Population Risk Scoring for Medical Exam Allocation
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Solution Overview
Problem
Current healthcare management systems are labor-intensive and inefficient, particularly in managing medical examinations, as they rely on manual data collection and lack effective automation for evaluating medical conditions and allocating resources.
Innovation Solution
A method and system that document historical medical test results, calculate relative risk scores for individuals, and select a subgroup for medical examinations based on a population examination framework, using a computerized processor to dynamically allocate resources and prioritize individuals with the highest risk, regardless of budget changes or demographic characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual systems are used to review individual files and collect statistics on health care treatment, then data collection can be performed, but the process becomes labor-intensive and inefficient
Solution Approach 1:
The patent replaces manual mechanical review of individual files with an automated computerized system that processes health care data electronically. The system automatically collects, stores, and analyzes data from multiple sources without requiring manual intervention to review individual patient files, thereby eliminating the labor-intensive nature of traditional methods while maintaining data collection capabilities
Solution Approach 2:
The system enables self-service by automatically performing data collection, processing, and analysis functions that previously required manual human effort. The automated system serves itself by continuously gathering data from connected health care providers and processing it without external intervention, improving productivity while reducing the need for manual operations
2Productivity
If automated analysis of historical health care data is implemented, then efficiency is improved, but the system focuses mainly on collecting financial data for accounting and administrative functions
Solution Approach 1:
The patent implements a multi-functional system that goes beyond financial data collection to include comprehensive clinical data analysis. The automated system performs multiple functions: collecting financial data for accounting, analyzing clinical outcomes, evaluating treatment effectiveness, and generating health care quality metrics. This universal system handles diverse data types and analysis purposes simultaneously, expanding the scope of automated analysis while maintaining efficiency
Solution Approach 2:
The system is designed to be dynamic and adaptable, allowing the scope of data analysis to expand beyond initial financial focus. The automated analysis can be configured to examine various data types including clinical outcomes, treatment effectiveness, and population health metrics, enabling the system to adapt to different analysis needs while maintaining operational efficiency
3Ease of operation
If medical examinations are allocated without a systematic framework, then resource distribution may occur, but there is no effective prioritization of individuals based on risk
Solution Approach 1:
The patent applies preliminary action by calculating risk scores for all individuals in the population before allocating medical examination resources. The system pre-processes health care data, evaluates risk factors, and generates prioritization rankings in advance of resource allocation decisions. This preliminary risk assessment ensures that when resources are distributed, they are automatically directed to high-risk individuals based on pre-calculated scores, improving prioritization accuracy while maintaining operational simplicity
Solution Approach 2:
The system uses parameter changes by transforming raw health care data into standardized risk score parameters that enable consistent comparison across individuals. By converting diverse clinical and demographic data into a unified risk scoring system, the patent enables reliable prioritization while keeping the allocation process simple and automated, resolving the contradiction between ease of operation and prioritization accuracy
Data Source
AI summary
A method of managing an allocation of medical examinations. The method comprises documenting, in at least one dataset, for each one of a plurality of individuals of a certain population, a plurality of historical medical test results, calculating, using a computerized processor, a plurality of relative scores each indicative of a risk of having a medical condition for one of the plurality of individuals based on respective the plurality of historical medical test results, each one of the plurality of relative scores is relative to the other of the plurality of relative scores, providing a population examination framework defining at least one criterion for selecting an individual, from the plurality of individuals, for a diagnosis of the medical condition, selecting a subgroup of the plurality of individuals according to the population examination framework, and designating members of the subgroup to perform the medical examinations.