Hospital selection and patient transport model in the emergency medical system

We designed a model for hospital selection and patient transport in the emergency medical system. The model integrates the criterium of insurance coverage, seldom used in the literature and the usual criteria such as care capacities, congestion and proximity, typical of countries with mixed health systems (public-private). In addition, the model considered the travel and waiting times in emergency departments as performance measures in different time slots and days of the week. We developed and implemented a prototype in the Python programming language connecting to web services from Google Maps API (Directions, Maps JavaScript) to support the decision-making process in real-time and tested its performance. This research study validated the model with actual data from events managed by the emergency medical system in a Colombian city. We used Monte Carlo simulation to predict the current and proposed models’ travel and transfer time (travel time + waiting time). The simulation results indicate that the proposed model, which considers insurance coverage, emergency departments capacities, congestion and proximity, has a lower probability of putting at risk the lives of critically ill patients. In addition, non-critical patient satisfaction increases as wait times decrease.