Consent Form Explanation Using AI-Generated Key Point Summaries
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Solution Overview
Problem
Existing systems require significant effort from medical professionals to explain lengthy and complex informed consent forms, which can be difficult for subjects to understand, leading to increased workload and inefficiency in the consent process.
Innovation Solution
An information processing system utilizing a large language model to generate explanatory sentences based on key point sentences from informed consent forms, FAQs, and scientific background documents, reducing the need for manual explanation by medical professionals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the informed consent form is made comprehensive and detailed to ensure ethical standards are met, then the completeness and accuracy of information provided to subjects is improved, but the length and complexity of the form increases, making it more difficult for subjects to understand and increasing the workload for medical professionals
Solution Approach 1:
The patent divides the comprehensive informed consent form into multiple short video clips, each covering a specific topic or section. This segmentation transforms the complex textual document into manageable visual segments that are easier for subjects to process and understand, while maintaining all required ethical information.
Solution Approach 2:
The patent introduces an AI-generated explanatory video as an intermediary between the detailed consent form and the subject. This intermediary translates complex medical and ethical terminology into accessible visual explanations, bridging the gap between comprehensive information and subject understanding.
2Reliability
If the informed consent form is made comprehensive to cover all ethical requirements, then the accuracy and completeness of subject information is improved, but the time required for medical professionals to explain the form increases significantly
Solution Approach 1:
The patent performs preliminary action by pre-producing comprehensive explanatory videos that cover all necessary consent information before the actual consent process. This allows medical professionals to simply guide subjects through pre-prepared visual explanations rather than creating explanations from scratch during each consent session.
Solution Approach 2:
The patent creates video copies of the consent form content, transforming textual information into visual format. These video copies can be repeatedly used across multiple consent sessions without requiring medical professionals to re-explain each point, significantly reducing repetitive time investment.
3Measurement precision
If the informed consent form is made detailed to ensure ethical compliance, then the accuracy of information is improved, but the number of items requiring explanation increases, overwhelming medical professionals
Solution Approach 1:
The patent segments the detailed consent form into discrete video modules, each addressing a specific ethical requirement or information point. This segmentation allows medical professionals to efficiently guide subjects through organized visual content rather than explaining lengthy text sections.
Solution Approach 2:
The patent replaces the mechanical process of oral explanation with automated video presentation. The AI-generated videos deliver precise ethical and informational content without requiring medical professionals to verbally explain each detail, thereby maintaining accuracy while improving efficiency.
Data Source
AI summary
Provided are a recording medium, an information processing method, and an information processing device that can reduce workload of medical professionals associated with explanation of informed consent forms.A computer readable non-transitory recording medium recording an information processing program causes a computer to execute: acquiring a key point sentence related to content of a consent form for a medical procedure or a clinical trial; reading a sentence related to the acquired key point sentence from a database; acquiring an explanatory sentence generated by inputting the key point sentence and the read sentence to a language model; and outputting the acquired explanatory sentence.


