Load Balancing at Emergency Departments using ‘Crowdinforming’

Emergency Department overcrowding is an important healthcare issue garnering significant public and regulatory scrutiny in Canada and around the world. Many approaches to alleviate excessive waiting times and lengths of stay have been considered and implemented to various degrees. In theory, a more optimal emergency department patient flow may be assisted via balancing patient loads between emergency departments within the region - in essence spreading patients more evenly throughout this system. This investigation uses available data for one regional health authority, and utilizes simulation to explore a process control strategy built on ‘crowdinforming’, aimed to balance patient loads between six Emergency Departments within a mid-sized Canadian city. The preliminary model uses patient arrival rates as an indicator of ‘busyness’ and as the basis for crowdinforming. Intuitively expected metrics such as the number of patients waiting, the average length of stay, and time waiting to be seen were not found to be meaningful metrics of emergency department ‘busyness’ with this particular data set for the purpose of a process control strategy.

[1]  M. Cooke,et al.  The effect of a separate stream for minor injuries on accident and emergency department waiting times , 2002, Emergency medicine journal : EMJ.

[2]  D. Magid,et al.  Emergency department crowding: consensus development of potential measures. , 2003, Annals of emergency medicine.

[3]  L J Shuman,et al.  An emergency department simulation and a neural network metamodel. , 1997, Journal of the Society for Health Systems.

[4]  Steven L Bernstein,et al.  Development and validation of a new index to measure emergency department crowding. , 2003, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[5]  Soemon Takakuwa,et al.  Modeling of patient flows in a large-scale outpatient hospital ward by making use of electronic medical records , 2007, 2007 Winter Simulation Conference.

[6]  Lawrence M Lewis,et al.  The impact of input and output factors on emergency department throughput. , 2007, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[7]  Albert-László Barabási,et al.  Limits of Predictability in Human Mobility , 2010, Science.

[8]  Dominik Aronsky,et al.  Crowding delays treatment and lengthens emergency department length of stay, even among high-acuity patients. , 2009, Annals of emergency medicine.

[9]  Margaret A. Draeger,et al.  An emergency department simulation model used to evaluate alternative nurse staffing and patient population scenarios , 1992, WSC '92.

[10]  Donna Kelly,et al.  Impact of rapid entry and accelerated care at triage on reducing emergency department patient wait times, lengths of stay, and rate of left without being seen. , 2005, Annals of emergency medicine.

[11]  N. Rathlev,et al.  Time series analysis of variables associated with daily mean emergency department length of stay. , 2007, Annals of emergency medicine.

[13]  Alex Kiss,et al.  The effect of low-complexity patients on emergency department waiting times. , 2007, Annals of emergency medicine.

[14]  F. P. Wieland,et al.  UNDERSTANDING ACCIDENT AND EMERGENCY DEPARTMENT PERFORMANCE USING SIMULATION , 2006 .

[15]  Ò. Miró,et al.  Analysis of patient flow in the emergency department and the effect of an extensive reorganisation , 2003, Emergency medicine journal : EMJ.

[16]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[17]  L. LeBlanc,et al.  Modeling emergency department operations using advanced computer simulation systems. , 1989, Annals of emergency medicine.

[18]  B. Mcnicholl,et al.  Team triage improves emergency department efficiency , 2004, Emergency Medicine Journal.

[19]  Robert Dunn Reduced access block causes shorter emergency department waiting times: An historical control observational study. , 2003, Emergency medicine.

[20]  Bruria Adini,et al.  Can patient flow be effectively controlled? , 2011, Health policy and planning.

[21]  P R Yarnold,et al.  How accurate are waiting time perceptions of patients in the emergency department? , 1996, Annals of emergency medicine.

[22]  Craig O'Neill,et al.  Computer Modeling of Patient Flow in a Pediatric Emergency Department Using Discrete Event Simulation , 2007, Pediatric emergency care.

[23]  Martin Schulz,et al.  ScalaTrace: Scalable compression and replay of communication traces for high-performance computing , 2008, J. Parallel Distributed Comput..

[24]  Todd G Nick,et al.  Estimating the degree of emergency department overcrowding in academic medical centers: results of the National ED Overcrowding Study (NEDOCS). , 2004, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[25]  J. Richards,et al.  Overcrowding in the nation's emergency departments: complex causes and disturbing effects. , 2000, Annals of emergency medicine.

[26]  J. Wiler,et al.  Optimizing emergency department front-end operations. , 2010, Annals of emergency medicine.

[27]  S. Trzeciak,et al.  Emergency department overcrowding in the United States: an emerging threat to patient safety and public health , 2003, Emergency medicine journal : EMJ.

[28]  H G Garrison,et al.  When the safety net is unsafe: real-time assessment of the overcrowded emergency department. , 2001, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[29]  A. Roalfe,et al.  Total time in English accident and emergency departments is related to bed occupancy , 2004, Emergency Medicine Journal.

[30]  P R Yarnold,et al.  Effects of actual waiting time, perceived waiting time, information delivery, and expressive quality on patient satisfaction in the emergency department. , 1996, Annals of emergency medicine.

[31]  Dominik Aronsky,et al.  The measurement of daily surge and its relevance to disaster preparedness. , 2006, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[32]  Simon Cooper,et al.  The “4-hour target”: emergency nurses’ views , 2007, Emergency Medicine Journal.

[33]  Ruth Brown,et al.  Factors that affect the flow of patients through triage , 2007, Emergency Medicine Journal.

[34]  Peter Sprivulis,et al.  Internet-accessible Emergency Department Workload Information Reduces Ambulance Diversion , 2005, Prehospital emergency care : official journal of the National Association of EMS Physicians and the National Association of State EMS Directors.