Context-Driven Radiology Summary View for Prior Study Matching
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Solution Overview
Problem
Radiologists face challenges in efficiently reviewing and summarizing numerous medical images and reports, leading to incomplete patient history overview and potential adverse patient outcomes due to lack of quality assurance tools for consistency and follow-up on findings.
Innovation Solution
A system and method for generating a context-driven summary view by extracting current context information from medical studies, matching it with prior studies, and storing relevant information in a database to provide a comprehensive overview of patient findings, using a processor, memory, and modules for context extraction, matching, and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If radiologists manually review multiple prior reports and images to build a complete patient history, then comprehensive patient finding history can be obtained, but the process becomes difficult and time consuming
Solution Approach 1:
The system performs preliminary actions by automatically retrieving, extracting, and organizing relevant findings from prior studies before the radiologist needs them. The context-driven summary is pre-assembled based on the current study's anatomy and clinical context, so when the radiologist opens a study, the consolidated patient history is already ready for review, eliminating the need to manually search through multiple prior reports.
2Loss of information
If radiologists open multiple prior reports to understand patient history, then complete picture of patient findings can be obtained, but the complexity of the process increases
Solution Approach 1:
The system merges multiple prior reports and findings into a single consolidated context-driven summary view. Instead of requiring the radiologist to open and cross-reference multiple separate reports, the system combines all relevant findings from prior studies into one integrated display that shows the complete patient history in a unified format, reducing process complexity.
3Productivity
If no quality assurance tools are used for finding consistency, then workflow remains simple, but previously identified findings may be overlooked
Solution Approach 1:
The system implements feedback mechanisms by automatically tracking findings across multiple studies and providing quality assurance checks. The context-driven summary displays the longitudinal history of findings, allowing the system to feedback on whether previously identified findings have been followed up on appropriately. This automated tracking ensures consistency without adding manual workflow steps.
4Loss of information
If radiologists manually build mental links between related findings, then comprehensive understanding can be achieved, but the process becomes time consuming
Solution Approach 1:
The system acts as an intermediary by automatically establishing and displaying the connections between related findings across different studies. Instead of requiring the radiologist to mentally link findings, the system retrieves prior studies, extracts relevant findings, and presents them in a context-driven summary that shows how findings are related through the patient's clinical history, anatomy, and timing, making the connections explicit and easily visible.
Data Source
AI summary
A system, method and computer readable storage medium for generating a context driven summary view of medical findings by retrieving a current study including at least one image to be analyzed, extracting current context information from the current study and storing the current context information in a database and matching the current context information with prior context information from prior studies to return a set of relevant prior studies.