Mayo Clinic, Department of Health Sciences Research, Center for the Science of Health Care Delivery, 200 1st Street SW, Rochester, MN, 55905, USA.
Health Care Manag Sci. 2013 Dec;16(4):314-27. doi: 10.1007/s10729-013-9231-5. Epub 2013 Mar 19.
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.
心血管外科患者在重症监护病房(ICU)和加强医疗护理病房(PCU)使用的恢复病床是昂贵的医院资源,需要进行有效的管理。本案例研究报告了开发和使用离散事件模拟模型的情况,该模型用于预测梅奥诊所所需的最低病床需求,以达到高的患者服务水平。除了包含手术增长和新恢复方案的床位预测外,该模型还用于研究平滑手术计划和将长期住院患者从 ICU 转科的影响。该模型预测的床位需求比传统床位规划方法和实践中探索的方案低 30%,所探索的方案可以大大减少所需的床位数量。