Optimization Software Component for Chronic Illness Treatment Plans

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Solution Overview

Problem

Current methods for managing chronic illnesses lack an efficient system for creating personalized treatment plans that optimize treatment options based on user feedback and health professional input, often failing to account for cost and long-term patient responses effectively.

Innovation Solution

A system and method that utilizes a Relational Remedy Database Server, Optimization Software Component, and Treatment Plan Software Component to create and update Individual Treatment Plans through user input, regression analysis, and cost optimization, enabling users to select and modify remedies based on effectiveness and cost, while allowing communication with health professionals and generating targeted advertising.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If current methods for managing chronic illnesses are used, then treatment plans can be created, but they lack personalization and optimization based on user feedback and cost considerations

Engineering Contradiction:

Improvepersonalization of treatment plansVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments the treatment plan creation process into distinct functional modules: a Relational Remedy Database Server for storing and retrieving treatment data, an Optimization Software Component for analyzing user feedback and cost data, and a Treatment Plan Software Component for generating personalized plans. This segmentation allows each component to specialize in specific tasks, improving personalization capabilities while managing system complexity through modular architecture.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system implements continuous feedback loops where user responses to treatments are collected, analyzed by the optimization component, and used to refine and update treatment plans. This feedback mechanism enables dynamic personalization of treatment plans based on actual patient outcomes, cost effectiveness, and evolving medical understanding, directly addressing the need for adaptable treatment approaches.

Inventive Principle:

Principle #23Feedback

2Reliability

If treatment options are expanded to include multiple remedies, then treatment effectiveness can be improved, but cost and complexity increase

Engineering Contradiction:

Improvetreatment effectivenessVSAvoidtreatment plan complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The optimization software component analyzes multiple treatment parameters simultaneously, including remedy effectiveness, cost, patient responses, and interaction effects. By systematically evaluating and adjusting these parameters, the system identifies optimal treatment combinations that maximize effectiveness while controlling complexity through data-driven decision-making rather than trial-and-error approaches.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system creates composite treatment plans that integrate multiple remedies into coordinated combinations. Rather than treating each remedy in isolation, the system analyzes how different treatments work together, optimizing synergistic effects while minimizing redundant or conflicting therapies. This composite approach improves overall treatment effectiveness while managing complexity through systematic integration.

Inventive Principle:

Principle #40Composite materials

3Reliability

If treatment plans are updated frequently based on user feedback, then treatment optimization is improved, but time and resources are consumed

Engineering Contradiction:

Improvetreatment optimizationVSAvoidtime for updates

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary analysis and organization of treatment data in the relational database, pre-structuring information to facilitate rapid optimization updates. By maintaining treatment plans, user profiles, and remedy information in optimized data structures beforehand, the system can quickly process new user feedback and generate updated treatment recommendations without requiring extensive processing time when updates are needed.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The optimization software component operates autonomously to analyze user feedback, evaluate treatment effectiveness, and generate updated treatment plans without requiring manual intervention for each update cycle. This self-service capability automates the optimization process, reducing the time and resources required for frequent updates while maintaining high levels of treatment optimization through continuous automated analysis.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS7827044B2Analytical tool for managing the treatment of chronic illnesses

Publication Date: 2010.11.02 MCCULLOUGH THOMAS J

AI summary

A system and method for creating an individual treatment plan which includes a user interface configured to receive user input and communicate with a Relational Remedy Database Server containing information about chronic illnesses and remedies. The Method and System described herein further utilizes a Treatment Plan Software Component, a Patient Data Update Software Component and an Optimization Software Component which performs a multiple regression analysis to determine an optimal combination of remedies based on user responses to create an Updated Treatment Plan.