Abstract

Medical system engineering is a theoretical discipline which unifies the methods of analysis and synthesis of complex medical systems, medical technology, and public health services in general. The work of medical institutions typically involves an abundance of medical and economic information, basically in statistical form. Mathematical models of medical institutions establish regularities in the mass of empirical information and remove distortions in the statistical data, thereby aiding the work of planning organizations. Considering medical institutions as complex queueing systems involving cost estimates of the institutions themselves and implicit losses connected with delay times, gives a theoretical basis for choosing the parameters of the medical institutions to be economically optimal. To determine these parameters we must solve problems of nonlinear programming. Some particular problems of public health services are studied: i.e., determining the optimal number of beds in a hospital and the optimal number of ambulances, and determining periodicities in conducting prophylactic examinations. The study of the systems of several medical institutions and their influence on the flow of patients leads to the use of the method of statistical simulation. A simulation using the Markov process, changing the random waiting times of individual cases to their mean values, thereby decreasing the variance of the statistical estimates, is considered. A numerical example is given, illustrating one heuristic approach to estimating the accuracy of the results of this type of simulation. The contradiction between the level of scientific achievements of medicine and the possibilities of their wide practical realization is discussed in the framework of the present system of public health services where individual forms of labor prevail, hampering the effective use of medical technology. The importance of computer automation in processing medical information is pointed out.

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