In this thesis the applicability of a hospital patient flow model is used in addressing hospital resource allocation problems. Three separate but interrelated models are presented. First, the hospital patient flow model is discussed. The main feature of the hospital patient flow model is the matrix of technical coefficients, which gives the probability of patient transfers throughout the hospital. Given the hospital system's daily patient input, the model provides the patient demands upon the different hospital services.

Results from the patient flow model are used in the development of a staff allocation model. The staffing model involves the minimization of a weighted quadratic penalty function. The weighting factors are based on the proportion of patients in each of three carelevels in the wards. The weights are also dependent upon whether overstaffing or understaffing is the situation. Constraints to the model include a desirable mix and number of the available nursing staff. Solution of the allocation model is obtained by using SUMT with a pattern search.

A third model concerned with predicting hospital revenues is presented. Again, results from the hospital patient flow model are used to present estimates of the expected values and variance of a hospital's revenue.

To illustrate the use of the models, results from a two-week study period of the Montgomery County Hospital are presented and discussed.