Lourdes Hospital uses a centralized system to schedule appointments by phone for outpatients, inpatients, and other ambulatory services requested by physicians, their staff, hospital personnel, and patients. Customer surveys and an increase in customer complaints revealed lengthy delays in answering telephone calls. We used a queuing model to find the optimal staffing levels to handle the variation in call arrivals within a day. The problem was solved by just rearranging the work shifts, without adding any staff. We also provide an easy-to-reference generalized queuing table to aid others in deciding staffing levels where M/M/c approximation is appropriate.

A probabilistic risk assessment method is described in this paper for the analysis of expected risk to life. The method involves stochastic, as well as deterministic, modelling of building occupant evacuation process and the attainment of untenable conditions due to fires in buildings. Both the number of occupants leaving a building at a given time and the time to untenable conditions are treated as random variables. A general expression for calculating the expected number of death is given. With the postulated Poisson distribution for the number of occupants leaving a building and uniform distribution for the time to untenability, a simple expression for the calculation of the expected number of deaths is obtained. An example is given to illustrate the application of the method.

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