Attempting to model referral patterns from emergency departments
Research type
Research Study
Full title
Decision support algorithms for emergency departments: Developing machine learning classifiers to predict departure points in emergency departments
IRAS ID
275577
Contact name
Neil White
Contact email
Sponsor organisation
University of Southampton
Duration of Study in the UK
1 years, 0 months, 30 days
Research summary
Using data collected by the University Hospitals Southampton Emergency Department (ED), the focus of the work will be investigating whether data collected during a given ED episode (typically lasting less than 4 hours) can be used with machine learning methodologies to predict the episode outcome (i.e., was the patient discharged, admitted to hospital or did they die?).
The study will be an entirely retrospective study, using only historical data, and data will include patient observations (e.g., blood pressure), patient laboratory tests (e.g., blood tests), patient information (e.g., date or year of birth, gender, ethnicity) and episode information (e.g., date of episode, duration of episode). The primary aim will be to validate the machine learning models we will build and compare the predictions to conventional methods.REC name
N/A
REC reference
N/A