Development and validation of a discrete event simulation model for planning hospital based provision of blood for mass casualty events

Simon Glasgow, Christos Vasilakis, Zane Perkins, Nigel Tai, Karim Brohi

Research output: Contribution to conferenceAbstract

Abstract

Mass casualty events (MCEs) create a surge in severely injured casualties amongst which haemorrhage is a leading cause of preventable mortality. Minimising in-hospital mortality therefore demands adequate blood provision. MCE planning through live or tabletop excercies is disruptive, costly and limited in terms of experimentation. A simulation model offers potential as a practical planning tool for understanding and improving outcomes from these events.
For this study we developed a discrete event simulation model of casualty blood provision at a UK major trauma centre following a generic MCE. The model incorporated the delivery of emergency red cells to different cohorts of casualties of varied priority and blood demands. Both treatment and laboratory-based blood group processing systems were modelled. The model was validated using real-life data from the experience at the main responding major trauma centre during the London bombings of 2005.
Nearly half of all the transfused casualties on the day of the bombings received their transfusion requirement within one hour. Similarly, our simulation experiments incorporated this same amount within the interquartile range (IQR) of results across all 100 replications performed. Furthermore, there was no significant difference identified between the real world values and the model output for all individual red cell treatment times on paired t-test analysis (p value = 0.35). The other principal output of interest was individual red cell group stock levels and their rate of consumption following an event, especially in terms of emergency universal donor group O red cells. All post event real world red cell stock levels were found to fall within the IQR produced by the simulation model for each corresponding group.
In conclusion, we have designed a simulation model to aid in understanding the transfusion system levers, which potentially have the greatest impact on improving bleeding casualty outcomes following these challenging events.

Conference

ConferenceThe 41th Meeting of the EURO Working Group on Operational Research Applied to Health Services (ORAHS 2015)
CountryCanada
CityMontreal
Period19/07/1524/07/15

Fingerprint

Hospital Planning
Mass Casualty Incidents
Trauma Centers
Emergencies
Hemorrhage
Blood Group Antigens
Hospital Mortality
Mortality

Cite this

Glasgow, S., Vasilakis, C., Perkins, Z., Tai, N., & Brohi, K. (2015). Development and validation of a discrete event simulation model for planning hospital based provision of blood for mass casualty events. Abstract from The 41th Meeting of the EURO Working Group on Operational Research Applied to Health Services (ORAHS 2015), Montreal, Canada.

Development and validation of a discrete event simulation model for planning hospital based provision of blood for mass casualty events. / Glasgow, Simon; Vasilakis, Christos; Perkins, Zane; Tai, Nigel; Brohi, Karim.

2015. Abstract from The 41th Meeting of the EURO Working Group on Operational Research Applied to Health Services (ORAHS 2015), Montreal, Canada.

Research output: Contribution to conferenceAbstract

Glasgow, S, Vasilakis, C, Perkins, Z, Tai, N & Brohi, K 2015, 'Development and validation of a discrete event simulation model for planning hospital based provision of blood for mass casualty events' The 41th Meeting of the EURO Working Group on Operational Research Applied to Health Services (ORAHS 2015), Montreal, Canada, 19/07/15 - 24/07/15, .
Glasgow S, Vasilakis C, Perkins Z, Tai N, Brohi K. Development and validation of a discrete event simulation model for planning hospital based provision of blood for mass casualty events. 2015. Abstract from The 41th Meeting of the EURO Working Group on Operational Research Applied to Health Services (ORAHS 2015), Montreal, Canada.
Glasgow, Simon ; Vasilakis, Christos ; Perkins, Zane ; Tai, Nigel ; Brohi, Karim. / Development and validation of a discrete event simulation model for planning hospital based provision of blood for mass casualty events. Abstract from The 41th Meeting of the EURO Working Group on Operational Research Applied to Health Services (ORAHS 2015), Montreal, Canada.
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N2 - Mass casualty events (MCEs) create a surge in severely injured casualties amongst which haemorrhage is a leading cause of preventable mortality. Minimising in-hospital mortality therefore demands adequate blood provision. MCE planning through live or tabletop excercies is disruptive, costly and limited in terms of experimentation. A simulation model offers potential as a practical planning tool for understanding and improving outcomes from these events.For this study we developed a discrete event simulation model of casualty blood provision at a UK major trauma centre following a generic MCE. The model incorporated the delivery of emergency red cells to different cohorts of casualties of varied priority and blood demands. Both treatment and laboratory-based blood group processing systems were modelled. The model was validated using real-life data from the experience at the main responding major trauma centre during the London bombings of 2005. Nearly half of all the transfused casualties on the day of the bombings received their transfusion requirement within one hour. Similarly, our simulation experiments incorporated this same amount within the interquartile range (IQR) of results across all 100 replications performed. Furthermore, there was no significant difference identified between the real world values and the model output for all individual red cell treatment times on paired t-test analysis (p value = 0.35). The other principal output of interest was individual red cell group stock levels and their rate of consumption following an event, especially in terms of emergency universal donor group O red cells. All post event real world red cell stock levels were found to fall within the IQR produced by the simulation model for each corresponding group.In conclusion, we have designed a simulation model to aid in understanding the transfusion system levers, which potentially have the greatest impact on improving bleeding casualty outcomes following these challenging events.

AB - Mass casualty events (MCEs) create a surge in severely injured casualties amongst which haemorrhage is a leading cause of preventable mortality. Minimising in-hospital mortality therefore demands adequate blood provision. MCE planning through live or tabletop excercies is disruptive, costly and limited in terms of experimentation. A simulation model offers potential as a practical planning tool for understanding and improving outcomes from these events.For this study we developed a discrete event simulation model of casualty blood provision at a UK major trauma centre following a generic MCE. The model incorporated the delivery of emergency red cells to different cohorts of casualties of varied priority and blood demands. Both treatment and laboratory-based blood group processing systems were modelled. The model was validated using real-life data from the experience at the main responding major trauma centre during the London bombings of 2005. Nearly half of all the transfused casualties on the day of the bombings received their transfusion requirement within one hour. Similarly, our simulation experiments incorporated this same amount within the interquartile range (IQR) of results across all 100 replications performed. Furthermore, there was no significant difference identified between the real world values and the model output for all individual red cell treatment times on paired t-test analysis (p value = 0.35). The other principal output of interest was individual red cell group stock levels and their rate of consumption following an event, especially in terms of emergency universal donor group O red cells. All post event real world red cell stock levels were found to fall within the IQR produced by the simulation model for each corresponding group.In conclusion, we have designed a simulation model to aid in understanding the transfusion system levers, which potentially have the greatest impact on improving bleeding casualty outcomes following these challenging events.

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