A Branch and Bound Algorithm for Optimum Allocation of Float Nurses

Abstract

This paper discusses a methodology developed for allocation of float nurses in short-term general hospitals. The severity of need for nursing care on a unit is measured from the perceptions of head nurses of the unit. A multivariate regression model is used to predict head nurses perceptions at the beginning of a shift from certain auditable variables. The multivariate regressions are used as an objective function in a branch and bound allocation model designed to allocate float nurses before the start of a shift. The model is tested in five nursing units of a study hospital, and results are presented.