An integrated nurse staffing and scheduling analysis for longer-term nursing staff allocation problems

The efficient and effective management of nursing personnel is of critical importance in a hospital's environment comprising a vast share of the operational costs. The adopted nurse workforce practices and policies highly affect the nurses' working conditions and the provided quality of care. Policy decisions on the staffing level have an impact on the outcome of the scheduling level and vice versa. Isolated reasoning typically leads to suboptimal decisions often resulting in ineffective outcomes of care. In order to overcome these inefficiencies, we propose in this paper a new integrative nurse staffing and shift scheduling approach. We test and assess the benefits of our approach in a reallife environment. Moreover, we examine the impact of several personnel policies on the staffing decision.     

Reconstructing nurse schedules: Computational insights in the problem size parameters

Managing nursing personnel properly is of critical importance as these resources comprise a vast share of the hospital's operational costs. The organisational support and the managerial policy decisions on the scheduling level are important determinants for the nurses' working conditions and the related quality of care. In this paper, we gain insights and understanding in the consequences and outcomes of various personnel re-rostering characteristics and strategies. We explore the boundaries of the time horizon and the nurse staffing size to consider for the nurse re-rostering problem based on computational experiments in a real-life problem environment.     

A comparison of procedures to correct for base-line differences in the analysis of continuous longitudinal data: a case-study

Summary.  The main advantage of longitudinal studies is that they can distinguish changes over time within individuals (longitudinal effects) from differences between subjects at the start of the study (base-line characteristics; cross-sectional effects). Often, especially in observational studies, subjects are very heterogeneous at base-line, and one may want to correct for this, when doing inferences for the longitudinal trends. Three procedures for base-line correction are compared in the context of linear mixed models for continuous longitudinal data. All procedures are illustrated extensively by using data from an experiment which aimed at studying the relationship between the post-operative evolution of the functional status of elderly hip fracture patients and their preoperative neurocognitive status.