Test Server Statistical Analysis for Diagnostic Accuracy
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Solution Overview
Problem
Current test systems lack the ability to provide preliminary predictive values and prevalence rates to doctors before clinical tests, fail to aggregate test results from dispersed locations, and do not effectively enhance diagnostic accuracy or handle infectious disease outbreaks.
Innovation Solution
A test system comprising a test server and communication terminals that collect, store, and statistically process test data from multiple locations, calculating and returning predictive values, prevalence rates, and sensitivity/specificity to assist doctors in diagnosis and treatment decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If test systems only perform local analysis based on patient test results, then the system structure remains simple, but the diagnostic accuracy and predictive value information cannot be improved
Solution Approach 1:
The system divides the test network into multiple independent test terminals distributed across different regions, each capable of local testing while contributing data to the central server. This segmentation allows the system to maintain simplicity at the terminal level while achieving enhanced diagnostic accuracy through centralized statistical analysis of aggregated data from multiple locations.
2Measurement precision
If test systems aggregate test results from multiple dispersed locations via network, then the prevalence rate and predictive value calculation accuracy improves, but the system complexity and data management burden increases
Solution Approach 1:
The invention introduces a central server as an intermediary that mediates between dispersed test terminals and doctors. The server automatically aggregates test results, calculates prevalence rates and predictive values using statistical methods, and provides this processed information back to terminals. This intermediary approach simplifies data management for individual terminals while achieving high-accuracy aggregated analysis.
3Measurement precision
If the total number of test results is increased to improve prevalence rate accuracy, then the statistical significance improves, but the time and resources required for data collection increases
Solution Approach 1:
The system enables continuous data collection from multiple test terminals simultaneously operating in parallel across different regions. Instead of sequentially collecting data from one location at a time, the networked system continuously aggregates test results from numerous terminals, achieving high statistical significance much faster through concurrent data accumulation from distributed sources.
4Ease of operation
If test systems provide only basic test results without predictive values, then the system operation remains simple, but the clinical decision-making support is insufficient
Solution Approach 1:
The test terminals automatically request and receive predictive value information, prevalence rates, and diagnostic support data from the central server without requiring manual intervention. The system performs self-service by automatically integrating basic test results with statistically processed predictive information, providing doctors with comprehensive decision-making support while maintaining simple terminal operation through automated information exchange.
Data Source
AI summary
A test server includes: a communication unit that communicates with a plurality of communication terminals via a network, the plurality of communication terminals each being connectable to a test device capable of executing a test on the presence or absence of a disease, the diagnosis being related to the test and made by a doctor; and a control unit that acquires at least one of a result of the test and the diagnosis as a test information item from each of the plurality of communication terminals via the communication unit, causes a storage unit to store the plurality of acquired test information items, performs statistical processing on the plurality of stored test information items, and causes the communication unit to return a result of the statistical processing according to a demand given from each of the communication terminals before the doctor makes a diagnosis.