Risk-Benefit Visualization Tool for Medical Treatment Assessment
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Solution Overview
Problem
Current decision aids for medical treatments are inadequate in simplifying the complex trade-offs between risks and benefits, leading to poor understanding among patients and physicians, particularly in cancer treatment options where toxicity, cost, and inconvenience play significant roles.
Innovation Solution
A communication tool that visualizes medical treatment options using a two-dimensional risk-benefit display, allowing patients to set their preferences and categorize risks and benefits, with an iso-preference boundary to identify preferred treatment options, and dynamic markers indicating uncertainty.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional decision aids are used to present treatment options, then comprehensive information about risks and benefits is provided, but patient understanding and ability to compare options deteriorates due to complexity
Solution Approach 1:
The patent transforms the traditional one-dimensional list of treatment options into a two-dimensional risk-benefit plane. Each treatment option is represented as a point positioned according to its risk level (x-axis) and benefit level (y-axis), enabling visual comparison while preserving comprehensive information about multiple risks and benefits simultaneously.
Solution Approach 2:
The patent introduces an iso-preference boundary line as an intermediary element that translates complex multi-dimensional risk-benefit preferences into a simple visual indicator. This boundary line intersects with treatment option markers to identify preferred options, mediating between the comprehensive data and patient understanding.
2Loss of information
If multiple treatment options with different risks and benefits are presented, then complete treatment information is available, but decision-making complexity increases making it harder to identify preferred options
Solution Approach 1:
The patent organizes multiple treatment options in a two-dimensional risk-benefit space rather than a linear list, allowing simultaneous visualization of multiple risks and benefits for each option. This dimensional transformation reduces decision-making complexity by enabling intuitive visual comparison while maintaining complete treatment information.
Solution Approach 2:
The iso-preference boundary line serves as a computational intermediary that automatically processes the complete treatment information and patient preferences to identify preferred options. This mediator handles the complexity of evaluating multiple treatment options against multiple risks and benefits, presenting simplified results to the user.
3Measurement precision
If detailed risk and benefit data for each treatment option is displayed, then accurate medical information is provided, but visual clarity and ease of comparison deteriorates
Solution Approach 1:
The patent extracts the essential characteristics of each treatment option (risk level and benefit level) and represents them as simplified visual markers in a two-dimensional space. This extraction preserves accurate medical information while dramatically improving visual clarity and ease of comparison by eliminating extraneous details.
Solution Approach 2:
The patent employs visual encoding where treatment option markers and the iso-preference boundary line use color and positioning to convey complex information. The two-dimensional positioning itself acts as a visual encoding scheme that maintains measurement precision while enhancing visual clarity through intuitive spatial relationships.
Data Source
AI summary
A tool for assessing treatment options within a risk-benefit space (plotting risk against benefit) and provides a superimposed boundary indicating patient risk-benefit preference for assessment of these options. The patient risk-benefit preference can be used to identify a preferred treatment option, and interactive controls can be provided to change risk-benefit preference, risk categories, benefit categories, disease type, and the like.