EMR-Based Dialog Service for Electronic Medical Records
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional dialog services in electronic devices struggle to efficiently determine the topic of conversation and maintain high recognition rates, especially in medical information services where user authentication and confidentiality are critical, due to the need for predefined topics and preset dialog options.
Innovation Solution
An electronic device initiates a dialog by generating and transmitting utterance data based on stored electronic medical record (EMR) data before receiving user input, allowing it to lead the conversation and authenticate the user, thereby determining the topic and enhancing recognition rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the dialog service uses predefined topics and preset dialog options to interpret user utterances, then the device can execute functions based on user inputs, but the dialog recognition rate decreases when dealing with multiple different topics
Solution Approach 1:
The server performs preliminary actions by proactively initiating dialog topics and generating utterance data before receiving user inputs. The system determines topics in advance based on stored EMR data and sends relevant utterances to the user device, allowing the user to respond to pre-determined topics rather than relying on user-initiated queries. This preliminary topic determination enables the system to maintain high recognition rates across multiple topics by having the user device send responses based on pre-identified EMR-related topics.
2Ease of operation
If the dialog service waits for user input to determine the topic, then the user can freely initiate conversations, but the service provider cannot specify the topic and facilitate user interaction efficiently
Solution Approach 1:
The server performs preliminary actions by proactively initiating dialog topics and generating utterance data before receiving user inputs. The system determines topics in advance based on stored EMR data and sends relevant utterances to the user device, allowing the user to respond to pre-determined topics rather than relying on user-initiated queries. This preliminary topic determination enables the system to maintain high recognition rates across multiple topics by having the user device send responses based on pre-identified EMR-related topics.
3Adaptability or versatility
If the dialog service processes medical information, then the system can provide healthcare-related services, but user authentication and confidentiality protection become critical requirements
Solution Approach 1:
The system performs self-service authentication by automatically identifying the user through the user device and accessing stored EMR data without requiring manual authentication steps. The server device autonomously determines which EMR data corresponds to the logged-in user and generates relevant utterance data based on that data, eliminating the need for complex manual authentication processes while maintaining security through automated user identification and data access controls.
Data Source
AI summary
An electronic device and method are disclosed herein. The electronic device includes a communication interface, a processor and a memory. The processor implements the method, including detecting a login to a first user account through a communication interface, identifying electronic medical record (EMR) data stored in a memory corresponding to the first user account based at least in part on a result of the detected login, generate first utterance data for output through a user device based at least in part on the stored EMR data, wherein the first utterance data is generated before any data associated with utterance is received from the user device; and transmitting the generated first utterance data to the user device through the communication interface for output by the user device.