Anatomy of a demand shock: Quantitative analysis of crowding in hospital emergency departments in Victoria, Australia during the 2009 influenza pandemic

Peter Sivey, Richard McAllister, Hassan Vally, Anna Burgess, Anne-Maree Kelly

Research output: Contribution to journalArticlepeer-review


OBJECTIVE: An infectious disease outbreak such as the 2009 influenza pandemic is an unexpected demand shock to hospital emergency departments (EDs). We analysed changes in key performance metrics in (EDs) in Victoria during this pandemic to assess the impact of this demand shock.

DESIGN AND SETTING: Descriptive time-series analysis and longitudinal regression analysis of data from the Victorian Emergency Minimum Dataset (VEMD) using data from the 38 EDs that submit data to the state's Department of Health and Human Services.

MAIN OUTCOME MEASURES: Daily number of presentations, influenza-like-illness (ILI) presentations, daily mean waiting time (time to first being seen by a doctor), daily number of patients who did-not-wait and daily number of access-blocked patients (admitted patients with length of stay >8 hours) at a system and hospital-level.

RESULTS: During the influenza pandemic, mean waiting time increased by up to 25%, access block increased by 32% and did not wait presentations increased by 69% above pre-pandemic levels. The peaks of all three crowding variables corresponded approximately to the peak in admitted ILI presentations. Longitudinal fixed-effects regression analysis estimated positive and statistically significant associations between mean waiting times, did not wait presentations and access block and ILI presentations.

CONCLUSIONS: This pandemic event caused excess demand leading to increased waiting times, did-not-wait patients and access block. Increases in admitted patients were more strongly associated with crowding than non-admitted patients during the pandemic period, so policies to divert or mitigate low-complexity non-admitted patients are unlikely to be effective in reducing ED crowding.

Original languageEnglish
Pages (from-to)e0222851
JournalPLoS ONE
Issue number9
Early online date24 Sept 2019
Publication statusE-pub ahead of print - 24 Sept 2019

Bibliographical note

© 2019 Sivey et al.


  • Crowding
  • Disease Outbreaks/statistics & numerical data
  • Emergency Service, Hospital/statistics & numerical data
  • Health Services Needs and Demand/statistics & numerical data
  • Hospitalization/statistics & numerical data
  • Humans
  • Influenza, Human/diagnosis
  • Length of Stay/statistics & numerical data
  • Pandemics/statistics & numerical data
  • Time Factors
  • Workload/statistics & numerical data

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