Literature DB >> 7950052

Optimal location for a helicopter in a rural trauma system: prediction using discrete-event computer simulation.

D E Clark1, D R Hahn, R W Hall, R E Quaker.   

Abstract

A discrete-event computer simulation was developed using the C programming language to determine the optimal base location for a trauma system helicopter in Maine, a rural area with unevenly distributed population. Ambulance run reports from a one-year period provided input data on the times and places where major injuries occurred. Data from a statewide trauma registry were used to estimate the percentage of cases which would require trauma center care and the locations of functional trauma centers. Climatic data for this region were used to estimate the likelihood that a helicopter could not fly due to bad weather. The incidence of trauma events was modeled as a nonstationary Poisson process, and location of the events by an empirical distribution. For each simulated event, if the injuries were sufficiently severe, if weather permitted flying, if the occurrence were not within 20 miles of a center or outside the range of the helicopter, and if the helicopter were not already in service, then it was used for transportation. 35 simulated years were run for each of 4 proposed locations for the helicopter base. One of the geographically intermediate locations was shown to produce the most frequent utilization of the helicopter. Discrete-event simulation is a potentially useful tool in planning for emergency medical services systems. Further refinements and validation of predictions may lead to wider utilization.

Entities:  

Mesh:

Year:  1994        PMID: 7950052      PMCID: PMC2247741     

Source DB:  PubMed          Journal:  Proc Annu Symp Comput Appl Med Care        ISSN: 0195-4210


  8 in total

1.  RURALSIM: the design and implementation of a rural EMS simulator.

Authors:  L J Shuman; H Wolfe; M J Gunter
Journal:  J Soc Health Syst       Date:  1992

2.  A procedure for locating emergency-service facilities for all possible response distances.

Authors:  A W Neebe
Journal:  J Oper Res Soc       Date:  1988-08

3.  Simulation of emergency medical service scheduling.

Authors:  C R White; J B Best; C K Sage
Journal:  Hosp Top       Date:  1992

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Authors:  T D Valenzuela; J Goldberg; K T Keeley; E A Criss
Journal:  Ann Emerg Med       Date:  1990-08       Impact factor: 5.721

5.  Utilization prediction for helicopter emergency medical services.

Authors:  A R Macione; D E Wilcox
Journal:  Ann Emerg Med       Date:  1987-04       Impact factor: 5.721

6.  Planning for emergency ambulance service systems.

Authors:  E D Hill; J L Hill; L M Jacobs
Journal:  J Emerg Med       Date:  1984       Impact factor: 1.484

7.  Predicting the utilization of helicopter emergency medical services: an approach based on need.

Authors:  K J Rhee; R E Burney; J R Mackenzie; J Flora
Journal:  Ann Emerg Med       Date:  1984-10       Impact factor: 5.721

8.  A comparison of the costs and performance of an emergency helicopter and land ambulances in a rural area.

Authors:  J P Nicholl; N R Beeby; J E Brazier
Journal:  Injury       Date:  1994-04       Impact factor: 2.586

  8 in total
  1 in total

1.  Understanding Emergency Care Delivery Through Computer Simulation Modeling.

Authors:  Lauren F Laker; Elham Torabi; Daniel J France; Craig M Froehle; Eric J Goldlust; Nathan R Hoot; Parastu Kasaie; Michael S Lyons; Laura H Barg-Walkow; Michael J Ward; Robert L Wears
Journal:  Acad Emerg Med       Date:  2017-09-21       Impact factor: 3.451

  1 in total

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