Mobile App for Care Continuity via ML Assignment Recommendations
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Solution Overview
Problem
Current healthcare systems face challenges in ensuring seamless communication and effective implementation of home-based exercises between patients, their caregivers, and healthcare experts, leading to gaps in care continuity and progress in managing conditions like autism.
Innovation Solution
A system and method that utilize machine learning and language learning models to generate patient-specific home assignment recommendations, which are communicated to parents and caregivers, ensuring seamless communication and enhancing care continuity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional communication methods (phone calls, written instructions) are used between therapists and parents, then simplicity and ease of operation are maintained, but information gaps and misinterpretations occur leading to poor communication effectiveness
Solution Approach 1:
The patent introduces a mobile application as an intermediary communication platform between therapists and parents. The app provides structured templates for therapy notes, automated translation features, and standardized communication protocols that reduce information loss while maintaining ease of use through intuitive interfaces.
Solution Approach 2:
The system implements real-time feedback mechanisms where parents can receive therapy updates, ask questions, and provide responses through the mobile app. This creates a continuous communication loop that reduces misinterpretation and ensures both parties have accurate information about the patient's progress and home exercises.
2Manufacturing precision
If comprehensive therapy documentation and analysis are provided during sessions, then treatment quality and precision are improved, but time consumption and session duration increase
Solution Approach 1:
The patent implements preliminary action by having therapists document therapy sessions during the actual treatment process rather than after. The mobile app allows real-time note-taking and analysis during sessions, so comprehensive documentation is completed concurrently with treatment delivery, eliminating post-session documentation time.
Solution Approach 2:
The system uses templates and standardized formats for therapy documentation that can be efficiently copied and adapted for different patients and session types. This reduces the time required to create comprehensive treatment records while maintaining precision and completeness.
3Adaptability or versatility
If home-based exercises are assigned and tracked manually, then personalization and adaptability are improved, but workload and complexity for caregivers increase
Solution Approach 1:
The patent implements self-service by enabling the mobile application to automatically track and monitor home exercise completion. The system sends push notifications to caregivers, automatically records completion status, and provides reminders, reducing the manual tracking burden while maintaining personalized exercise programs.
Solution Approach 2:
The mobile app serves multiple functions including exercise assignment, tracking, monitoring, communication, and documentation within a single unified platform. This multi-functionality reduces the need for separate tools and simplifies the overall system complexity while providing personalized exercise management.
Data Source
AI summary
A system and a method to enhance the continuity of care for a patient is disclosed. The method disclosed herein includes accessing the patient's data available in one or more formats, where the patient's data includes a pre-stored data, a real-time generated data or a combination thereof. The patient's data is then processed using machine learning techniques and language learning model by extracting relevant information from the patient's data. Further, the one or more patient-specific assignment recommendations are generated in correspondence to the processed patient's data, where the assignment recommendations are designed to address a condition management in the patient.