Automated Safety Checking for Medical Diagnostic Reports
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Diagnostic reports often miss secondary findings in radiological images, leading to potential diagnostic and treatment errors due to the susceptibility of manual review processes, especially when numerous secondary findings are present.
Innovation Solution
A computer-implemented method that reads sensor data from medical imaging files, assigns focus areas based on viewing patterns by trained personnel, and compares these areas with the diagnostic report to output warnings for missing information, ensuring comprehensive reporting and improved diagnostic quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual review by senior physicians is performed, then diagnostic completeness is improved, but time consumption and resource requirements increase
Solution Approach 1:
The patent introduces an automated analysis system that acts as an intermediary between image acquisition and manual review. This system processes images to identify focus areas and generates preliminary reports, serving as a mediator that prepares data for senior physicians and reduces their manual workload while maintaining diagnostic completeness.
Solution Approach 2:
The system performs preliminary analysis of medical images automatically before manual review, identifying focus areas and generating initial diagnostic reports. This preliminary action prepares the data in advance, allowing senior physicians to review pre-processed information rather than raw images, thereby reducing their time consumption.
2Productivity
If automated analysis is implemented, then processing speed is improved, but risk of overlooking secondary findings increases
Solution Approach 1:
The patent applies local quality by differentiating between focus areas (requiring detailed analysis) and non-focus areas (allowing automated processing). The system concentrates computational resources on identified focus areas while using automated methods for other regions, thereby maintaining high detection accuracy in critical areas while improving overall processing speed.
Solution Approach 2:
The system implements feedback mechanisms where automated analysis results are reviewed and refined by senior physicians, and this feedback is used to improve future automated analysis. The iterative process between automated detection and manual verification enhances both speed and reliability over time.
3Reliability
If comprehensive manual review is performed, then diagnostic accuracy is improved, but device complexity and operational burden increase
Solution Approach 1:
The patent segments the diagnostic process into distinct automated and manual components. The automated system handles image processing, focus area identification, and preliminary report generation, while senior physicians focus on review and final decision-making. This segmentation reduces the complexity burden on any single operator while maintaining high diagnostic accuracy.
4Reliability
If automated safety checking is implemented, then error reduction is improved, but implementation complexity increases
Solution Approach 1:
The system implements self-service by automatically detecting focus areas, generating preliminary reports, and identifying potential errors without requiring complex manual configuration. The automated safety checking performs self-verification through comparison of detected features with established medical criteria, reducing the need for complex external validation systems.
Data Source
AI summary
A computer-implemented method comprises: reading in sensor data relating to an image file; assigning the sensor data to a first position of a patient's anatomical structure; extracting at least one second position of the patient's anatomical structure from a medical diagnostic report; comparing the first position and the at least one second position; and outputting a warning signal if the comparison does not yield a match.