UPDATE:
Much progress has been made on this project.
Goal
The Intelligent Chart Summarization project is an effort led by Dr. André Millet. Dr. Millet has put forth an idea of using an algorithm to summarize the most vital parts of a patient’s timeline. This project will extract out relevant medical codes for each unstructured encounter and work with @JBW and @toolbox on the analytics side.
Resources
- Picture of web ui: https://raw.githubusercontent.com/GoTeamEpsilon/cTAKES-Friendly-Web-UI/master/sample-visit-note.PNG
- Repos: https://github.com/GoTeamEpsilon/cTAKES-Intelligent-Chart-Summarization-Solution
- Getting started video: https://www.youtube.com/watch?v=0V584l8J8_Y
- Tasks management Intelligent Chart Summarization project · GitHub
- C_ClinicalDocumentProcessing.class.php example: https://gist.github.com/MatthewVita/5de7971e1adfb8724bdb989aa23317de
- Parser example: https://gist.github.com/MatthewVita/06a8c99339c3cb04d88c6646208ee37b
- Demo 1: https://i.imgur.com/liMVBwM.gifv
- Demo 2: GitHub - TheToolbox/ctakes-mockup
- related issue: Create Timeline View of Patient · Issue #808 · openemr/openemr · GitHub
Notes
- Need to get ICD working as well
- There will be a GLOBALS feature toggle for this as it requires additional setup (docker). We must document everything in the wiki!
Workflow
- Provider creates encounter
- Enters free form notes
- Clicks save
- Text is HTTP POST’ed to the Docker solution (the head of the pipeline) via an HTTP endpoint over there
- Text is processed
- At the tail of the pipeline (i.e.: after Python does its parsing), an HTTP POST is made to an OpenEMR controller endpoint called
/ctakes/{pid}/content
which stores the ctakes JSON into the database - cTAKES SNOMED/RXNORM codes are available for viewing in the encounter form notes
Team
- @MatthewVita and TeamEpsilon
- @andremillet
- @toolbox
- @brady.miller (who I am volunteering because he expressed interest :))
Chatroom
#ctakes