Natural Language Interface for Electronic Health Record Navigation
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Solution Overview
Problem
The complexity of data entry and limited access in Electronic Health Records (EHR) systems hinder medical professionals' ability to efficiently interact with patients and make decisions, as existing systems are cumbersome with many features and navigation layers, leading to time constraints and accuracy issues.
Innovation Solution
A natural language interface is introduced into EHR systems, allowing medical professionals to navigate and perform functions using domain-specific language and terminology, with voice or keyboard input, and incorporating context, history, and workflow to provide autosuggestions, thereby reducing the need for clicks and enhancing usability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional EHR systems are used with multiple navigation menus and features, then system functionality and completeness are improved, but ease of operation and time efficiency deteriorate
Solution Approach 1:
A natural language processing intermediary layer is introduced between the user and the EHR system. This intermediary translates natural language commands into system actions, eliminating the need for users to navigate through multiple menus and interfaces. The NLP mediator understands domain-specific terminology and contextual nuances, enabling direct access to EHR functions without traditional navigation overhead.
Solution Approach 2:
The mechanical interaction model of clicking through menus and buttons is replaced with a linguistic interaction model. Instead of physically navigating through hierarchical interfaces, users communicate with the system through natural language, which is processed and executed automatically. This substitution eliminates the mechanical burden of menu navigation while preserving full system functionality.
2Measurement precision
If traditional EHR systems require multiple clicks and navigation steps, then data access precision is maintained, but time efficiency and productivity deteriorate
Solution Approach 1:
The system performs preliminary action by pre-processing and indexing all EHR data structures, navigation paths, and available functions before user interaction. When a natural language command is received, the system already has the parsed intent and can directly execute the corresponding action without requiring the user to navigate through intermediate steps. This pre-prepared state enables instant, precise data access while maintaining high productivity.
3Adaptability or versatility
If EHR systems provide comprehensive features and options, then system capability is improved, but device complexity and navigation difficulty increase
Solution Approach 1:
The complexity of the EHR system interface is extracted and contained within the natural language processing layer. The underlying system maintains its comprehensive capabilities, but the interaction layer is simplified to pure natural language understanding. By taking out the complexity into a dedicated NLP processing layer, the user-facing interface becomes simple and intuitive while the system retains full functionality.
Data Source
AI summary
A technique involves providing a natural language interface to an electronic health record (EHR) system to enable a user to navigate the system efficiently. One or more input stimuli are received from the user via the natural language interface and converted into one or more commands that are used to change a navigational or other state of the EHR system. In an embodiment, the one or more commands are displayed in a navigation prioritized list. In an embodiment, the natural language interface is incorporated into an Internet of Things (IOT) device.