Bimodal Auto-Response System for Secure Messaging
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Solution Overview
Problem
Current messaging systems, particularly in expert-consumer interactions, face challenges such as delayed responses, loss of conversation threads, inability to handle ad-hoc questions, and security issues with unsecured communication formats like SMS, especially in medical contexts where sensitive information is involved.
Innovation Solution
A bimodal auto-response system that switches between predictive and structured modes based on user input, utilizing longitudinal data to maintain conversation flow and store information for context-aware responses, while ensuring secure communication through secure messaging channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a case manager manually types messages to communicate with multiple patients, then secure communication can be maintained, but response time increases and the case manager may lose track of conversation threads
Solution Approach 1:
The system segments the communication task by introducing an automated response generator that handles routine messages, allowing the case manager to focus on complex interactions. The automated system processes messages independently while maintaining security protocols, dividing the workload between human and machine.
Solution Approach 2:
An automated response generation system acts as an intermediary between the case manager and patients. This intermediary receives patient messages, generates appropriate responses based on predefined protocols and longitudinal data, and presents them for case manager approval before sending, thereby reducing response time while maintaining security oversight.
2Productivity
If the case manager handles multiple patient conversations simultaneously, then more patients can be served, but conversation threads may be lost and assessment completeness decreases
Solution Approach 1:
The system implements feedback mechanisms where each message is tracked through a structured workflow. The automated response system monitors conversation state, tracks which assessments have been completed for each patient, and provides feedback to the case manager about pending items, ensuring no information is lost even when handling multiple patients.
Solution Approach 2:
The system performs preliminary actions by automatically generating response options and tracking conversation state before the case manager needs to review them. This includes pre-processing patient messages, identifying required assessments, and preparing appropriate response templates, reducing the cognitive load on the case manager.
3Device complexity
If unimodal predictive systems are used for auto-response, then response generation is simplified, but the system cannot handle structured conversational flows or ad-hoc questions effectively
Solution Approach 1:
The system dynamically adapts its response generation approach based on the conversation context. It switches between structured protocols for routine assessments and more flexible, ad-hoc response generation for unexpected questions. The system's behavior changes dynamically based on the patient's message type, maintaining both structure and adaptability.
Solution Approach 2:
The automated response system is designed with multi-functionality to handle both structured conversational flows (such as standardized assessments) and ad-hoc questions. It incorporates multiple response generation modes within a single system, making it universally applicable to various communication scenarios without requiring separate systems.
4Stability of the object's composition
If structured systems are used for auto-response, then conversational flow can be controlled, but the system cannot handle ad-hoc or unexpected questions from users
Solution Approach 1:
The system dynamically adjusts its level of structure based on the conversation context. When a structured assessment is needed, it enforces the conversational flow strictly. When an ad-hoc question arises, it transitions to a more flexible mode that allows deviation from the script while maintaining overall conversation stability and eventually returning to structured protocols when appropriate.
Data Source
AI summary
Systems and methods of automatically generating a proposed response to user input are provided. A method includes receiving, via a text-based messaging system, a plurality of messages from a user, determining a respective confidence level for each message of the plurality of messages that the respective message has a respective intent corresponding to a respective defined intent, generating, responsive to the defined intent of a first message of the plurality of messages being a structured intent, a first proposed communication from the structured intent, and generating, responsive to the defined intent of a second message of the plurality of messages being a predictive intent and the confidence level of the second message meeting a defined threshold, a second proposed communication from the predictive intent.