Rules-Based Medical Information Management System
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Solution Overview
Problem
Current healthcare information management systems fail to provide real-time or near real-time information transfer and data-intensive services required for modern healthcare decisions, relying on legacy algorithms that are not sufficient for complex and time-sensitive hospital operations.
Innovation Solution
A rules-based management system utilizing artificial intelligence and cloud-computing algorithms to control, store, access, and disseminate medical information through a cloud network, comprising a rule repository, rule query language engine, rule processing engine, and interface for task execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If legacy algorithms are used for information transfer, then system simplicity is maintained, but real-time information transfer capability is insufficient
Solution Approach 1:
The patent replaces traditional mechanical legacy algorithms with an intelligent rules-based management system that uses artificial intelligence and cloud-computing algorithms. This substitution enables real-time information transfer by allowing the system to dynamically process and respond to medical information without being constrained by predetermined fixed algorithms, thus resolving the contradiction between transfer speed and system complexity.
Solution Approach 2:
The system implements dynamic rule processing where rules can be added, modified, or removed based on changing healthcare requirements. The rule repository and processing engine allow the system to adapt its behavior in real-time, enabling fast information transfer while maintaining manageable complexity through flexible, dynamic configuration rather than static hard-coded algorithms.
2Productivity
If legacy messaging systems are used, then system simplicity is maintained, but data-intensive and time-sensitive demands cannot be satisfied
Solution Approach 1:
The rules-based management system serves multiple functions within a single unified platform: it stores medical information, processes rules, transfers data, and supports complex healthcare operations. This multi-functional approach enables the system to handle data-intensive and time-sensitive demands while avoiding the need for multiple separate legacy systems, thus improving productivity without proportionally increasing complexity.
Solution Approach 2:
The patent introduces a cloud network as an intermediary layer between healthcare providers and patients. This intermediary enables efficient data-intensive operations by providing centralized storage and processing capabilities, allowing the system to meet complex demands without requiring each local system to handle all processing independently, thereby improving productivity while distributing complexity across the network.
3Reliability
If real-time information transfer is implemented, then healthcare decision quality is improved, but system complexity increases
Solution Approach 1:
The system implements feedback mechanisms where the rule processing engine continuously monitors information flow and adjusts rule application based on outcomes. This feedback loop ensures high-quality healthcare decisions by validating information transfers and applying appropriate rules dynamically, while the automated nature of the feedback reduces the complexity burden that would otherwise require manual oversight.
Data Source
AI summary
A rules-based management system includes a rule repository to store a plurality of rules relating to medical information, a rule query language engine to generate a query based on a received signal and to search the rule repository based on the query, and a rule processing engine to formulate an instruction based on one or more rules produced by the search of the rule repository and to generate a signal based on the instruction. The system further includes an interface to a cloud network connected to a plurality of doctors, nurses, technicians, and/or other personnel or patients.