Patient Risk Score Interpretation via Reference Population Matching
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Solution Overview
Problem
Current risk analysis methods for determining the likelihood of medical events in patients are unreliable and inefficient, leading to delays in processing and potential missed critical events due to the lack of a direct link between group and individual risk scores.
Innovation Solution
A computer-implemented method that acquires and compares a patient's risk profile with a database of other subjects' risk profiles to select the most similar profiles, allowing for a more accurate and timely determination of the likelihood of a medical event by processing risk scores efficiently and providing timely interventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If risk scores are used as probabilities for group analysis only, then group-level risk estimation is achieved, but individual-level risk interpretation becomes difficult and unreliable
Solution Approach 1:
The patent introduces a reference population as an intermediary between group-level risk scores and individual-level interpretation. By comparing the subject's risk score trajectory against the reference population's risk score distribution and medical event outcomes, the system enables individualized risk assessment without requiring complex individual-level prognostic models. The reference population serves as a mediator that translates aggregate risk scores into meaningful individual predictions.
2Productivity
If traditional risk analysis methods are used, then processing can be performed, but delays occur and critical events may be missed due to lack of direct link between group and individual risk scores
Solution Approach 1:
The patent implements feedback by continuously monitoring the subject's risk score over time and comparing it against the reference population's risk score trajectories. The system provides feedback signals when the subject's risk score deviates significantly from the reference distribution or when similar reference subjects experienced medical events. This feedback mechanism enables timely detection of critical events while maintaining efficient processing through automated comparison algorithms.
3Measurement precision
If risk scores are treated as estimates only, then computational simplicity is maintained, but accuracy and reliability of risk determination decreases leading to false alarms
Solution Approach 1:
The patent applies preliminary action by pre-processing and storing risk score trajectories and medical event outcomes for a reference population in advance. This pre-computed reference data includes risk score distributions, trajectories, and associated medical event rates across different risk levels. When assessing a new subject, the system quickly compares their risk score against this pre-prepared reference framework, achieving high accuracy without computationally intensive real-time analysis of individual risk factors.
Data Source
AI summary
There is provided a computer-implemented method and apparatus for determining a likelihood of occurrence of a medical event for a subject. A risk profile for the subject is acquired and a plurality of risk profiles for other subjects are obtained from a database. The acquired subject risk profile is compared to the obtained plurality of other subject risk profiles. At least one risk profile is selected from the obtained plurality of other subject risk profiles that most closely matches the acquired subject risk profile. The likelihood of occurrence of a medical event for the subject is determined based on the selected at least one risk profile. A signal indicative of the determined likelihood of occurrence of the medical event for the subject is output.