DIMENSIONING THE PARK OF MECHANICAL VENTILATORS ON AN INTENSIVE CARE UNIT OF A HOSPITAL

It is described how the common problem of dimensioning (or resizing) a randomly requested life-support equipment can be solved, resorting not to the classic analytical methods proposed by the theory of waiting lines in Operational Research, which requires the acceptance of some simplifying assumptions, but rather to the Monte Carlo simulation technique, which allows greater flexibility in the construction of a sufficiently representative model of reality. The method is applied to an Intensive Care Unit (ICU) of a Cardiology Department of a Hospital in Lisbon, in which an increase of the number of pulmonary ventilators is believed to be necessary to meet the influx of patients. The methodology for constructing a representative model of this reality in EXCEL (R) is described. This model can be updated with new data at any time and provides the expected values of various performance indicators (expected occupancy rates, average and maximum waiting times, average and maximum number of waiting patients), thus providing a suitable support tool for decision making. By keeping the pertinent set of variables updated in the model, decision makers may find the most adequate solution at any time, in the long run of the service. However, the use of the Monte-Carlo simulation technique is very limited, due to the lack of its dissemination and also to the weak dominance of the underlying and necessary statistical background of potential users to discriminate between inputs and interpret the outputs of a simulation model. Aiming to contribute to the increasing dissemination of simulation techniques, as a tool for describing complex problems and for decision support, we present this communication, describing synthetically, the steps taken for the construction of a sufficiently representative model of a system composed by mechanical ventilators in the above mentioned ICU.