Send Orders for Reprints to reprints@benthamscience.ae The Ergonomics Open Journal, 2017, 10, 1-13 1 1875-9343/17 2017 Bentham Open The Ergonomics Open Journal Content list available at: www.benthamopen.com/TOERGJ/ DOI: 10.2174/1875934301710010001 RESEARCH ARTICLE Forecasting Hourly Patient Visits in the Emergency Department to Counteract Crowding Morten Hertzum * Royal School of Library and Information Science, University of Copenhagen, Copenhagen, Denmark Received: September 27, 2016 Revised: February 23, 2017 Accepted: March 03, 2017 Abstract: Background: Emergency Department (ED) crowding is a frequent problem that causes prolonged waiting and increased risk of adverse events. While the number of daily and monthly patient arrivals can be forecasted with good accuracy, ED clinicians need hourly forecasts in their ongoing scheduling and rescheduling of their work. Objective: We aim to assess whether the hour-by-hour evolution in patient arrivals and ED occupancy can be accurately forecasted using calendar variables. Method: We obtained data about the patient visits at four Danish EDs from January 2012 to January 2015, a total of 393717 ED visits. The data for 2012-2014 were used to create linear regression models, autoregressive integrated moving average (ARIMA) models, and – for purposes of comparison – naïve models of hourly patient arrivals and ED occupancy. Using the models, patient arrivals and ED occupancy were forecasted for every hour of January 2015. Results: Hourly patient arrivals were forecasted with a mean percentage error of 47-58% (regression), 49-58% (ARIMA), and 60-76% (naïve). Increasing the forecasting interval decreased the mean percentage error. ED occupancy was forecasted with better accuracy by ARIMA than regression models. With ARIMA the mean percentage error of the forecasts of the hourly ED occupancy was 69-73% for three of the EDs and 101% for the last ED. Factors beyond calendar variables might possibly have improved the models of ED occupancy, provided that information about these factors had been consistently available. Conclusion: Hourly patient arrivals can be forecasted with decent accuracy. Forecasts of hourly ED occupancy are less accurate and their accuracy varies more across EDs. Keywords: Crowding, Emergency department, Forecasting, Occupancy, Patient arrivals, Healthcare. 1. INTRODUCTION The common entry point to hospitals for nearly all patients with acute problems is the emergency department (ED), which is a busy – sometimes hectic – place where severely injured persons may arrive at little notice, yet the bulk of the patients have unalarming injuries. EDs become crowded “when the identified need for emergency services exceeds * Address correspondence to this author at the Royal School of Library and Information Science, University of Copenhagen, Njalsgade 76, Bldg 4, Copenhagen, Denmark; Tel: 45 3234 1344; E-mail: hertzum@hum.ku.dk