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.
Original language | English (US) |
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Pages (from-to) | 314-327 |
Number of pages | 14 |
Journal | Health Care Management Science |
Volume | 16 |
Issue number | 4 |
DOIs | |
State | Published - Dec 2013 |
Keywords
- Case study
- Hospital bed planning
- Intensive care unit
- Simulation
ASJC Scopus subject areas
- Medicine (miscellaneous)
- Health Professions(all)