Radiology Exam Program Selection From RIS Comments
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Solution Overview
Problem
Current radiological examination processes lack a standardized, technology-assisted end-to-end process for defining optimal imaging programs, relying heavily on manual interpretation and selection by skilled personnel, which is prone to errors, time-consuming, and laborious.
Innovation Solution
An automated method and apparatus that utilize character string comparisons and semantic analysis to select radiological examination programs from a radiology information system (RIS) comment field, incorporating logical operators and machine learning to streamline the selection process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual interpretation and selection of examination programs is performed by radiologists or technicians, then accurate program selection can be achieved, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs preliminary automated analysis of the RIS comment and pre-selects suitable examination programs before the technologist needs to make a final selection. This reduces the time required for program selection while maintaining accuracy through the automated comparison process.
Solution Approach 2:
An automated program selection system acts as an intermediary between the RIS comment input and the final examination program selection. This intermediary automatically compares the comment with available programs and presents pre-selected options, reducing both time and manual effort.
2Adaptability or versatility
If manual selection of examination programs is performed, then flexibility in handling complex cases is maintained, but the process is prone to human error
Solution Approach 1:
The system provides feedback by automatically comparing the RIS comment with the available examination programs and presenting the best matches. This automated feedback loop reduces human error while maintaining flexibility, as the technologist can review and adjust the automated suggestions if needed.
Solution Approach 2:
The manual mechanical process of interpreting RIS comments and selecting programs is replaced with an automated computer-based system that performs string comparison and program selection, thereby eliminating human error while preserving adaptability through configurable matching rules.
3Loss of information
If detailed information is entered into the RIS comment field, then sufficient information is available for program selection, but the information may be misplaced or ambiguously formatted
Solution Approach 1:
The automated program selection system acts as an intermediary that handles the complexity of parsing and interpreting RIS comments with various formats. It automatically extracts relevant information regardless of how it is formatted in the comment field, making the system robust to information placement variations.
Solution Approach 2:
The system changes the parameter of information processing by using flexible string comparison algorithms that can handle various formats and placements of information within the RIS comment. This allows the system to extract meaningful data regardless of the specific format or position of the information.
4Productivity
If automated program selection is implemented, then time efficiency is improved, but the system may lack the nuanced understanding of complex medical cases
Solution Approach 1:
The automated system performs preliminary program selection based on the RIS comment, providing a starting point that saves time. The technologist then performs a final review and adjustment if needed, combining automated efficiency with human clinical judgment for complex cases.
Solution Approach 2:
The automated system performs partial program selection rather than complete autonomous selection. It handles the routine aspects of program selection automatically while leaving room for human intervention in complex or ambiguous cases, thus achieving a balance between automation and clinical judgment.
Data Source
AI summary
The disclosure relates to automated planning of a radiological examination, comprising providing information about a pending examination of a patient from a radiology information system) and providing at least one RIS comment relating to the examination. The automated planning also includes comparing, in an automated manner, character strings in the RIS comment with names of examination programs in a specified examination list, and selecting a number of examination programs for these character strings based on the comparison. Finally, the selected examination programs are output.