Simulation modeling for hospital bed planning

Abstract

A computer simulation model was developed to address the problem of allocating beds to hospital services, by bed type and sex. The model, written in Simscript II.5, was designed to per mit experimentation with and evaluation of bed usage policies and admissions rules as well as allocation plans. Using the model, hospital beds at the Mount Sinai Medical Center, New York City, were reallocated. Incorporated in this reallocation was the creation of a new service. Also developed was a revised elective admissions reservation board. An altered view of measures of performance was another outcome. Discussion in this paper will center around the allocation prob lem, the simulation model, the performance measures, the hos pital configurations, the experiments and the results obtained.

Integrated decision making in healthcare : an operations research and management science perspective

“…Each care unit has its designated staff, equipment and beds (in one or more wards). The objective is to guarantee care from appropriately skilled nurses and required equipment to patients with specific diagnoses, while making efficient use of scarce resources [26,156,157,206,243,251,439,499]. First, the desirability of opening shared higher-level care units like Intensive Care Units (ICU) or Medium Care Units (MCU) should be considered [480].…”

“…Methods: computer simulation [156,157,206,243,259,439], heuristics [26,309,482], mathematical programming [376], queueing theory [217,251,355,359,360,480,522].…”

“…First, patients might have to be transferred to another hospital in case of an emergency [108,292,347,524]. Second, patients may (temporarily) be placed in less appropriate units, so-called misplacements [112,156,157,217,242,247,524]. Third, backlogs may be created in emergency rooms or surgical recovery units [104,206,217,375,376].…”

“…Methods: computer simulation [7,19,104,108,112,156,157,206,221,222,238,241,242,243,244,259,292,295,347,371,372,373,375,415,439,478,497,517,519,523,524], heuristics [309], Markov processes [7,68,172,192,199,245,246,247,335], mathematical programming [127,202,241,318,327,375,376], queueing theory [11,29,…”

“…For many inpatient care services the authority on admission control is limited due to the high dependency on the operating room schedule (see surgical care services). By adjusting the surgical schedule, extremely busy and slack periods can be avoided [4,26,152,156,170,210,217,238,469,492,493,501,502,524] and cancellation of elective surgeries can be avoided [291]. In practice, the operating room planning is generally done under the assumption that a free bed is available for postoperative care [293], which may result in surgery cancellations.…”