Integrated Multi-Criteria Decision Framework for Medical Treatment Selection
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Solution Overview
Problem
Existing decision-making systems face challenges in effectively evaluating complex medical treatment options by relying on single multi-criteria methods, which limits the ability to incorporate multiple perspectives and adapt to new information, leading to suboptimal choices.
Innovation Solution
An integrated multi-criteria decision framework that combines multiple modules such as decision strategy, balance sheet, ordinal ranking, direct weighting, and Analytic Hierarchy Process (AHP) to facilitate comprehensive evaluation of treatment options, allowing for the incorporation of new information and adaptive decision-making processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single multi-criteria method is used to evaluate treatment options, then the decision support system is simple to implement, but the ability to incorporate multiple perspectives and adapt to new information is limited
Solution Approach 1:
The patent combines multiple multi-criteria decision-making methods (analytic hierarchy process, outranking methods, goal programming, etc.) into a single integrated decision support system. This merging allows the system to incorporate diverse perspectives and adapt to new information by selecting and applying appropriate methods based on the specific decision context, thereby resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The decision support system is designed with universal functionality to handle various types of medical treatment decisions through multiple methodologies. The system can adaptively apply different multi-criteria methods depending on the decision scenario, making it versatile across different medical contexts while maintaining a unified interface for users.
2Reliability
If multiple multi-criteria methods are combined in an integrated framework, then the comprehensiveness of treatment evaluation is improved, but the complexity of the system increases
Solution Approach 1:
The integrated decision support system is segmented into distinct functional modules, each implementing a specific multi-criteria method (AHP module, outranking module, goal programming module, etc.). This segmentation allows the system to maintain comprehensive evaluation capabilities while managing complexity through modular design, where each module can be independently developed, tested, and maintained.
Solution Approach 2:
The patent introduces an intermediary layer that coordinates between multiple multi-criteria methods and the user interface. This intermediary manages the complexity by providing a unified control mechanism that selects and integrates results from different methods, thereby maintaining comprehensiveness while simplifying the user's interaction with the complex integrated framework.
3Ease of operation
If extensive data visualization techniques are used to reduce cognitive effort, then the ease of operation is improved, but the device complexity increases
Solution Approach 1:
The decision support system creates simplified visual representations (copies) of complex treatment option data through multiple visualization techniques including dashboards, graphs, and tables. These visual copies present information in intuitive formats that reduce cognitive effort for users while the underlying complex data processing and multiple criteria evaluations are handled automatically by the system.
Solution Approach 2:
The patent replaces manual cognitive processing of complex treatment data with automated computational systems that perform multi-criteria evaluations and generate visualizations. This substitution of mechanical/computational systems for human cognitive effort simplifies the user's interaction while managing the underlying complexity through algorithmic processing and automated data presentation.
Data Source
AI summary
Integrated multi-criteria decision frameworks disclosed herein can facilitate making good decisions when faced with a complex choice among several alternatives with different combinations of strengths and weaknesses. Some decision support systems using multi-criteria methods can combine multiple multi-criteria methods in a single adaptable decision support intervention. In some embodiments, the framework can include some or all of the following modules: a decision strategy module; a balance sheet module; an interactive decision dashboard module; an ordinal ranking module; a direct weighting module; and an Analytic Hierarchy Process (AHP) module.