EMR Template Speech Input for Accurate Medical Record Filling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing speech-recognition technologies in the medical field face challenges with homophones and limited accuracy, necessitating manual correction in electronic medical record (EMR) template input, leading to labor-intensive data entry and increased costs for customization.
Innovation Solution
A system utilizing structured EMR templates with selectable and free-text input content, combined with speech-recognition technology, identifies input items and content through designated medical terms, and includes a speech input guide UI to enhance precision and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If speech-recognition processing is performed using a specialized dictionary in the medical field, then speech recognition capability is provided, but accuracy is limited due to homophones with different written forms, requiring manual correction
Solution Approach 1:
The system performs preliminary action by automatically filling EMR template fields based on speech recognition results before manual review. The processor automatically identifies input items and input content from speech data and populates the EMR template, reducing the need for manual data entry while maintaining the ability to correct inaccuracies.
Solution Approach 2:
The system implements feedback by allowing manual correction of speech recognition results. The EMR template display shows both automatically filled content and fields requiring manual input, enabling users to review and correct inaccuracies. This feedback loop ensures high accuracy while maintaining automation benefits.
2Measurement precision
If manual correction is performed for speech-recognition errors, then accuracy is improved, but labor intensity and time consumption increase
Solution Approach 1:
The system performs preliminary action by automatically identifying and filling EMR template fields based on speech recognition. The processor automatically maps speech data to input items and input content, reducing the time needed for manual data entry while maintaining accuracy through subsequent review.
Solution Approach 2:
The system enables self-service by automatically populating EMR templates without requiring manual data entry for each field. The speech recognition system automatically identifies relevant information and fills appropriate fields, reducing labor intensity while allowing manual correction when necessary.
3Productivity
If speech-recognition technology is implemented for EMR input, then productivity is improved, but customization costs increase due to the need for specialized dictionaries and processing
Solution Approach 1:
The system achieves universality by using a general-purpose speech recognition processor that can handle multiple EMR template types through software configuration rather than hardware customization. The processor identifies input items and input content based on template structure, eliminating the need for expensive specialized hardware or custom dictionaries while maintaining high productivity.
Solution Approach 2:
The system applies parameter changes by configuring the speech recognition processor through software parameters rather than hardware customization. The processor can be adapted to different EMR templates by changing identification parameters and mapping rules, reducing customization costs while maintaining improved productivity.
Data Source
AI summary
A terminal device includes a memory; and one or more processors operatively coupled to the memory and configured to maintain, in the memory, structured data of an electronic medical record (EMR) template, the structured data associating input items of the EMR template with input content, the input content including at least one of selectable input content and free text input content, accept, from a user, text data including an input item of the EMR template and input content corresponding to the input item, and identify, based on at least one of the selectable input content and the free text input content included in the text data, record content to populate the EMR template data.