Digital Platform Automated Health Plan Generation
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Solution Overview
Problem
Conventional digital health systems rely heavily on skilled users for data interpretation and treatment plan generation, making them labor-intensive and costly, with limited functionality.
Innovation Solution
A digital platform with a graphical user interface that automatically generates individual-specific schedules or plans by matching data from individual-specific and non-individual-specific databases using pre-determined criteria, reducing the need for highly trained users and enabling efficient, cost-effective implementation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data interpretation and treatment plan generation by skilled medical practitioners is used, then reliability and accuracy of health records are improved, but labor intensity and cost increase significantly
Solution Approach 1:
The system enables self-service through automated data interpretation where the digital health system independently processes patient data, matches it with treatment protocols, and generates treatment plans without requiring continuous skilled user intervention. The automated algorithm serves itself by interpreting data and generating appropriate treatment schedules.
Solution Approach 2:
The patent replaces the mechanical system of manual data interpretation by skilled practitioners with an automated digital system. The processing means automatically matches patient data with treatment protocols, substituting human expertise with computational algorithms that achieve similar reliability without the labor intensity.
2Manufacturing precision
If manual treatment plan generation by skilled users is used, then accuracy of treatment plans is improved, but cost and time consumption increase
Solution Approach 1:
The system performs preliminary action by pre-storing treatment protocols, guidelines, and algorithms in the digital health system before actual treatment plan generation is needed. When patient data is input, the system instantly matches against pre-existing protocols, eliminating the need for real-time skilled judgment and significantly reducing generation time while maintaining accuracy.
Solution Approach 2:
The patent substitutes the time-consuming manual process of treatment plan generation with automated computational matching. The processing means rapidly compares patient data against stored protocols and generates treatment plans instantaneously, replacing skilled user time investment with efficient algorithmic processing.
3Device complexity
If conventional digital health systems are used, then basic data storage functionality is provided, but functionality and versatility are limited
Solution Approach 1:
The patent implements universality by designing the digital health system to perform multiple functions beyond basic data storage. The same automated processing architecture handles data input, matching with various treatment protocols, generating different types of treatment plans, and creating schedules, thereby expanding functionality without proportionally increasing complexity.
Solution Approach 2:
The system introduces dynamics by enabling flexible configuration of treatment protocols and matching criteria that can be adapted to different patient scenarios. The automated algorithm dynamically adjusts treatment plan generation based on input data, allowing the system to handle diverse medical scenarios while maintaining a consistent core structure.
Data Source
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AI summary
A digital platform is provided including at least one graphical user interface (GUI) for display on display means in use and for allowing input of data relating to an individual in use. The digital platform is arranged to generate a digital data record including individual specific data based on the data input into the GUI in use. At least a first database is associated with and/or communicatively coupled to the digital platform for storing the digital data record. At least a second database is associated with and/or communicatively coupled to the digital platform for storing further digital data which comprises non-individual specific digital data. Processing means are provided with and/or associated with the digital platform. The processing means is arranged to undertake one or more data matching processes between data in the digital data record in the at least first database and the non-individual specific digital data in the at least second database, such that, on detection of one or more data matches based on one or more pre-determined data criteria between the digital data record and the non-individual specific digital data, a digital schedule and/or digital plan of action specific to the individual is automatically generated that is based on the one or more data matches of the one or more pre-determined data criteria in the at least first and second databases.