Automated Medical Device Assignment via Patient Parameter Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional methods for scheduling patients to medical imaging devices, such as MRI scanners, are inefficient and require skilled personnel, leading to suboptimal patient treatment, scanner utilization, and safety-critical situations due to the complexity of information needed and institutional rules that do not optimize scanner utilization.
Innovation Solution
A computer-implemented method using a scheduler agent device that receives patient parameters and determines suitable medical devices based on device parameters, optimizing the assignment of patients to medical devices for improved diagnosis, scanner utilization, and timely examinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional manual scheduling methods are used, then scheduling decisions can be made with human judgment, but the process becomes time-consuming and requires highly qualified personnel
Solution Approach 1:
The system enables automated self-service scheduling where the scheduling algorithm independently evaluates patient requirements against device capabilities and availability without human intervention. The scheduler automatically matches patients to appropriate medical devices based on predefined criteria, eliminating the need for highly qualified personnel to manually perform scheduling tasks while maintaining high accuracy through systematic evaluation of multiple parameters simultaneously.
Solution Approach 2:
The patent replaces the mechanical human decision-making process with an automated computer-based scheduling system. The system uses algorithmic logic to evaluate patient parameters, device capabilities, and availability constraints, substituting human judgment with systematic computational analysis that processes multiple factors simultaneously and delivers consistent, reproducible scheduling decisions without time loss.
2Reliability
If complex information about scanner infrastructure is gathered manually, then comprehensive scheduling decisions can be made, but the process becomes significantly time-consuming
Solution Approach 1:
The system performs preliminary actions by pre-collecting and storing comprehensive information about medical device capabilities, availability, and operational parameters in a centralized database before scheduling is needed. Device metadata including hardware specifications, software licenses, imaging modalities, and availability windows are预先 gathered and structured, enabling the scheduler to quickly retrieve and evaluate relevant information without time-consuming manual data collection during the scheduling process.
Solution Approach 2:
The patent introduces an intermediary scheduling system that acts as a mediator between patient requirements and device capabilities. This intermediary automatically retrieves and processes complex infrastructure information from multiple sources, evaluates compatibility between patient needs and device features, and resolves conflicts according to predefined rules, thereby simplifying the information gathering process while maintaining comprehensive scheduling decisions.
3Ease of operation
If institutional rules are used for patient planning, then scheduling can be simplified, but scanner utilization becomes suboptimal
Solution Approach 1:
The system implements dynamic scheduling that adapts to changing conditions in real-time. Rather than applying static institutional rules, the scheduler continuously evaluates current device availability, patient urgency, and utilization metrics, adjusting assignments dynamically to optimize scanner usage. The system can reassign patients to different devices based on real-time conditions, ensuring high utilization while maintaining operational simplicity through automated decision-making.
Solution Approach 2:
The patent employs parameter-based optimization where the scheduling algorithm adjusts multiple parameters simultaneously including device availability windows, patient priority levels, utilization thresholds, and compatibility constraints. By systematically varying and optimizing these parameters, the system achieves both simplified operation through automated parameter management and optimal scanner utilization through multi-criteria evaluation, overcoming the limitations of rigid institutional rules.
4Reliability
If multiple device parameters are considered for assignment, then patient-specific requirements are met, but the assignment process becomes more complex
Solution Approach 1:
The system segments the complex assignment process into distinct modular evaluation stages. Each stage assesses specific parameters such as hardware compatibility, software license availability, imaging modality match, and temporal availability independently. This segmentation allows the scheduler to systematically evaluate multiple device parameters without overwhelming complexity, as each parameter group is processed separately and combined to produce the final assignment decision, maintaining both comprehensiveness and manageability.
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
The present invention relates to a technique for assigning a medical device from a group of medical devices to an examination of a patient.A procedure is implemented in a scheduler agent device (200) and comprises receiving, from a patient agent device (402), a usage request containing patient parameters for the examination of a patient using a medical device from the group; determining the suitability of at least one medical device from the group for the examination based on the patient parameter(s) and one or more device parameters; assigning a medical device determined to be suitable to the usage request based on the patient parameter(s) and device parameters; sending a notification to the patient agent device (402) regarding the assignment; and sending a notification to a device agent device (300-1; 300-2; 300-3; 300-4) associated with the assigned medical device.