These peak time–based bed needs are well known in hospitals, but their occurrence appears to be largely unpredictable. During these times, everything goes wrong: ambulances are diverted, patients are boarded in emergency departments, patients are often prematurely discharged from the ICU to make room for more ill patients or elective surgical cases, nurses are overloaded and stressed,5 and patient discharges take place prematurely, resulting in patient readmissions.7 On days like these, hospital clinicians and managers face an unlikable dilemma: to admit a patient to a nonpreferred unit or to board the patient in the emergency department or the postanesthesia care unit until a bed in the preferred unit becomes available. During these times, proper patient placement is an exercise in wishful thinking and the definition of a preferred bed becomes “the one that is available.” Because of these artificial peaks in scheduled admissions, US hospitals ration ICU beds, monitored beds, and even regular-floor beds every day. Surprisingly, this situation is much easier in managing natural (unpredictable) fluctuations in the demand. In this case, queuing theory, widely used in other industries although rarely used in health care,5 ,8 is helpful, providing an accurate way of matching random demand to fixed capacity.9