Clinical Document Ranking via Relevancy Scoring
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Solution Overview
Problem
Radiologists face inefficiencies in diagnosing medical images due to the need to search through multiple electronic medical records to determine the underlying reason for an exam, which increases the time required for making an accurate diagnosis.
Innovation Solution
A processor-based system that determines the intent of an exam request, retrieves relevant documents, assigns a relevancy score based on user profiles, and ranks them for display, thereby streamlining the review process by presenting the most relevant information first.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If radiologists manually search through multiple electronic medical records to determine the reason for an exam, then they can gather comprehensive clinical information, but the time required to make a diagnosis increases
Solution Approach 1:
The system performs preliminary actions by automatically retrieving and pre-ranking clinical documents before the radiologist begins their review. Documents are fetched based on the exam request and initially ranked using algorithmic relevancy scoring, so that when the radiologist accesses them, the most relevant information is already positioned at the top, eliminating the need for manual searching through multiple records.
Solution Approach 2:
The manual mechanical process of radiologists searching through electronic medical records is replaced with an automated information retrieval and ranking system. The system uses computer algorithms to automatically search, retrieve, and rank documents based on relevancy scores, substituting the manual search mechanism with an automated computational system that delivers pre-organized clinical information.
2Reliability
If radiologists review multiple clinical documents to ensure accurate diagnosis, then diagnostic accuracy improves, but the review process becomes more complex and time-consuming
Solution Approach 1:
The system segments the clinical documents and presents them in a hierarchical structure with the most relevant document at the top and less relevant documents below. This segmentation allows radiologists to focus on the most critical information first while having access to additional documents if needed, reducing the perceived complexity of reviewing multiple documents.
Solution Approach 2:
The system retrieves and presents more clinical documents than a radiologist might manually search for, ranking them by relevancy. This excessive action ensures that all potentially relevant information is available, but the radiologist only needs to review the top-ranked documents for accurate diagnosis, simplifying the review process while maintaining completeness.
3Loss of information
If radiologists review files that may not be relevant to the underlying condition, then they ensure comprehensive coverage, but the review time increases
Solution Approach 1:
The system performs preliminary filtering and ranking of documents before presentation to the radiologist. Documents are pre-ranked using relevancy scores calculated from multiple factors including user profiles, exam attributes, and document content analysis. This preliminary action ensures that irrelevant files are positioned lower in the ranking, allowing radiologists to quickly identify and skip non-relevant documents while maintaining access to comprehensive information if needed.
Data Source
AI summary
A system may include a processor-based device configured to store or access a ranking application. When executed on or in communication with the workstation, the ranking application may determine a purpose of an exam request based on one or more attributes of the exam, retrieve a plurality of documents from a database based on the determined purpose, and assign a relevancy score to each of the plurality of documents based on a user profile. The ranking application may also create a list comprising the plurality of documents, wherein an order of the plurality of documents is based on the relevancy score and populate a graphical user interface (GUI) with the list for display on the workstation.