Statistical methods for supporting urgent care delivery

Abstract

Forecasting procedures were developed and implemented in an out-of-hours GP provider in the North East of England to ensure staffing levels were optimised, and server performance was investigated. Initial methods included linear regression to predict calls per day into a call centre, loess to predict arrival rates, and moving averages to deal with unexpected flu pandemics. We also tried to understand the behaviour of GPs and develop a fair rating system, based on their speed. Finally, we introduced some novel dissemination techniques so that the procedures could be completed by non-experts through the implementation of the RExcel software.