Patient Health Score Processing With Standardized Health Indicators
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Solution Overview
Problem
Existing health evaluation methods are often based on incomplete or erroneous concepts, neglecting the balance between the gastrointestinal and nervous systems, and lack accessibility and efficiency in determining a comprehensive health score for patients.
Innovation Solution
A system for processing health indicator values that integrates a database with standardized values, input means, intermediate servers, and a master server to compute a numerical health score, allowing real-time updating and accessibility through devices like smartphones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a comprehensive health evaluation system is implemented to assess multiple health indicators, then the accuracy and completeness of health assessment is improved, but the complexity of the system and difficulty of operation increases
Solution Approach 1:
The health assessment system is divided into multiple independent modules, each responsible for specific health indicators (e.g., digestive health module, nervous system module, physical activity module). Each module processes its specific indicators separately and contributes to the overall health score, making the complex system manageable and easier to implement while maintaining comprehensive assessment capability
Solution Approach 2:
The system uses a unified computational framework that can process multiple types of health indicators (laboratory values, questionnaire data, physical activity data) through a common scoring algorithm. The master server handles diverse data formats and sources using standardized processing protocols, reducing operational complexity while maintaining comprehensive evaluation coverage
2Ease of operation
If real-time health score computation is implemented to provide immediate feedback, then the responsiveness and usability of the system is improved, but the computational load and processing time requirements increase
Solution Approach 1:
The system pre-establishes weightings and scoring algorithms for different health indicators during the setup phase. When new data is input, the system only needs to perform simple arithmetic operations using pre-computed weights rather than running complex algorithms in real-time, enabling immediate feedback with minimal computational power
Solution Approach 2:
The master server acts as an intermediary between data input devices and the final health score calculation. It receives raw data from multiple sources, performs preliminary processing and validation, then computes the health score using efficient algorithms. This intermediary layer distributes computational tasks and optimizes processing flow to maintain responsiveness without excessive power consumption
3Loss of information
If multiple health indicator data from various sources is integrated to provide comprehensive health assessment, then the completeness of health information is improved, but the difficulty of data processing and standardization increases
Solution Approach 1:
The system converts different types of health data (laboratory values, questionnaire responses, physical activity measurements) into a standardized set of numerical parameters with consistent units and formats. Each data type is transformed into comparable numerical values that can be processed uniformly by the scoring algorithm, enabling comprehensive integration while simplifying processing
Solution Approach 2:
The system creates standardized data templates and reference values that can be copied and applied across different data sources. Pre-defined data formats, validation rules, and processing protocols are replicated for each indicator type, ensuring consistent handling of diverse health information while reducing the complexity of manual standardization
Data Source
AI summary
A system for processing health indicator values in order to determine a numerical score representative of the general health of a patient, the system including a database that comprises a series of values for indicators of different aspects of health which are calibrated using standardized values. A plurality of input means are each associated with at least one patient. As many intermediate servers are each associated with the input means of one or more patients, and communicate with a master server that comprises a computation unit for all the intermediate servers. Raw data of indicators of different aspects of a patient's health which are received by the input means are calibrated and transmitted to the master server, and the calculated score for which is stored in a display device, for example a smartphone associated with the patient's input means.