recommendations, and adapts protocols dynamically. This multi-functional approach enables the system to provide customized adaptability to each radiologist while sharing common infrastructure and algorithms, thereby achieving versatility without proportionally increasing implementation complexity
Data Source
AI summary
Embodiments of the presently described technology provide a method for adapting a hanging protocol based on an efficiency of use. The method includes monitoring usage information for a hanging protocol, determining a productivity factor based on an efficiency of a first user during a reading of an imaging study, and recommending at least one of a hanging protocol selection and a hanging protocol change to a second user based on the productivity factor. The usage information includes at least one of a selection of a hanging protocol and a change to the hanging protocol by a first user during the reading of the imaging study.