Integrated staffing and scheduling of cross-trained float nurses

Health care staff are becoming a scarce resource in the coming years, stressing the need for efficient use of nursing staff. In this paper, we study the optimal sizing of nursing pools. In contrast to traditional unit nurses, cross-trained nurses have the competencies to cover multiple units and can be assigned to units that require additional staffing on short notice. With a pool of cross-trained nurses, clinics can cover demand with staff working regular hours rather than summoning unit nurses for overtime work or hiring external nurses. The main contribution of the paper is a two-stage stochastic optimization model for sizing pools of cross-trained nurses in a multi-unit setting. Based on a stochastic demand for additional nursing staff in each unit on each workday and shift, the model minimizes the total costs of covering the demand. In contrast to the existing literature, we integrate the staffing and shift scheduling decisions in the model and argue that the scheduling decisions should not be omitted when sizing pools. Furthermore, we evaluate different cross-training policies in a theoretical setting and find that chained cross-training performs almost as well as complete flexibility. Finally, we conduct a case study based on the Clinic of Child and Adolescence Care at St. Olav’s Hospital, Norway, where we apply the model to dimension a pool based on historical demand data.