Recovery bed planning in cardiovascular surgery: a simulation case study

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 nee...

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Bibliographic Details
Published in:Health care management science 2013-12, Vol.16 (4), p.314-327
Main Authors: Marmor, Yariv N., Rohleder, Thomas R., Cook, David J., Huschka, Todd R., Thompson, Jeffrey E.
Format: Article
Language:English
Subjects:
Business and Management
Cardiovascular Surgical Procedures - statistics & numerical data
Case studies
Clinics
Computer Simulation
Costs
Critical care
Econometrics
Financial analysis
Health Administration
Health care management
Health Informatics
Heart surgery
Hospital Bed Capacity - statistics & numerical data
Hospitals
Humans
Intensive care
Intensive Care Units - statistics & numerical data
Management
Models, Statistical
Needs Assessment
Operations Research/Decision Theory
Patient care planning
Patient safety
Planning Techniques
Postoperative period
Quality of service
Recovery (Medical)
Resource allocation
Simulation
Studies
Workforce planning
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Summary: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.
ISSN:1386-9620
1572-9389
DOI:10.1007/s10729-013-9231-5