A note on "Bed allocation techniques based on census data"
In: Socio-economic planning sciences: the international journal of public sector decision-making, Band 39, Heft 2, S. 183-192
ISSN: 0038-0121
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In: Socio-economic planning sciences: the international journal of public sector decision-making, Band 39, Heft 2, S. 183-192
ISSN: 0038-0121
In: Socio-economic planning sciences: the international journal of public sector decision-making, Band 33, Heft 3, S. 231-245
ISSN: 0038-0121
In: Decision sciences journal of innovative education, Band 20, Heft 1, S. 5-16
ISSN: 1540-4595
AbstractPopular game shows offer educators the opportunity to develop active‐learning exercises that provide students with a real‐world connection to analytical reasoning and methods. We describe a classroom assignment developed for quantitative business courses based on the Monty Hall Problem (MHP), a probability puzzle with ties to the long‐running television game showLet's Make a Deal. Through a holistic view of the MHP, we provide instructors with various avenues to use the MHP as a comprehensive experiential learning exercise with multiple opportunities for individual and class discussions and exercises. Instructors adopting our multifaceted approach to the MHP will expose students to myriad analytical tools including probability, decision trees, and Monte Carlo simulation as well as to cognitive biases that can affect the decision‐making process. Among the unique contributions of our work is its focus on the commonly held MHP assumptions. Specifically, we challenge students to articulate conditions inherent to the MHP solution and assess their appropriateness in context. By relaxing one or more of those assumptions, and observing differences in solutions, students become attuned to the importance of knowing and assessing conditions that underlie all quantitative decision‐making tools.
In: Decision sciences, Band 37, Heft 1, S. 39-70
ISSN: 1540-5915
ABSTRACTLegislators 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.