Probabilistic Forecasting of Patient Waiting Times in an Emergency Department

33 Pages Posted: 23 Jun 2020

See all articles by Siddharth Arora

Siddharth Arora

University of Oxford - Said Business School

James W. Taylor

University of Oxford - Said Business School

Ho-Yin Mak

University of Oxford - Said Business School

Date Written: May 30, 2020

Abstract

We study the estimation of the probability distribution of individual patient waiting times in an emergency department (ED). Our feature-rich modelling allows for dynamic updating and refinement of waiting time estimates as patient- and ED-specific information (e.g., patient condition, ED congestion levels) is revealed during the waiting process. Aspects relating to communicating forecast uncertainty to patients, and implementing this methodology in practice, are also discussed.

Keywords: machine learning, quantile regression forest, managing patient-flow

Suggested Citation

Arora, Siddharth and Taylor, James W. and Mak, Ho-Yin, Probabilistic Forecasting of Patient Waiting Times in an Emergency Department (May 30, 2020). Available at SSRN: https://ssrn.com/abstract=3614760 or http://dx.doi.org/10.2139/ssrn.3614760

Siddharth Arora (Contact Author)

University of Oxford - Said Business School ( email )

Park End Street
Oxford, OX1 1HP
Great Britain

James W. Taylor

University of Oxford - Said Business School ( email )

Park End Street
Oxford, OX1 1HP
Great Britain

Ho-Yin Mak

University of Oxford - Said Business School ( email )

Park End Street
Oxford, OX1 1HP
Great Britain

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