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To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1540-5915.2010.00269.x Byline: P. Daniel Wright (1[dagger]), Kurt M. Bretthauer (2) Keywords: Coordinated Decision Making; Cross-training; Flexible Workforce Capacity; Health Care Applications; Nursing Shortage Abstract: ABSTRACT In this article, we present strategies to help combat the U.S. nursing shortage. Key considerations include providing an attractive work schedule and work environment-critical issues for retaining existing nurses and attracting new nurses to the profession-while at the same time using the set of available nurses as effectively as possible. Based on these ideas, we develop a model that takes advantage of coordinated decision making when managing a flexible workforce. The model coordinates scheduling, schedule adjustment, and agency nurse decisions across various nurse labor pools, each of differing flexibility levels, capabilities, and costs, allowing a much more desirable schedule to be constructed. Our primary findings regarding coordinated decision making and how it can be used to help address the nursing shortage include (i) labor costs can be reduced substantially because, without coordination, labor costs on average are 16.3% higher based on an actual hospital setting, leading to the availability of additional funds for retaining and attracting nurses, (ii) simultaneous to this reduction in costs, more attractive schedules can be provided to the nurses in terms of less overtime and fewer undesirable shifts, and (iii) the use of agency nurses can help avoid overtime for permanent staff with only a 0.7% increase in staffing costs. In addition, we estimate the cost of the shortage for a typical U.S. hospital from a labor cost perspective and show how that cost can be reduced when managers coordinate. Author Affiliation: (1)Department of Management and Operations, Villanova University, Villanova, PA 19085, e-mail:daniel.wright@villanova.edu (2)Department of Operations and Decision Technologies, Indiana University, Bloomington, IN 47405, e-mail:kbrettha@indiana.edu Article History: [Received: October 2008. Accepted: February 2010.] Article note: ([dagger]) Corresponding author.

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1540-5414.2006.00109.x Byline: P. Daniel Wright (1[dagger]), Kurt M. Bretthauer (2), Murray J. Cote (3) Keywords: Health Care Policy; Labor and Staff Planning; Mathematical Programming/Optimization; Nurse Scheduling; and Planning and Scheduling Abstract: ABSTRACT Legislators at the state and national levels are addressing renewed concerns over the adequacy of hospital nurse staffing to provide quality care and ensure patient safety. At the same time, the well-known nursing shortage remains an ongoing problem. To address these issues, we reexamine the nurse scheduling problem and consider how recent health care legislation impacts nursing workforce management decisions. Specifically, we develop a scheduling model and perform computational experiments to evaluate how mandatory nurse-to-patient ratios and other policies impact schedule cost and schedule desirability (from the nurses' perspective). Our primary findings include the following: (i) nurse wage costs can be highly nonlinear with respect to changes in mandatory nurse-to-patient ratios of the type being considered by legislators; (ii) the number of undesirable shifts can be substantially reduced without incurring additional wage cost; (iii) more desirable scheduling policies, such as assigning fewer weekends to each nurse, have only a small impact on wage cost; and (iv) complex policy statements involving both single-period and multiperiod service levels can sometimes be relaxed while still obtaining good schedules that satisfy the nurse-to-patient ratio requirements. The findings in this article suggest that new directions for future nurse scheduling models, as it is likely that nurse-to-patient ratios and nursing shortages will remain a challenge for health care organizations for some time. Author Affiliation: (1)Department of Decision and Information Technologies, Villanova University, Villanova, PA 19085, e-mail:daniel.wright@villanova.edu (2)Department of Operations and Decision Technologies, Indiana University, Bloomington, IN 47405, e-mail:kbrettha@indiana.edu (3)Department of Health Services Research, Management and Policy, University of Florida, Gainesville, FL 32610, e-mail:mjcote@phhp.ufl.edu Article History: [Received: September 2005. Accepted: January 2006.] Article note: ([dagger]) Corresponding author.

An optimization/queueing network model was created to effectively plan resource requirements in health care organizations. The model, which was implemented in a blood bank and in a health maintenance organization, was able to reduce capacity expenditures while regulating customer service through imposition of performance constraints. It was also able to illustrate the stochastic behavior of health care systems and to assess customer service levels contained in the optimization framework.

A general model for multi-item production and inventory management problems that include a resource limitation is introduced. The model's decision variables normally represent cycle times, production batch sizes, number of production runs or order quantities per item. Its objective function includes reciprocal, linear, and constant terms which often arise from setup costs, inventory holding costs and purchase costs.