Clinical Structured Reporting via Default Template Modification
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Solution Overview
Problem
Current document generation systems for clinical reports, particularly in healthcare, are time-consuming and costly due to the need for manual transcription and correction, with low accuracy in voice recognition systems and complexity in hierarchical input systems, leading to errors and inefficiencies in generating reports, especially for normal findings which constitute a significant proportion of medical reports.
Innovation Solution
A system and method for generating clinical structured reports that utilize a default template pre-filled with normal findings, allowing users to easily indicate abnormalities, with options for multi-language support and integration with computer-aided diagnosis tools, enabling efficient and accurate report generation and billing information creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual transcription and correction processes are used, then report accuracy can be maintained, but time consumption and cost increase significantly
Solution Approach 1:
The system pre-fills report templates with standard normal findings before the user inputs abnormal findings. This preliminary action eliminates the need for users to manually transcribe and correct entire reports, reducing time consumption while maintaining accuracy through structured templates that ensure all necessary information is included.
Solution Approach 2:
The system uses template copying where standard report structures and normal findings are replicated and reused. Users copy the template and only modify the portions related to abnormal findings, significantly reducing the time required for report generation while maintaining professional accuracy through consistent template usage.
2Productivity
If voice recognition technology is used to reduce dictation/transcription time, then productivity improves, but accuracy rates become too low for medical applications
Solution Approach 1:
The system pre-provides structured templates with correct medical terminology and standard phrasing for normal findings. Users simply select or modify pre-validated content rather than relying on voice recognition to generate accurate medical terminology, ensuring high accuracy while maintaining efficiency through rapid template selection and modification.
Solution Approach 2:
The template system acts as an intermediary between the user's diagnostic findings and the final report. Instead of relying on voice recognition to translate spoken words into accurate medical terminology, the template serves as a mediator that provides the correct terminology, ensuring accuracy while allowing rapid input through simple selection mechanisms.
3Manufacturing precision
If hierarchical input nodes are used to generate reports, then structured data entry is achieved, but the system becomes complex and time-consuming to navigate
Solution Approach 1:
The system pre-organizes all possible report content into structured templates before the user needs to input data. This eliminates the need for users to navigate complex hierarchical trees during report generation, as the structure is already in place. Users simply select or modify content within the pre-organized template, maintaining data consistency while reducing navigation complexity.
Solution Approach 2:
Instead of requiring users to navigate through complex hierarchical structures to find and select appropriate terms, the system inverts the approach by pre-placing all appropriate terms in organized templates. Users interact with the inverted structure by selecting from pre-arranged options rather than searching through complex hierarchies, reducing complexity while maintaining structural precision.
4Reliability
If blank report templates are used requiring users to populate all findings, then complete report generation is achieved, but time consumption increases significantly for normal findings
Solution Approach 1:
The system pre-fills templates with standard normal findings before the user inputs abnormal findings. This preliminary action ensures report completeness for normal findings without requiring users to manually enter them, significantly improving productivity. Users only need to modify or add information related to abnormal findings, maintaining completeness while reducing the time required to generate reports.
Solution Approach 2:
The system extracts and separates normal findings from abnormal findings by providing pre-filled templates that contain only the normal findings. This extraction allows users to focus their attention and input efforts only on the abnormal findings that require their expertise, improving efficiency while maintaining report completeness through the inclusion of pre-provided normal findings.
Data Source
AI summary
Systems and methods for generating clinical structured reports, allowing users to indicate findings from a medical examination without having to enter normal findings. In one aspect, a user selects a clinical structured report template for a particular type of medical examination. A default clinical structured report based on the template, and comprising normal findings for the medical examination type, is presented to the user. The user modifies one or more of the normal findings to indicate abnormal findings. A clinical structured report is generated, based on the default normal findings and the abnormal findings received from the user. The report is stored in a database or sent to one or more recipients over a network. In one aspect, the normal findings comprise text data. In another aspect, the normal findings comprise plots, graphs, diagrams, or other types of data. In one aspect, the system provides for multi-language support and translations. In one aspect, the clinical structured report is used to generate billing information. In one aspect, the clinical structured report is generated by a computer aided diagnosis tool.