Abstract
Freidenfields (1980) introduced for the modeling of several transport systems demands the concepts of queueing theories and studied the problem of the capacity expansion of the transport system as a random process of life and death, showing that it is possible to adapt the stochastic model of demand growth into a deterministic model. Souza (1996) applied this theory to predict the expansion of the emergency care systems. The modeling of the supply of Us integrated into the hospitals - emergency care and inter-hospital removals - despite being considered a restricted market service, as new solutions are developed new knowledge is aggregated into an increasingly lower cost (GOLDBERG, 2004). The dimensioning, allocation and distribution of the supply of Us developed for the pre-hospital mobile care system, utilizing data based on the Brazilian situation, is a field that deserves extreme attention. That will allow the assessment of the present situation and can lead to new routes in terms of public policies. Thus, the distribution of service stations of the regulation centers represents the ordering and orienting element of the State Systems of Urgency and Emergency. These centers must be structured in all levels, organizing the relation between several services, qualifying the flux of patients in the system and generating an integrative gateway for the hospitals, by which distress signals are received, evaluated and ranked. These rules must be followed by all services, both public or private. It can be mentioned, as an example, that for the emergency services a widely used measure is the maximization use of the Us or the minimization of response time TR, between any user of the transport system and the nearest hospital.
Highlights
The first models developed for care emergency services were deterministic according to (CRONK et al, 1986; GOODMAN et al, 1986) and were important for planning and investigation analysis, ignoring the stochastic considerations about the problem
As a result of the similarity of the equations mentioned, we can state that the process of distribution of K emergencies in the In entries in hospitals – injured individuals that arrive to the hospitals – spaced out from E(T EESH) is equivalent to considering that the emergency entries are independent and randomly distributed in a period of time ∆t
4) After determining the travel time and the estimation for the times T P, T A, and T D, we find the expected value of the service time E(T S) = 17, 30 mins and V (T S) = 31, 91 mins2
Summary
The first models developed for care emergency services were deterministic according to (CRONK et al, 1986; GOODMAN et al, 1986) and were important for planning and investigation analysis, ignoring the stochastic considerations about the problem. It is important to know what is the probability of an individual never being a user of the system – there never is an accident with this individual inside the region R, in a way that, by suffering an accident, he/she will be relocated to a hospital using Us as a means of transport. Knowing nL, the problem consists in calculating the maximum user population of the transport by Us, in a way that the probability of not having missing hospital beds is known (α). The solution for this problem will be important in the division of a city in assistance zones (ZA) which will correspond to the hospitals in a one-to-one relation.
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