Exploring the use of Machine Learning and Natural Language Processing to teach a machine to predict whether a patient is likely to be imminently admitted to hospital based on GP data and clues in GP notes


30 Second Summary

This project used Natural Language Processing to automate key information extraction from patient notes, aiming to predict imminent hospital admissions. Findings included indicators like increased note frequency, verbosity, and specific words.

Natural Language Processing (NLP)
Primary Care (GP)
Inpatient Admissions
Hospitals
Machine Learning
NHS
Authors
Affiliations

Dr Adam Kwiatkowski

Torridge Primary Care Network

Prof Mona Nasser

Peninsula Dental Social Enterprise

Imca Hensels-Pelling

Royal Devon University Healthcare NHS Foundation Trust

This exploratory project explored the use of Natural Language Processing methods to automate the extraction of key information from free-text patient notes in order to ascertain whether clues in notes could be used to predict an imminent admission to hospital. The team found certain important aspects that seemed to offer indications of an imminent admission, such as increased frequency and verbosity of patient notes, and the use of certain words. The team is now continuing to use these preliminary insights to develop a machine learning algorithm to try to predict an imminent admission for patients in Devon.