title: Meeting national response time targets for priority 1 incidents in an urban emergency medical services system in South Africa: More ambulances won't help.
abstract: BACKGROUND
  Response time is viewed as a key performance indicator in most emergency medical services (EMS) systems.
  
  
  OBJECTIVE
  To determine the effect of increased emergency vehicle numbers on response time performance for priority 1 incidents in an urban EMS system in Cape Town, South Africa, using discrete-event computer simulation.
  
  
  METHODS
  A simulation model was created, based on input data from part of the EMS operations. Two different versions of the model were used, one with primary response vehicles and ambulances and one with only ambulances. In both cases the models were run in seven different scenarios. The first scenario used the actual number of emergency vehicles in the real system, and in each subsequent scenario vehicle numbers were increased by adding the baseline number to the cumulative total.
  
  
  RESULTS
  The model using only ambulances had shorter response times and a greater number of responses meeting national response time targets than models using primary response vehicles and ambulances. In both cases an improvement in response times and the number of responses meeting national response time targets was observed with the first incremental addition of vehicles. After this the improvements rapidly diminished and eventually became negligible with each successive increase in vehicle numbers. The national response time target for urban areas was never met, even with a seven-fold increase in vehicle numbers.
  
  
  CONCLUSIONS
  The addition of emergency vehicles to an urban EMS system improves response times in priority 1 incidents, but alone is not capable of the magnitude of response time improvement needed to meet the national response time targets.
authors.affiliation: Department of Emergency Medical Care, Faculty of Health Sciences, University of Johannesburg, South Africa. cstein@uj.ac.za.
authors.forename: Christopher
authors.initials: C
authors.lastname: Stein
authors.forename: Lee
authors.initials: L
authors.lastname: Wallis
authors.forename: Olufemi
authors.initials: O
authors.lastname: Adetunji
mesh_terms: D000552:Ambulances; D003198:Computer Simulation; D004632:Emergency Medical Services / Q000458:organization & administration*; D006801:Humans; D013019:South Africa; D013997:Time Factors; D019037:Urban Health Services / Q000458:organization & administration*