Performance‐based metamodel for healthcare facilities

This paper introduces an organizational model describing the response of the Hospital Emergency Department (ED). The metamodel is able to estimate the hospital capacity and the dynamic response in real time and to incorporate the influence of the damage of structural and non-structural components on the organizational ones. The waiting time is the main parameter of response and it is used to evaluate the disaster resilience index of healthcare facilities. Its behaviour is described using a double exponential function and its parameters are calibrated based on simulated data. The metamodel covers a large range of hospital configurations and takes into account hospital resources, in terms of staff and infrastructures, operational efficiency and existence of an emergency plan, maximum capacity and behaviour both in saturated and over-capacitated conditions. The sensitivity of the model to different arrival rates, hospital configurations, and capacities and the technical and organizational policies applied during and before the strike of the disaster has been investigated. This model becomes an important tool in the decision process either for the engineering profession or for the policy makers

[1]  Karin V Rhodes,et al.  The effect of crowding on access and quality in an academic ED. , 2006, The American journal of emergency medicine.

[2]  Michel Bruneau,et al.  A Framework to Quantitatively Assess and Enhance the Seismic Resilience of Communities , 2003 .

[3]  Michel Bruneau,et al.  Framework for analytical quantification of disaster resilience , 2010 .

[4]  P. Yarnold,et al.  Relating patient satisfaction to waiting time perceptions and expectations: the disconfirmation paradigm. , 1995, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[5]  R J Maxwell,et al.  Quality assessment in health. , 1984, British medical journal.

[6]  Hannah McGee,et al.  Outpatient clinic waiting times and non-attendance as indicators of quality , 2000 .

[7]  T. T. Soong,et al.  Fundamentals of Probability and Statistics for Engineers , 2004 .

[8]  S J Stratton,et al.  The 1994 Northridge Earthquake Disaster Response: The Local Emergency Medical Services Agency Experience , 1996, Prehospital and Disaster Medicine.

[9]  Dan Hanfling,et al.  Health care facility and community strategies for patient care surge capacity☆☆☆ , 2004, Annals of Emergency Medicine.

[10]  Gian Paolo Cimellaro,et al.  QUANTIFICATION OF SEISMIC RESILIENCE OF HEALTH CARE FACILITIES , 2006 .

[11]  Gian Paolo Cimellaro,et al.  Seismic resilience of a hospital system , 2010 .

[12]  G. Mosqueda,et al.  Damage to Engineered Buildings and Lifelines from Wind, Storm Surge and Debris following Hurricane Katrina , 2006 .

[13]  Francesca Valent,et al.  Are pre-hospital time and emergency department disposition time useful process indicators for trauma care in Italy? , 2007, Injury.

[14]  Gian Paolo Cimellaro,et al.  Multidimensional Performance Limit State for Hazard Fragility Functions , 2011 .

[15]  Gian Paolo Cimellaro,et al.  Quantification of Disaster Resilience of Health Care Facilities , 2009 .

[16]  A. Floren,et al.  ' " ' " ' " . " ' " " " " " ' " ' " " " " " : ' " 1 , 2001 .

[17]  Catherine A. Cardno USGS Updates National Seismic Hazard Maps , 2008 .

[18]  M. Hubble,et al.  Influence of Ambulance Arrival on Emergency Department Time to Be Seen , 2005, Prehospital emergency care : official journal of the National Association of EMS Physicians and the National Association of State EMS Directors.

[19]  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.