Impact of surgical sequencing on post anesthesia care unit staffing

被引:91
作者
Marcon E. [1 ,2 ,3 ]
Dexter F. [4 ,5 ]
机构
[1] Laboratory of Signal and Manufacturing Systems Analysis, Jean Monnet University of Saint Etienne
[2] Department Manufacturing System Management and Maintenance, Jean Monnet University of Saint Etienne
[3] LASPI - IUT de Roanne, City, Roanne, 42334 Cedex
[4] Division of Management Consulting, University of Iowa, Iowa City, IA
[5] Departments of Anesthesia and Health Management and Policy, University of Iowa, Iowa City, IA
关键词
Economics; Operating Room and PACU; Optimization; Schedule; Staffing;
D O I
10.1007/s10729-006-6282-x
中图分类号
学科分类号
摘要
This paper analyzes the impact of sequencing rules on the phase I post anesthesia care unit (PACU) staffing and over-utilized operating room (OR) time resulting from delays in PACU admission. The sequencing rules are applied to each surgeon's list of cases independently. Discrete event simulation shows the importance of having a sufficient number of PACU nurses. Sequencing rules have a large impact on the maximum number of patients receiving care in the PACU (i.e., peak of activity). Seven sequencing rules are tested, over a wide range of scenarios. The largest effect of sequencing was on the percentage of days with at least one delay in PACU admission. The best rules are those that smooth the flow of patients entering in the PACU (HIHD (Half Increase in OR time and Half Decrease in OR time) and MIX (MIX OR time)). We advise against using the LCF (Longest Cases First) and equivalent sequencing methods. They generate more over-utilized OR time, require more PACU nurses during the workday, and result in more days with at least one delay in PACU admission. © Springer Science + Business Media, Inc. 2006.
引用
收藏
页码:87 / 98
页数:11
相关论文
共 33 条
[1]  
Dexter F., Traub R.D., Sequencing cases in the operating room: Predicting whether one surgical case will last longer than another, Anesthesia and Analgesia, 90, pp. 975-979, (2000)
[2]  
Macario A., Dexter F., Estimating the duration of a case when the surgeon has not recently scheduled the procedure at the surgical suite, Anesthesia and Analgesia, 89, pp. 1241-1245, (1999)
[3]  
May J.H., Strum D.P., Vargas L.G., Fitting the lognormal distribution to surgical procedure times, Decision Sciences, 31, pp. 129-148, (2000)
[4]  
Zhou J., Dexter F., Macario A., Lubarsky D.A., Relying solely on historical surgical times to estimate accurately future surgical times is unlikely to reduce the average length of time cases finish late, Journal of Clinical Anesthesiology, 11, pp. 601-605, (1999)
[5]  
Blake J.T., Dexter F., Donald J., Operating room managers' use of integer programming for assigning block time to surgical groups: A case study, Anesthesia and Analgesia, 94, pp. 143-148, (2002)
[6]  
Blake J.T., Donald J., Mount Sinai hospital uses integer programming to allocate operating room time, Interfaces, 32, pp. 66-73, (2002)
[7]  
Dexter F., Traub R.D., Macario A., How to release allocated operating room time to increase efficiency: Predicting which surgical service will have the most underutilized operating room time, Anesthesia and Analgesia, 96, pp. 507-512, (2003)
[8]  
Marcon E., Kharraja S., Smolski N., Luquet B., Viale J.P., Determining the number of beds in postanesthesia care unit: A computer simulation flow approach, Anesthesia and Analgesia, 96, pp. 1415-1423, (2003)
[9]  
Strum D.P., Vargas L.G., May J.H., Surgical subspeciality block utilization and capacity planning: A minimal cost analysis model, Anesthesiology, 90, pp. 1176-1185, (1999)
[10]  
Dexter F., Macario A., Traub R.D., Hopwood M., Kubarsky D.A., An operating room scheduling strategy to maximize the use of operating room block time: Computer simulation of patient scheduling and survey of patients' preferences for surgical waiting time, Anesthesia and Analgesia, 89, pp. 7-20, (1999)