This paper presents the application of a mixed integer linear programming model to the choice of an optimal staff for an ambulatory medical care practice. Instead of adding further institutional and financial constraints to earlier models, this paper describes a strategy for the measurement of the key empirical constructs on which such analysis must rest. The analysis illustrates the use of the model for selecting the optimal staff and shows the relationships of this staff to the types of problems presented to the practice and the scale of activity. The effect of scale and patient mix on average cost per encounter are examined and the dual solution is used to determine the relative costs of producing encounters in the various groups. Finally, the allocation of responsibilities for different types of patient problems among the various members of the medical team is presented as part of the optimal solution.
OR professionals in every field of study will find information of interest in this balanced, full-spectrum industry review. Essential reading for practitioners, researchers, educators and students of OR. Computing and decision technology Environment, energy and natural resources Financial services Logistics and supply chain operations Manufacturing operations Optimization Public and military services Simulation Stochastic models Telecommunications Transportation
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