Nurse workforce scheduling in the emergency department: A sequential decision support system considering multiple objectives.

Abstract

We propose a nurse scheduling framework based on a set of performance measures that are aligned with multiple outcome measures. A case study for the emergency department is presented. A total of 142,564 emergency department attendances over 1year were included in this study. Operational requirements, constraints and historical workload data were translated into a mixed-integer sequential goal programming model, which considers the following outcome measures: (1) nurse-patient ratios; (2) number of favourable/unfavourable shifts; and (3) dispersion of rest days. Computational studies compared the performance of the mixed-integer sequential goal programming results with manually generated historical nurse schedules. The maximum nurse-patient ratio deviation against the target was approximately 10% compared to 47% generated by the historical rosters (a 10% deviation translates to approximately two nurses). An on-line decision support system, which integrates shift preferences, staff databases and a workload forecasting module, was also developed. A decision support system based on the mixed-integer sequential goal programming modelling framework was proposed. The application of the model in a case study for an emergency department demonstrated improvements over existing manual scheduling methods. This study demonstrates a mathematical, programming-based decision support system, which allows for managerial priorities and nurse preferences to be jointly considered in the automatic generation of nurse rosters.