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Abstract
Staff scheduling in hospital emergency departments is challenging due to the uncertainty involved in the work needed to be performed, the high impact if the work is not performed, and the non-traditional working hours. Also, the desires of the stakeholder on what should be optimized may not be clear. This paper addresses the impacts of preferences in the staffing of emergency department nurses. The research uses data collected from a local hospital on patient flow to model nurse staffing. This model is used in an optimization framework where objective functions and constraints are varied to determine their impact on scheduling. Value models of patient care and wasted funds, as well as four constraints are explored in this research. The research concludes that understanding and representing the stakeholder's preference properly is critical in determining an optimal schedule.
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1.Introduction
Hospital administrations have the difficult task of scheduling workers where uncertainty in the work that needs to be performed exists (Bruin, Rossum, Visser, & Koole, 2007). High impact exists on both patients and the hospital if the work is not performed to a certain set of standards (Van Den Bos et al., 2011), and non-traditional working hours exist (Trinkoff, Le, Geiger-Brown, Lipscomb, & Lang, 2006). In addition, the preferences of the stakeholder must be well understood if a preferred schedule is to be formed. Examples of preferences that are relevant to the health care sector are minimizing costs, maximizing profit, maximizing patient satisfaction, and minimizing employee attrition. These preferences indicate desire for one alternative over another alternative.
To determine a preferred schedule, two things are needed: a preference and a prediction of a future state. This paper leverages patient flow data on Emergency Department (ED) nurse staffing for a local hospital in Northern Alabama to establish a demand prediction model. There are two preferences specified by the local hospital that are examined in this paper. The first preference is to ensure that there are enough nurses scheduled to meet hospital needs. The second preference is to ensure that resources are not being wasted by scheduling nurses who are not needed. While there are many ways to approach these preferences, this paper opts for an optimization and value model approach. Therefore, the...