Nursing care is arguably the single biggest factor in both the cost of hospital care and patient satisfaction. Inadequate inpatient nursing levels have also been cited as a significant factor in medical errors and emergency room overcrowding. Yet, there is widespread dissatisfaction with the current methods of determining nurse staffing levels, including the most common one of using minimum nurse-to-patient ratios. In this paper, we represent the nursing system as a variable finite-source queuing model. We show that though the exact model requires a four-dimensional state space, an approximating assumption results in a reliable, tractable, easily parameterized two-dimensional model. We use this model to show how unit size, nursing intensity, occupancy levels and unit length-of-stay each affect the impact of nursing levels on performance and thus how inflexible nurse-to-patient ratios can lead to either understaffing or overstaffing. In addition, we develop a very accurate one-dimensional heuristic which can be more readily implemented and which can be extended to incorporate high priority nursing jobs which require an immediate response to insure patient safety.
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Yankovic, Natalia, and Linda Green. "Identifying Good Nursing Levels: A Queuing Approach." Operations Research 59, no. 4 (July 2011): 942-955.
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