Browsing by Author "Adetunji, Olufemi"

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    Emergency medical service response system performance in an urban South African setting: a computer simulation model
    (2014) Stein, Christopher Owen Alexander; Wallis, Lee; Adetunji, Olufemi
    This study investigated the effects of different response strategies, vehicle location strategies and vehicle numbers on response times in a simulated Emergency Medical Services system. The simulation was a computer model using discrete-event simulation and the model was based on Western Cape Emergency Medical Services operations in Cape Town. The study objectives were to (i) create the simulation model, (ii) determine the best-performing combination of explanatory factors and (iii) determine the effect of increasing vehicle numbers on response time performance. The simulation model took into account incident arrival rates, incident and hospital spatial distributions, vehicle numbers and dispatch practices in the modelled system. Verification and validation of the simulation model utilised a combination of quantitative and qualitative methods. The validated simulation model was changed in two ways: (i) the response strategy was changed to either single or two-tier (the response model factor) and (ii) the vehicle location strategy was changed to either dynamic or static (the vehicle location factor). This yielded four individual models each representing one combination of these factors. Each simulation model was run for a simulated period of seven days. Output data were analysed using multivariate analysis of variance in order to identify differences in response time between the factor combinations. A single-tier model using dynamic vehicle locations produced the best response performance. This model was run repeatedly, increasing vehicle numbers incrementally with each run to assess the effect of increased vehicle numbers on response time performance. A doubling of vehicle numbers resulted in an 14% increase in the number of responses meeting the national performance target for high acuity incidents, while a seven-fold increase in vehicle numbers increased this to 15%. No further performance increases were seen beyond this with increased vehicle numbers. A 2% performance increase for lower acuity incidents was seen with the same increase in vehicle numbers. In the system modelled, increasing vehicle numbers should not be expected to realise anything more than small improvements in response time performance, at a high operational cost. Fine-grained dynamic deployment of vehicles in anticipation of system demand appears to be a more important determinant of response performance than vehicle numbers alone.
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    Meeting national response time targets for priority 1 incidents in an urban emergency medical services system in South Africa: More ambulances won’t help
    (2015) Stein, Christopher; Wallis, Lee; Adetunji, Olufemi
    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. METHOD: 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. CONCLUSION: 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.