Radiologist Dashboard With Multimodal Retrieval for Report Workflow
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Solution Overview
Problem
Radiologists face challenges in efficiently retrieving and processing relevant patient information during report generation, often leading to missed critical information and increased workload, which affects diagnosis accuracy and consistency.
Innovation Solution
A system and method that utilizes a multimodal model to automatically retrieve and dynamically render relevant radiology information at a dashboard, incorporating inputs from radiologists to provide real-time updates and streamline workflows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radiologists manually retrieve and process patient information during report generation, then they can access relevant data, but the workload increases and critical information may be missed
Solution Approach 1:
The system enables self-service by automatically retrieving and presenting relevant patient information without requiring manual searching. The dashboard proactively surfaces critical data including prior imaging studies, lab results, and clinical notes based on the current case context, allowing radiologists to receive information service rather than actively seeking it.
Solution Approach 2:
The system performs preliminary actions by pre-retrieving and organizing relevant patient information before the radiologist needs it. The dashboard anticipates information requirements and displays pertinent data in advance, including historical imaging studies and relevant clinical data, so that when the radiologist needs information, it is already prepared and presented.
2Loss of information
If radiologists manually search through patient records, then they can find information, but the time required increases significantly
Solution Approach 1:
The dashboard acts as an intermediary between the patient's medical records and the radiologist. It automatically queries multiple data sources including PACS, EMR, and lab systems, then synthesizes and presents relevant information in a unified interface, eliminating the need for radiologists to manually navigate multiple systems and reducing both time and information loss.
3Loss of information
If the dashboard displays all available patient information, then completeness is achieved, but information overload occurs making it harder to find critical data
Solution Approach 1:
The dashboard applies local quality by providing different levels of information presentation tailored to specific needs. It uses hierarchical organization where summary views provide key information at a glance, while detailed sections allow drilling down into specific data types. The interface adapts the level of detail displayed based on the current task context, ensuring critical information is prominently featured without overwhelming the user.
Solution Approach 2:
The dashboard segments information into distinct, organized categories such as imaging studies, laboratory results, clinical notes, and patient demographics. Each segment can be independently accessed and explored, allowing radiologists to efficiently navigate to specific information types without being overwhelmed by the entire dataset presented as a single undifferentiated mass.
4Productivity
If the system automatically retrieves and displays information, then workflow efficiency improves, but the system complexity increases
Solution Approach 1:
The dashboard implements universality by designing a single integrated platform that performs multiple functions: retrieving data from diverse sources (PACS, EMR, lab systems), processing and filtering information, presenting customized views, and adapting to different user preferences. This multi-functional approach consolidates what would otherwise require multiple separate systems into one unified solution, managing complexity while maintaining high productivity.
Data Source
AI summary
Embodiments of systems and methods for dynamic and/or live retrieval and display of relevant clinical outputs to a clinical entity are provided, for a clinical entity processing a case. The systems and methods leverage advanced models (e.g., multimodal models) for retrieval, processing, and rendering of relevant information to the clinical entity, in a manner that improves worklist processing performance. Application areas include systems and tools for radiologists.