Dynamic Care Decision Platform with Adaptive Curricula
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Solution Overview
Problem
Existing care decision platforms lack a dynamic and personalized approach to recommending care services and lifestyle choices, failing to effectively engage users and optimize outcomes.
Innovation Solution
A care decision platform that utilizes a system comprising user devices, a cloud platform, an assessment platform, a data collection engine, a scoring engine, a recommendation engine, and a decision coach to provide a dynamically updating curriculum and virtual nurturing for users, facilitating interaction with care service providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static care decision platform is used, then the system complexity is low, but the personalization and adaptability of recommendations deteriorate
Solution Approach 1:
The platform transitions from static to dynamic by continuously collecting user data through multiple channels (assessments, sensors, EHRs, wearables) and updating recommendations in real-time. The curriculum adapts automatically as new data becomes available, ensuring personalization without requiring manual intervention.
Solution Approach 2:
The system segments data collection into multiple independent sources (assessments, passive sensors, EHR integrations, wearable devices) and processes them through separate modules (data collection engine, scoring engine, recommendation engine). This modular architecture manages complexity by dividing the system into manageable, independent components.
2Measurement precision
If comprehensive data collection is implemented, then the precision of recommendations improves, but the data processing complexity increases
Solution Approach 1:
The data collection engine acts as an intermediary layer between multiple data sources and the scoring engine. It standardizes and integrates diverse data formats into a unified structure, simplifying downstream processing. The scoring engine then processes this standardized data to generate recommendations, separating the complexity of data integration from the complexity of analysis.
3Speed
If real-time updates are provided, then the responsiveness to user needs improves, but the computational resources required increase
Solution Approach 1:
The platform implements periodic data collection and update cycles rather than continuous real-time processing. Data is collected at scheduled intervals from assessments, sensors, and external sources, and recommendations are updated periodically based on accumulated data. This approach provides timely updates while reducing computational burden compared to continuous real-time processing.
Data Source
AI summary
Systems and methods for a care decision platform operable to facilitate shared decision making for care services and/or lifestyle choices related to aging. The present invention incorporates medical decision aids, recommendation engines, and scoring algorithms to design a dynamically updating curriculum for improving customer outcomes as a result of care services and/or lifestyle choices. The curriculum is operable to be implemented as a customer relationship management tool for a care service provider.