NLP Nursing Record Automation for Module Prediction
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Solution Overview
Problem
Nurses face inefficiencies and data integrity issues when manually recording nursing information, often neglecting to fill in important modules due to the tediousness and complexity of existing nursing information systems, leading to incomplete records and inaccurate quality indicator analysis.
Innovation Solution
A nursing information module automation system using natural language processing (NLP) technology to interpret nursing records, predict care focuses, and recommend relevant modules, incorporating semantics extraction to assist caregivers in filling out records efficiently and ensuring data integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If nurses manually record nursing information in existing NIS, then nursing records can be created, but the operation is tedious and complicated causing burden to nurses and leading to incomplete records
Solution Approach 1:
The system enables self-service by automatically generating nursing records through NLP processing of nursing speech. The system extracts key information elements autonomously without requiring manual intervention from nurses, thus improving both ease of operation and record completeness simultaneously
Solution Approach 2:
The patent replaces the mechanical manual typing system with an automated speech-to-text NLP system. This substitution eliminates the tedious manual operation while maintaining high reliability through automated information extraction and structured record generation
2Loss of information
If nurses manually fill in multiple modules in NIS, then comprehensive nursing information can be recorded, but the complexity of remembering module locations and repeating information increases operational burden
Solution Approach 1:
The system merges multiple scattered nursing modules into a unified speech-based input interface. By combining all information collection functions into a single speech processing workflow, it eliminates the need for nurses to navigate multiple modules and repeat information, while ensuring data integrity through centralized processing
Solution Approach 2:
The NLP system serves as a universal interface that handles multiple nursing information collection functions simultaneously. A single speech input can trigger multiple information extraction tasks across different nursing domains, reducing operational complexity while maintaining comprehensive data collection
3Productivity
If nurses focus on writing nursing records, then nursing documentation can be completed, but they may neglect to fill in files for special events resulting in incomplete records and inaccurate quality indicator analysis
Solution Approach 1:
The system implements feedback mechanisms where the NLP processor continuously monitors nursing speech for special event keywords and triggers appropriate file generation automatically. This feedback loop ensures that quality indicators are captured accurately without requiring additional nurse attention, maintaining both productivity and measurement precision
Data Source
AI summary
The present invention relates to a nursing information module automation system and method. The method includes steps of detecting a nursing record inputted by a user; transmitting the nursing record to a nursing information module automation natural language processing model to perform a focus prediction, so as to automatically predict at least one nursing focus based on the nursing record; and recommending at least one recommended module in accordance with the at least one nursing focus by the nursing information module automation natural language processing model.