Development and implementation of a real time statistical control method to identify the start and end of the winter surge in demand for paediatric intensive care

Abstract

Winter surge management in intensive care is hampered by the annual variability in the winter surge.We aimed to develop a real-time monitoring system that could promptly identify the start, and accurately predict the end, of the winter surge in a paediatric intensive care (PIC) setting. We adapted a statistical process control method from the stock market called "Bollinger bands" that compares current levels of demand for PIC services to thresholds based on the medium term average demand.Algorithms to identify the start and end of the surge were developed for a specific PIC service: the North Thames Children's Acute Transport Service (CATS) using eight winters of data (2005-12) 3

Using a genetic algorithm to solve a non-linear location allocation problem for specialised children’s ambulances in England and Wales

“…When there is no team available for a referral (if all teams are out on a retrieval), a sick child at the DGH will have to wait longer for specialist care. While relatively rare, such delays do happen, particularly in winter when demand for PICRT services almost doubles (Ramnarayan S. et al, 2018) (Ramnarayan S. et al, 2015). With such a centralised service, important questions are: how many PICRT locations should there be?…”

Modelling the association between weather and short-term demand for children’s intensive care transport services during winter in the South East of England

“…There is a strong seasonal component to demand for CATS services -the number of referrals almost doubles during winter [5,6]. In addition to modelling these effects, however, a key focus of the present study is short-term weatherinduced fluctuations in demand for the service during winter.…”