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 careAuthor-Name: Pagel, Christina

Padmanabhan Ramnarayan, Samiran Ray and Mark J. Peters

European Journal of Operational Research, 2018, vol. 264, issue 3, 847-858

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) to tune the algorithms and one winter to test the final method (2013/14). The optimal Bollinger band thresholds were 1.2 and 1 standard deviations above and below a 41-day moving average of demand respectively. A simple linear model was found to predict the end of the surge and overall demand volume as soon as the start had been identified. Applying the method to the validation winter of 2013/14 showed excellent performance, with the surge identified from 18th November 2013 to 4th January 2014.

Keywords: OR in health services; Analytics; Statistical process control; Implementation; Emergency medical services (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:264:y:2018:i:3:p:847-858

DOI: 10.1016/j.ejor.2016.08.023

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