Simulation Modeling for Planning Bed Capacities
A hospital bed footprint specifies how many inpatient beds each hospital service (e.g. neurology, general internal medicine (GIM), geriatrics, etc.) is allotted on each nursing unit. One of the consequences of an inadequately designed bed footprint is bed spacing. Bed spacing occurs when a patient’s admitting service does not have an appropriate bed available, so the patient is sent to an off-service bed instead.
For example, if a patient in the emergency department is waiting for a bed on the GIM unit and no beds are available, they may be instead assigned a bed on the geriatrics unit. Consequently, attending physicians need to leave their unit to see bed spaced patients, which reduces efficiency and may compromise care. An efficient bed footprint should ensure that bed spacing is minimized and that occupancy levels (the number of occupied beds on each unit) are appropriate and balanced across units.
This project uses historical data and priority rules for bed assignment to predict what the daily number of bed spaced patients per service and the daily number of occupied beds per unit would be after the implementation of a new bed footprint.
Discrete event simulation is being used to model the effect of a hypothetical bed footprint on patient flow in the hospital before implementation in the actual hospital environment. This will allow for data informed decisions regarding the optimal allocation of beds, so that bed spacing is minimized and unit occupancy levels are balanced across units.