Risk Analysis System for Medical Expense Prediction
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Solution Overview
Problem
Current methods lack the ability to accurately predict future medical expenses for individuals, failing to consider their unique health conditions and risks, which is crucial for both health insurance subscribers and providers.
Innovation Solution
A risk analysis system that estimates event onset risks and predicts future medical expenses by combining subject data with average medical expense data, incorporating factors like hypertension and multiple potential diseases, to provide a reliable prediction of both hospitalization and outpatient costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If average future medical expenses are determined by consulting an expert, then the prediction process is simplified, but the accuracy decreases because individual health conditions and risks are not considered
Solution Approach 1:
The system segments the prediction process into two distinct components: (1) a risk estimation module that calculates individual health risks based on personal data, and (2) an expense calculation module that uses these risk scores with average expense data. This segmentation allows the system to maintain operational simplicity while incorporating individualized risk factors for improved accuracy.
Solution Approach 2:
The invention introduces an intermediary element - the risk score - that bridges individual health conditions and average medical expense data. The risk score acts as a mediator that translates personal health information into a quantifiable factor that can be applied to expense predictions, enabling individualized accuracy without complex direct modeling.
2Measurement precision
If a system collects and analyzes multiple health parameters and risk factors, then the prediction accuracy improves, but the device complexity increases
Solution Approach 1:
The system divides complex health data analysis into separate functional modules: data collection, risk factor analysis, risk scoring, and expense calculation. Each module handles a specific aspect of the prediction process, reducing overall system complexity while maintaining comprehensive data utilization for accurate predictions.
Solution Approach 2:
The system automatically processes and analyzes health data without requiring manual intervention. The risk estimation and expense calculation are performed autonomously based on input data, eliminating the need for complex manual assessment procedures while maintaining high prediction accuracy.
3Reliability
If individual health risks are incorporated into future medical expense predictions, then the prediction reliability improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The risk score serves as an intermediary that simplifies the measurement of individual health risks. Instead of directly measuring and analyzing multiple complex health parameters separately, the system aggregates them into a single risk score that can be easily applied to expense predictions, reducing measurement difficulty while improving reliability.
Solution Approach 2:
The system transforms multiple health parameters into a standardized risk score parameter. This parameter transformation simplifies the detection and measurement process by converting complex health data into a unified metric that directly correlates with future medical expense risk, making the assessment more manageable and reliable.
Data Source
AI summary
The risk analysis system according to the present invention includes: a storage apparatus which stores subject data including information related to health of a subject; an analyzer which analyzes a risk related to the health of the subject based on the subject data acquired from the storage apparatus; and an output apparatus which outputs an analysis result by the analyzer. The analyzer has: a risk estimating unit which estimates an event onset risk of the subject based on the subject data; and a medical expense predicting unit which predicts future medical expenses, which are medical expenses to be incurred in the future by the subject, based on the event onset risk estimated by the risk estimating unit and the subject data.