title: Recovery bed planning in cardiovascular surgery: a simulation case study.
abstract: Recovery beds for cardiovascular surgical patients in the intensive care unit (ICU) and progressive care unit (PCU) are costly hospital resources that require effective management. This case study reports on the development and use of a discrete-event simulation model used to predict minimum bed needs to achieve the high patient service level demanded at Mayo Clinic. In addition to bed predictions that incorporate surgery growth and new recovery protocols, the model was used to explore the effects of smoothing surgery schedules and transferring long-stay patients from the ICU. The model projected bed needs that were 30 % lower than the traditional bed-planning approach and the options explored by the practice could substantially reduce the number of beds required.
authors.affiliation: Mayo Clinic, Department of Health Sciences Research, Center for the Science of Health Care Delivery, 200 1st Street SW, Rochester, MN, 55905, USA.
authors.forename: Yariv N
authors.initials: YN
authors.lastname: Marmor
authors.forename: Thomas R
authors.initials: TR
authors.lastname: Rohleder
authors.forename: David J
authors.initials: DJ
authors.lastname: Cook
authors.forename: Todd R
authors.initials: TR
authors.lastname: Huschka
authors.forename: Jeffrey E
authors.initials: JE
authors.lastname: Thompson
mesh_terms: D013504:Cardiovascular Surgical Procedures / Q000706:statistics & numerical data*; D003198:Computer Simulation; D006742:Hospital Bed Capacity / Q000706:statistics & numerical data*; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D015233:Models, Statistical; D020380:Needs Assessment; D010934:Planning Techniques