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

TY - JOUR

T1 - Anatomy of a demand shock

T2 - Quantitative analysis of crowding in hospital emergency departments in Victoria, Australia during the 2009 influenza pandemic

AU - Sivey, Peter

AU - McAllister, Richard

AU - Vally, Hassan

AU - Burgess, Anna

AU - Kelly, Anne-Maree

N1 - © 2019 Sivey et al.

PY - 2019/9/24

Y1 - 2019/9/24

N2 - 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.

AB - 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.

KW - Crowding

KW - Disease Outbreaks/statistics & numerical data

KW - Emergency Service, Hospital/statistics & numerical data

KW - Health Services Needs and Demand/statistics & numerical data

KW - Hospitalization/statistics & numerical data

KW - Humans

KW - Influenza, Human/diagnosis

KW - Length of Stay/statistics & numerical data

KW - Pandemics/statistics & numerical data

KW - Time Factors

KW - Workload/statistics & numerical data

U2 - 10.1371/journal.pone.0222851

DO - 10.1371/journal.pone.0222851

M3 - Article

C2 - 31550288

SN - 1932-6203

VL - 14

SP - e0222851

JO - PLoS ONE

JF - PLoS ONE

IS - 9

ER -