Centralized nurse scheduling to simultaneously improve schedule cost and nurse satisfaction

Wright, P. Daniel; Mahar, Stephen

doi:10.1016/j.omega.2012.08.004

Cited by 75 publications

(45 citation statements)

References 32 publications

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“…The study also develops an allocation model for beginning of shift decisions, including additions of unscheduled overtime and cross‐utilization of nurses across departments. Wright and Mahar () develop a model for centralized nurse shift scheduling that considers the preferences and capabilities of individual nurses, and prescheduled overtime is included in conjunction with regular‐time scheduling. They show that centralized scheduling can result in significantly less overtime while lowering costs and improving the desirability of schedules for the nurses.…”

Section: Literature Reviewmentioning

confidence: 99%

Time‐Staged Overtime Staffing for Services with Updated Forecasts and Availabilities

Campbell

2016

Decision Sciences

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This article develops a framework for staffing in a service environment when multiple opportunities exist for prescheduling overtime prior to the start of a shift. Demand forecasts improve as the shift approaches, while the availability of workers to be scheduled for overtime decreases. First, a single‐shift model is developed and used in computational studies to evaluate the benefits of time‐staged overtime staffing, which include slightly lower costs and significant reductions in unscheduled overtime and outside agents. A multishift model is then developed to consider constraints on consecutive hours worked and minimum rest intervals between shifts. A multishift computational study shows how the benefits of time‐staged overtime staffing depend on problem characteristics when interactions between shifts are considered. The article discusses how single‐shift and multishift models relate to each other and alternative ways the models may be used in practice, including decentralized open shift management and centralized overtime scheduling.

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Section: Literature Reviewmentioning

confidence: 99%

Time‐Staged Overtime Staffing for Services with Updated Forecasts and Availabilities

Campbell

2016

Decision Sciences

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“…However, by pooling the demand of clusters or departments it becomes more likely that high demand from one resident will be balanced out by low demand from another (Eppen, 1979;Wallace and Whitt, 2004). The studies by Vanberkel et al (2012) and Wright and Mahar (2013) examines pooling effects on the nursing staff in a hospital setting. The study of Moeke et al (2014) examines scale efficiencies in a nursing home context.…”

Section: Research In Nursing Homesmentioning

confidence: 99%

Task scheduling in long-term care facilities: A client-centered approach

Lieder

Moeke

Koole

et al. 2015

Operations Research for Health Care

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In this study, we analyze a task scheduling problem with small time windows and care workers with different levels of qualification in a nursing home. A set of care tasks has to be assigned to a given number of care workers, so that the total earliness and tardiness from the nursing home residents' preferred time is minimized.To optimally solve this scheduling problem, we formulate a mixed integer program (MIP) and develop a dynamic programming (DP) approach. The numerical analysis shows the reliability of this optimization approach as well as of a heuristic DP approach. A sensitivity analysis with real-world demand data shows the impact of hierarchical qualification levels and large-scale scheduling.

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“…In addition, cross-training in a single department or between departments can be considered (Van den Bergh, 2013), the possibility of overtime can be included (Wright & Mahar, 2013) and, for each worker, primary and secondary skills can be distinguished (de Matta & Peters, 2009;Guerry et al, 2013). In this paper, several straightforward assumptions regarding these options have been adopted: categorical skills, homogeneity of workers regarding learning, one single department, with no overtime considered.…”

Section: Introductionmentioning

confidence: 99%

Calibrating cross-training to meet demand mix variation and employee absence

Olivella

Nembhard

2016

European Journal of Operational Research

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Abstract:We address the problem of determining the cross-training that a work team needs in order to cope with demand mix variation and absences. We consider the case in which all workers can be trained on all tasks, the workforce is a resource that determines the capacity and a complete forecasting of demand is not available. The demand mix variation that the organization wants to be able to cope with is fixed by establishing a maximum time to devote to each product. We contend that this approach is straightforward, has managerial practicality and can be applied to a broad range of practical scenarios. It is required that the demand mix variation be met, even if there are a certain level of absences. To numerically solve the mathematical problem, a constraint-based selection procedure is developed, which we term CODEMI. We provide illustrated examples demonstrating solution quality for the approximation, and we report on an illustrative set of computational cases.

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Centralized nurse scheduling to simultaneously improve schedule cost and nurse satisfaction

Cited by 75 publications

References 32 publications

Time‐Staged Overtime Staffing for Services with Updated Forecasts and Availabilities

Time‐Staged Overtime Staffing for Services with Updated Forecasts and Availabilities

Task scheduling in long-term care facilities: A client-centered approach

Calibrating cross-training to meet demand mix variation and employee absence

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