Text mining of patient experience data
May 15, 2023
Patient experience
- The NHS collects a lot of patient experience data
- Rate the service 1-5 (Very poor… Excellent) but also give written feedback
- “Parking was difficult”
- “Doctor was rude”
- “You saved my life”
- Many organisations lack the staffing to read all of the feedback in a systematic way
Text mining
- We have built an algorithm to read it
- Fits alongside other work happening within NHSE
- A framework for understanding patient experience
Patient experience 101
- Tick box scoring is not useful (or accurate)
- Text based data is complex and built on human experience
- We’re not making word clouds!
- We’re not classifying movie reviews or Reddit posts
- The tool should enhance, not replace, human understanding
- “A recommendation engine for feedback data”
Everything open, all the time
- This project was coded in the open and is MIT licensed
- Engage with the organisations as we find them
- Do they want code or a docker image?
- Do they want to fetch their own themes from an API?
- Do they want to use our dashboard?
Phase 1
- 10 categories and moderate performance on criticality analysis
- scikit-learn
- Shiny
- Reticulate
- R package of Python code
Golem all the things!
- Opinionated way of building Shiny
- Allows flexibility in deployed versions using YAML
- Agnostic to deployment
- Emphasises dependency management and testing
- Separate “reactive” and “business” logic (see the accompanying book)
Making it useful
- Accurately rating low frequency categories
- Per category precision and recall
- Speed versus accuracy
- Representing the thematic structure
The future
- Off the shelf, proprietary data collection systems dominate
- They often offer bundled analytic products of low quality
- The DS time can’t and doesn’t want to offer a complete data system
- How can we best contribute to improving patient experience for patients in the NHS?
- If the patient experience data won’t come to the mountain…
Open source FTW!
- Often individuals in the NHS don’t want private companies to “benefit” from open code
- But if they make their products better with open code the patients win
- Best practice as code
The projects
- https://github.com/CDU-data-science-team/pxtextmining
- https://github.com/CDU-data-science-team/experiencesdashboard
- https://github.com/CDU-data-science-team/PatientExperience-QDC
The team
- YiWen Hon (Python & Machine learning)
- Oluwasegun Apejoye (Shiny)
Contact:
- chris.beeley1@nhs.net
- https://fosstodon.org/@chrisbeeley