AI Patient Visit Notes Using Triggered Templates and Parallel Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for documenting patient visits by doctors are time-consuming, diverting attention from patient care as doctors spend significant time preparing notes after the visit.
Innovation Solution
An artificial intelligence (AI) system that analyzes conversations between doctors and patients in real-time, generates decision support insights, and automatically creates patient visit notes using templates triggered by specific phrases from the conversation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If doctors manually prepare patient visit notes after conversations, then the notes can be accurately documented, but the time required for documentation increases significantly
Solution Approach 1:
The system performs preliminary actions by automatically generating patient visit notes during or immediately after the doctor-patient conversation, using AI to analyze the conversation and populate note templates in advance, eliminating the need for manual post-visit documentation
Solution Approach 2:
The system enables self-service documentation where the AI automatically analyzes conversation data, identifies trigger phrases, selects appropriate templates, and generates complete patient visit notes without requiring manual intervention from the doctor, allowing the note to write itself based on the conversation transcript
2Loss of information
If doctors spend time preparing detailed notes after patient visits, then comprehensive patient records are created, but the time available for patient care is reduced
Solution Approach 1:
The system performs preliminary documentation actions during the patient visit itself, with the AI analyzing the conversation in real-time and preparing note content before the doctor leaves the patient's office, ensuring comprehensive records are created without extending the visit duration
Solution Approach 2:
The AI system performs self-service by automatically generating comprehensive patient records from conversation analysis, eliminating the need for doctors to manually document after visits, thereby preserving all patient information while freeing up doctor time for additional patient care
3Manufacturing precision
If multiple sections of patient notes are generated sequentially, then each section can be thoroughly processed, but the overall note generation time increases
Solution Approach 1:
The system segments the patient visit note into multiple independent sections (subjective, objective, assessment, plan), each associated with specific trigger phrases, allowing each section to be processed independently and in parallel by separate AI instances
Solution Approach 2:
The system transitions from sequential single-instance processing to parallel multi-instance processing by deploying multiple AI instances that work simultaneously on different note sections, adding a parallelism dimension to the processing architecture and dramatically reducing overall generation time while maintaining section quality
Data Source
AI summary
In some aspects, an artificial intelligence (AI) performs an analysis of a conversation between a doctor and a patient, determines a first trigger phrase in the conversation, and determines a template of a patient visit note based on the first trigger phrase. The AI determines a second trigger phrase in the conversation, determines a particular treatment plan from a plurality of treatment plans based on the second trigger phrase, and adds the particular treatment plan to the template. A first instance of the AI adds a first portion of the conversation to the template and a second instance of the AI, in parallel with the first portion of the conversation being added to the template, adds a second portion of the conversation to the template. The AI provides the template of the patient visit note to a device associated with the doctor.