A computer-based simulator for air ambulance system analysis, design and optimization.
BACKGROUND
Little is known about how best to quantitatively measure air medical system performance and optimally manage air medical emergency medical services start-up, operation and growth. Moreover, very little has been done to produce and distribute relevant tools for these critical tasks.


METHODS
A hypothetical system modeled on the Ontario, Canada, air ambulance operation.


METHODS
A user-friendly, high-performance computer simulation tool for air ambulance system design, quality management and optimization was developed. In this report, the authors describe the simulator's basic structure and method of operation and present the initial findings for application to the Ontario air ambulance system. The tool tested the hypothesis that if shorter patient transfer times positively influence patient survival and higher aircraft performance, as measured by block speed, has a positive correlation with aircraft direct operating costs, then there is a pattern of "best matching" between aircraft performance, flight economics and patient survival probability for the system.


RESULTS
In the Ontario air ambulance system, an additional outlay in direct operating costs of $100 per flight yields an improvement in system quality, as measured by an improvement of 1% to 30% in the predicted patient survival probability, depending on the reference cohort and the efficacy of the life support procedures administered by the air crew.


CONCLUSIONS
A notable feature of this model is that it separates the impact of air medical transport on patient survival from subsequent measures undertaken at the emergency department after delivery to the trauma center. The current needs of the air medical transport industry, combined with the progress to date, suggest that computer-based simulators can be a powerful, cost-effective means of extracting meaning from air medical data and applying the results to productive ends.
Institute of Medical Sciences and Department of Medicine, University of Toronto, Ontario, Canada.
A B
AB
Stundzia
C J
CJ
Lumsden
D017732:Air Ambulances / Q000191:economics / Q000592:standards* / Q000706:statistics & numerical data; D003198:Computer Simulation; D003365:Costs and Cost Analysis; D008020:Life Support Care / Q000592:standards / Q000706:statistics & numerical data; D015233:Models, Statistical; D009864:Ontario; D015397:Program Evaluation / Q000379:methods; D011785:Quality Assurance, Health Care; D013597:Systems Analysis