Emergency department optimization by simulation: two actual applications

The Emergency Department of a hospital is devoted to provide first aid to outpatients who suffer from an injury or an illness requiring urgent care. Emergency Department service is characterized by: a) high variability of patient arrivals, depending on time (day, week, year intervals ) and on exceptional events (epidemics, maxiemergencies) occurring, according to extreme randomness; b) different required assistance type according to patient characteristics and to suffered injury or illness; c) hard requirements for quick (sometimes immediate) response, also in case of congestion. An emergency department shall be correctly designed and managed for what concerns: a) structures (major treatment, minor treatment rooms, waiting rooms, short term admission rooms, beds); b) technological resources (specifical instruments); c) human resources (doctors, nurses, engineers and related working rules, turns of duty, etc.) in order to supply a high quality service at minimum cost. Once given the presence of randomness in patient arrival, in patient management (due to priorities and possible preemption) and in services’ duration, an analytical model is hard to build and anyway not suitable, as it is able to provide only mean behaviour results, while a simulation model is able to describe system behaviour in detail, and to give results related both to mean and to extreme conditions. A correct organization and resource dimensioning is very important both in the planning and in the management phase and may be usefully supported by a simulation model to be applied by administrators and operators. As an emergency department is a very complex framework, a model which simulates it requires a large amount of time and an expert software programmer to be built and implemented. In this paper we employ a generalized flexible model built up by us and presented in a previous paper, able to reproduce all common structural and functional characteristics of every actual emergency room only by adjusting functional parameters. This simulation model was adapted to two actual emergency departments requiring reorganization as they evidenced performance problems. By an easy simulation exercise: a) present situations were reproduced and weak organizational aspects of system behaviour analyzed; b) a new dimensioning of employed resources and working rules were suggested and tested by means of parameters setting; c) new dimensioning was evaluated in terms of economical and social costs.