Guided Structured Reporting Apparatus for Clinical Data
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Solution Overview
Problem
Current patient diagnostic and reporting systems are time-consuming and prone to errors due to the need for clinicians to navigate multiple menus and select pre-defined finding codes one by one, often resulting in incomplete and tedious reporting.
Innovation Solution
A guided structured reporting apparatus and method that suggests physiological parameter measurements and finding codes to ensure all aspects of a report are addressed, reducing the need for extensive menu navigation and improving user interface efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If clinicians manually navigate multiple menus and select pre-defined finding codes one by one, then reporting completeness can be maintained, but reporting time and complexity increase significantly
Solution Approach 1:
The system automatically generates a preliminary structured report by extracting physiological parameters and suggesting finding codes based on imaging data analysis, eliminating the need for clinicians to manually navigate menus and select codes from scratch. This preliminary draft provides a comprehensive foundation that ensures reporting completeness while significantly reducing the time required for final review and sign-off.
2Manufacturing precision
If extensive menu navigation is required to select finding codes, then coding precision can be maintained, but user interface complexity and ease of operation worsen
Solution Approach 1:
The system performs self-service by automatically extracting physiological parameters from imaging data and generating suggested finding codes based on predefined coding schemes. The system autonomously populates the structured report with appropriate codes and findings, eliminating the need for clinicians to manually navigate complex menus while maintaining coding precision through algorithmic accuracy and validation rules.
Solution Approach 2:
The manual mechanical process of navigating menus and selecting codes is replaced by an automated computational system that uses image processing algorithms and decision support rules to generate finding codes. This substitution transforms the manual selection process into an automated generation process, significantly improving user interface efficiency while maintaining or enhancing coding precision through systematic analysis.
3Adaptability or versatility
If manual reporting processes are used, then flexibility in report customization is maintained, but reporting speed and productivity decrease
Solution Approach 1:
The system implements dynamic adaptability by allowing the structured report template to be automatically customized based on the specific imaging study type, patient characteristics, and clinical context. The system dynamically adjusts which physiological parameters are extracted and which finding codes are suggested, providing flexible customization tailored to each case while maintaining high reporting speed through automated processing.
Data Source
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AI summary
A guided structured reporting apparatus (10) that enables clinicians to select report elements and generate a structured report (56), offering novel and improved structured reporting solutions that improves report (56) accuracy and precision, and expedites the generation of such a report (56). One or more processors (18) receive physiological information, generate a display, generate and display suggested finding codes (48) for adoption in the structured report (56), and generates and displays a structured report (56) based on the adopted finding codes (40).