Chronic Illness Care Decision Support System
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Solution Overview
Problem
Current healthcare systems face challenges in managing chronic illnesses due to fragmented and labor-intensive clinical decision-making, particularly for high-risk patients with multiple co-morbidities, leading to incomplete or inaccurate care and cost-benefit analyses that do not accurately reflect individual patient needs.
Innovation Solution
A computerized system that integrates a medical professional module, health coach module, patient module, and public health module, utilizing decision support algorithms, health monitoring data, and communication tools to provide comprehensive care support, including medication alerts, treatment compliance guidance, and cost-benefit analysis, accessible through a network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If clinicians rely on memory and manual reference sources for decision-making, then flexibility in care delivery is maintained, but information accuracy and completeness deteriorate
Solution Approach 1:
The patent introduces an intermediary computer-based decision support system that mediates between the clinician and the vast amount of medical information. The system includes a knowledge base, retrieval mechanisms, and display interfaces that automatically provide accurate, complete, and up-to-date information during clinical encounters, eliminating the need for clinicians to rely on memory or manually search multiple reference sources.
2Measurement precision
If comprehensive patient data is collected and analyzed, then care accuracy improves, but information processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-processing and organizing vast amounts of patient data, medical knowledge, and research information into structured databases and knowledge bases before clinical encounters. The system pre-retrieves relevant information based on patient profiles and pre-computes decision support recommendations, so that during actual clinical encounters, information is instantly available without requiring real-time data processing or analysis.
Solution Approach 2:
The patent replaces manual mechanical information processing with automated computer-based systems. Instead of clinicians manually searching through medical literature, databases, and reference sources, the system uses automated retrieval mechanisms, artificial intelligence algorithms, and computer processing to quickly access, analyze, and present relevant patient information and decision support recommendations, dramatically reducing processing time while maintaining high accuracy.
3Loss of information
If multiple reference sources are consulted during clinical encounters, then decision completeness improves, but encounter time increases
Solution Approach 1:
The patent merges multiple disparate reference sources, medical databases, research literature, and decision support tools into a single integrated computer-based system. The system combines information from various sources through unified search and retrieval mechanisms, presenting consolidated, relevant information to the clinician in one location rather than requiring consultation of multiple separate references, thereby maintaining decision completeness while improving encounter efficiency.
Solution Approach 2:
The patent creates a universal decision support system that performs multiple functions simultaneously: it provides information retrieval, knowledge application, decision recommendation, and continuous learning capabilities. This multi-functional system replaces the need for clinicians to switch between multiple specialized reference sources, as a single system handles all information needs throughout the clinical encounter, improving both completeness and efficiency.
4Measurement precision
If cost-benefit analyses are performed for each treatment decision, then resource allocation accuracy improves, but decision-making complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing cost-benefit analysis parameters, treatment guidelines, and resource allocation recommendations in the decision support system before clinical encounters. The system pre-processes economic data, insurance coverage information, and treatment cost structures, so that during actual decision-making, the system can instantly retrieve and present relevant cost assessments without requiring complex real-time calculations, thereby improving accuracy while reducing decision-making complexity.
Data Source
AI summary
In one aspect, the present invention relates to a computerized system programmed for providing care support to at least one patient having at least one chronic illness. In one embodiment, the system includes a medical professional module adapted for receiving, storing, and providing data in communication with at least one medical professional at the point of care, a health coach module adapted for receiving, storing, and providing data in communication with the at least one patient and at least one health coach, a patient module adapted for receiving, storing, and providing data in communication with the at least one patient, and, a public health module adapted for receiving, storing, and providing data in communication with at least one research professional. Each of the medical professional module, health coach module, patient module, and public health module is operatively associated with a corresponding one of the at least one medical professional, at least one health coach, at least one patient, and at least one research professional through a network.