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 Anesthesia

Volumn 11, Issue 7, 1999, Pages 601-605

  Zhou, Jinshi ^a   Dexter, Franklin ^a   MacArio, Alex ^a   Lubarsky, David A ^a  

^a UNIVERSITY OF IOWA   (United States)

Author keywords

Monte Carlo simulation; Operating room: economics of, management of; Random effect; Variance component

Indexed keywords

ARTICLE; ECONOMIC ASPECT; HISTORY; HOSPITAL ORGANIZATION; INFORMATION PROCESSING; INFORMATION SYSTEM; PRIORITY JOURNAL; PROGNOSIS; STATISTICAL MODEL; SURGICAL WARD; TIME MANAGEMENT;

AMBULATORY SURGICAL PROCEDURES; APPOINTMENTS AND SCHEDULES; COMPUTER SIMULATION; EFFICIENCY, ORGANIZATIONAL; FORECASTING; HUMANS; MODELS, STATISTICAL; OPERATING ROOM INFORMATION SYSTEMS; OPERATING ROOMS; RETROSPECTIVE STUDIES; SURGICAL PROCEDURES, OPERATIVE; SURGICENTERS; TIME FACTORS;

EID: 0032747306     PISSN: 09528180     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0952-8180(99)00110-5     Document Type: Article

References (12)

1. Richins S., Holmes M. Waiting for satisfaction. J Healthcare Manage. 43:1998;281-285.
2. Shukla R.K., Ketcham J.S., Ozcan Y.A. Comparison of subjective versus data base approaches for improving efficiency of operating room scheduling. Health Serv Manage Res. 3:1990;74-81.
3. Wright I.H., Kooperberg C., Bonar B.A., Bashein G. Statistical modeling to predict elective surgery time. Anesthesiology. 85:1996;1235-1245.
4. Opit L.J., Collins R.E.C., Campbell G. Use of operating theatres the effects of case-mix and training in general surgery . Ann R Coll Surg Engl. 73:1991;389-393.
5. Searle S.R., Casella G., McCulloch C.E. Variance Components. 1992;John Wiley & Sons, New York.
6. Law AM, Kelton WD: Simulation Modeling & Analysis, 2nd ed. New York: McGraw-Hill, Inc., 1991.
7. Dexter F., Traub R.D., Qian F. Comparison of statistical methods to predict the time to complete a series of surgical cases. J Clin Monit Comput. 15:1999;45-51.
8. Solovy A. Benchmarking guide 99. Hosp Health Network. 73:1999;49-62.
9. Strum DP, May JH, Vargas LG: Surgical procedure times are well modeled by the log-normal distribution [Abstract]. Anesth Analg 1998;82:S47.
10. Wortmann K.D., Weeks T. Successful preference list building. Surg Serv Manage. 4:1998;20-26.
11. Hancock W.M., Walter P.F., More R.A., Glick N.D. Operating room scheduling data base analysis for scheduling. J Med Syst. 12:1988;397-409.
12. Zhou J., Dexter F. Method to assist in the scheduling of add-on surgical cases - upper prediction bounds for surgical case durations based on the log normal distribution. Anesthesiology. 89:1998;1228-1232.