Forecasting modelling for A&E attendance


30 Second Summary

The project aims to forecast A&E attendances 6 weeks in advance, considering seasonal patterns. This helps manage limited resources, plan staffing levels, and assess the need for escalation during abnormal events. Using Time Series Forecasting and a Repeatable Analytical Pipeline, the project addresses the unpredictability of A&E demand influenced by various factors.

Forecasting
Reproducible Analytical Pipelines (RAP)
Emergency Departments
Demand & Capacity
Seasonality
Author
Affiliation

Yu Qiao

Liverpool University Hospitals NHS Foundation Trust

The aim of this project is to forecast future A&E attendances 6 weeks in advance, accounting for seasonal patterns.

NHS A&E is under pressure nationwide for a long-time and often we do not know what lies ahead of us to manage the limited resources available and understand when interventions and helps are needed. This is in addition to seasonal pressures.

Currently A&E has a challenging time looking ahead and manage staffing level needed to match the demand. Furthermore, this can help staff to assess if an escalation process is needed when the abnormal events occur.

A&E is known for its unpredictability in demand that varies with seasonal trend, location, population, weather and various of other factors.

The project will use Time Series Forecasting methods and a Repeatable Analytical Pipeline for Deployment.