Another limitation is that the data used to validate the model outcomes may have contained erroneous transport times that could not be corrected, which is illustrated by some extremely short or very long transport times in the database provided by the RAS. In our opinion, these 4-digit, 2-letter zip codes are an acceptable proxy because these codes cover areas of a few streets at most, meaning that the actual accident scene is in close proximity. For example, instead of using the exact geographic coordinates of the accident scenes, the zip codes were used as a proxy. Although we validated the model, we must emphasize that the results are based on a mathematical model, which is of course a simplification of the real world. The transport times for these patients would, in fact, be shorter if they were to be brought to the nearest TC in an adjacent region.Ī major strength of this study is that the outcomes of the model were validated, using factual data of a large number of high-urgency cases, largely publicly available data, and commercially available GIS-based technology. Although in all scenarios roughly 98% of the population could reach the hospital within 45 minutes in both rush hour and low traffic, the transport time for the population living in the region’s periphery did increase substantially. This study showed that the transport time in the geographically less well spread 2-TC scenario (scenario 4) and in the 1-TC scenarios (scenario 5-7) exceeds the maximum time with 4 to 10 minutes. As mentioned before, the Dutch government set a time limit of approximately 20 minutes for transporting severely injured patients to the nearest TC. The influence of high traffic density on transport times was substantial in the 1-TC scenarios (5-7) and in the 2-TC scenario with 2 TCs that are geographically near to each other (scenario 4), compared with the current situation with 3 TCs in the region (scenario 1) and the situation with 2 geographically well-spread TCs (scenarios 2 and 3). This model allows for the assessment of different potential changes in the number and location of TCs in the midwest trauma region in The Netherlands, and predicts that a suboptimal approach to centralization of trauma care (scenario 4-7) could result in increased transport times to the closest TC, especially during rush hour. 12/2016: Making Choices on the Journey to Universal Health Care Coverage: From Advocacy to Analysis.2/2017: “Mapping Studies” In Cost-Utility Analyses: New Recommendations From ISPOR Task Force.2/2017: ISPOR Releases New Task Force Recommendations for the Development of Clinician-Reported Outcome Assessments.
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