Triage AI Consensus for Real-Time Doctor-Patient Diagnosis
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Solution Overview
Problem
Current doctor-patient interactions often result in delayed diagnosis due to inadequate questioning and referral processes, leading to potential delays in appropriate treatment.
Innovation Solution
A triage AI system that utilizes a large language model to analyze doctor-patient conversations, selectively engages multiple AI specialists based on trigger words, and generates a consensus answer displayed through a graphical user interface, providing real-time decision support insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a doctor asks comprehensive questions to cover all possible ailments, then diagnostic accuracy is improved, but consultation time increases
Solution Approach 1:
The patent introduces an AI intermediary system that acts as a mediator between the doctor and patient. The AI analyzes conversation data in real-time, identifies potential ailments based on symptoms, and provides diagnostic suggestions to the doctor. This allows the doctor to maintain a natural conversation flow while the AI performs comprehensive analysis, thereby improving diagnostic accuracy without significantly increasing consultation time.
Solution Approach 2:
The system performs preliminary diagnostic analysis by continuously monitoring the doctor-patient conversation and pre-identifying potential ailments before the consultation ends. The AI prepares diagnostic suggestions and recommended follow-up actions in advance, allowing the doctor to quickly review and act on them without extending the consultation time.
2Measurement precision
If a patient is referred to multiple specialists for comprehensive evaluation, then diagnostic accuracy is improved, but time to receive treatment increases
Solution Approach 1:
The patent segments the diagnostic process by using AI to analyze the patient's symptoms and conversation data to identify which specific specialists are needed. Instead of automatically referring patients to all possible specialists, the AI provides targeted recommendations for only those specialists relevant to the identified ailments, reducing unnecessary referrals and wait times while maintaining diagnostic accuracy.
Solution Approach 2:
The system implements feedback by continuously monitoring the doctor-patient conversation and providing real-time diagnostic suggestions and specialist referral recommendations. This allows the doctor to make informed decisions about specialist referrals during the consultation, reducing delays associated with post-consultation referrals and enabling faster treatment initiation.
3Measurement precision
If a doctor manually reviews all patient symptoms and determines follow-up actions, then diagnostic accuracy is improved, but productivity decreases
Solution Approach 1:
The patent enables the AI system to perform self-service by automatically analyzing conversation data, identifying potential ailments, and generating diagnostic suggestions and follow-up action recommendations. This automates the review process, allowing doctors to quickly verify AI-generated recommendations rather than manually analyzing all symptoms from scratch, thereby improving both diagnostic accuracy and productivity.
Solution Approach 2:
The system replaces the mechanical process of manual symptom review and diagnostic reasoning with an AI-based computational system. The AI processes conversation data, applies medical knowledge, and generates diagnostic suggestions, substituting the doctor's manual cognitive work with automated intelligence while maintaining diagnostic accuracy and significantly improving productivity.
Data Source
AI summary
In some aspects, a triage artificial intelligence (AI) continually receives a portion of a conversation between a doctor and a patient. When the triage AI determines that the conversation includes a first set of trigger words of a first symptom, the triage AI selects a first AI specialist in a first medical specialty from a plurality of AI specialists and provides it access to the conversation. When the triage AI determines that the conversation includes a second set of trigger words of a second symptom, the triage AI selects a second AI specialist in a second medical specialty from the plurality of AI specialists and provides it access to the conversation. The consensus AI determines a consensus answer to questions sent to a subset of the plurality of AI specialists and provides the consensus answer to a continually updated user interface of a computing device associated with the doctor.