Planning models for skills-sensitive surgical nurse staffing: a case study at a large academic medical center

Surgical nurses are essential resources in the surgery delivery system. However, staffing decisions present a challenge due to the stochastic nature of surgical demand, nurse availability, skill requirements, and hospital or union regulations. This research focuses on a case study based on collaboration with a large academic hospital. We present planning level optimization models to group surgical services into service teams with the goal of achieving fairness in nurse training time, overnight surgical volume, and balance size across teams. Once teams are created, we further assign shifts to services and teams, ensuring that a sufficient number of nurses are available for the demand. We present results that provide insight into optimal surgical nurse staff planning decisions, and show that the newly designed teams are more balanced with respect to the performance metrics, and at the same time lead to improved coverage of surgical demand.