Asthma Therapy Regimen Determination System
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Solution Overview
Problem
Individuals with asthma often fail to correctly monitor and treat their symptoms and conditions without proper guidance, leading to inadequate management of their asthma.
Innovation Solution
A system that determines an effective therapy regimen for asthma by obtaining subject information, including environmental conditions and diagnostic test results, and uses this data to select and transmit a suitable therapy regimen to a client computing platform for the subject, allowing for personalized asthma management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If individuals with asthma monitor and treat their symptoms without guidance, then they can manage their asthma independently, but they often fail to correctly monitor and treat their symptoms leading to inadequate management
Solution Approach 1:
The system enables patients to independently manage their asthma by providing automated therapy regimen determination based on their symptom data and environmental conditions. The system serves itself by automatically selecting and updating appropriate therapy regimens without requiring constant physician intervention, thus improving both independent management capability and management effectiveness.
Solution Approach 2:
The system continuously monitors patient symptoms, environmental conditions, and therapy response, then uses this feedback to automatically adjust therapy regimens. This closed-loop feedback mechanism ensures that therapy decisions are data-driven and responsive to changing conditions, improving both the reliability of management and the ease of operation for patients.
2Adaptability or versatility
If physicians determine therapy regimens manually, then they can provide personalized treatment, but it increases the need for frequent physician adjustments and reduces productivity
Solution Approach 1:
The system performs therapy regimen determination autonomously by processing patient data and environmental conditions to select appropriate treatments. This self-service capability maintains personalized therapy adaptability while eliminating the need for frequent physician interventions, thereby improving productivity.
Solution Approach 2:
The system replaces the manual mechanical process of physician therapy determination with an automated computational system. This substitution maintains the adaptability and personalization of therapy decisions while dramatically reducing the time and resources required for physician involvement, thus improving productivity.
3Reliability
If therapy regimens are adjusted frequently based on changing conditions, then asthma management remains effective, but it increases complexity and requires more monitoring
Solution Approach 1:
The system uses continuous feedback from symptom monitoring and environmental data to automatically adjust therapy regimens. This feedback mechanism maintains management effectiveness by responding to changing conditions while simplifying the process through automated decision-making, reducing the complexity burden on patients and physicians.
Solution Approach 2:
The system automatically changes therapy parameters (medication type, dosage, frequency) based on predefined criteria and patient response. This parameter change approach maintains effective asthma management while reducing complexity by using systematic, rule-based adjustments rather than ad-hoc decisions, making the complexity manageable and transparent.
Data Source
AI summary
Systems and methods to determine a therapy regimen to treat asthma of a subject are disclosed. Exemplary implementations may: store a condition impact assessment and multiple therapy regimens for treating asthma; obtain subject information for the subject, wherein the subject information includes (i) environmental conditions at or around a physical location of the subject, (ii) results of remote diagnostic tests for the subject, and (iii) physician-certified condition information including results to physician-administered diagnostic tests for the subject; obtain the multiple therapy regimens; obtain the condition impact assessment; determine a particular therapy regimen from the multiple therapy regimens as an effective therapy regimen for a period of time based on the subject information and condition impact assessment; and define the effective therapy regimen as a current therapy regimen; and transmit the current therapy regimen to a subject client computing platform associated with the subject for presentation to the subject.