Abstract
Patients flow in outpatient surgical unit is a major issue with regards to resource utilization, overall case load and patient satisfaction. An electronic Radio Frequency Identification Device (RFID) was used to document the overall time spent by the patients between their admission and discharge from the unit. The objective of this study was to evaluate how a RFID-based data collection system could provide an accurate prediction of the actual time for the patient to be discharged from the ambulatory surgical unit after surgery. This is an observational prospective evaluation carried out in an academic ambulatory surgery center (ASC). Data on length of stay at each step of the patient care, from admission to discharge, were recorded by a RFID device and analyzed according to the type of surgical procedure, the surgeon and the anesthetic technique. Based on these initial data (n = 1520), patients were scheduled in a sequential manner according to the expected duration of the previous case. The primary endpoint was the difference between actual and predicted time of discharge from the unit. A total of 414 consecutive patients were prospectively evaluated. One hundred seventy four patients (42 %) were discharged at the predicted time ± 30 min. Only 24 % were discharged behind predicted schedule. Using an automatic record of patient’s length of stay would allow an accurate prediction of the discharge time according to the type of surgery, the surgeon and the anesthetic procedure.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Casey JT, Brinton TS, Gonzalez CM. Utilization of lean management principles in the ambulatory clinic setting. Nat Clin Pract Urol 2009;6:146–53.
Tanaka M, Lee J, Ikai H, Imanaka Y. Development of efficiency indicators of operating room management for multi-institutional comparisons. J Eval Clin Pract 2011;19:335–41.
Cendan JC, Good M. Interdisciplinary work flow assessment and redesign decreases operating room turnover time and allows for additional caseload. Arch Surg 2006;141:65–9.
Heslin MJ, Doster BE, Daily SL et al. Durable improvements in efficiency, safety, and satisfaction in the operating room. J Am Coll Surg 2008;206:1083–9.
Marjamaa RA, Torkki PM, Torkki MI, Kirvela OA. Time accuracy of a radio frequency identification patient tracking system for recording operating room timestamps. Anesth Analg 2006;102:1183–6.
Park KW, Smaltz D, McFadden D, Souba W. The operating room dashboard. J Surg Res 2010;164:294–300.
Castro L, Lefebvre E, Lefebvre LA. Adding intelligence to mobile asset management in hospitals: the true value of RFID. J Med Syst 2013;37:9963.
Coustasse A, Tomblin S, Slack C. Impact of radio-frequency identification (RFID) technologies on the hospital supply chain: a literature review. Perspect Health Inf Manag 2013;10:1d.
Southard PB, Chandra C, Kumar S. RFID in healthcare: a Six Sigma DMAIC and simulation case study. Int J Health Care Qual Assur 2012;25:291–321.
Yao W, Chu CH, Li Z. The adoption and implementation of RFID technologies in healthcare: a literature review. J Med Syst 2012;36:3507–25.
Marjamaa R, Vakkuri A, Kirvela O. Operating room management: why, how and by whom? Acta Anaesthesiol Scand 2008;52:596–600.
Dempsey C, Rudolph M. Questions managers ask on patient flow. OR Manager 2005;21:20–1.
Park KW, Dickerson C. Can efficient supply management in the operating room save millions? Curr Opin Anaesthesiol 2009;22:242–8.
Strum DP, Sampson AR, May JH, Vargas LG. Surgeon and type of anesthesia predict variability in surgical procedure times. Anesthesiology 2000;92:1454–66.
Dexter F, Dexter EU, Ledolter J. Influence of procedure classification on process variability and parameter uncertainty of surgical case durations. Anesth Analg 2010;110:1155–63.
Dexter F, Ledolter J. Bayesian prediction bounds and comparisons of operating room times even for procedures with few or no historic data. Anesthesiology 2005;103:1259–167.
Harders M, Malangoni MA, Weight S, Sidhu T. Improving operating room efficiency through process redesign. Surgery 2006;140:509–14.
Liu SS, Strodtbeck WM, Richman JM, Wu CL. A comparison of regional versus general anesthesia for ambulatory anesthesia: a meta-analysis of randomized controlled trials. Anesth Analg 2005;101:1634–42.
Torkki PM, Marjamaa RA, Torkki MI et al. Use of anesthesia induction rooms can increase the number of urgent orthopedic cases completed within 7 hours. Anesthesiology 2005;103:401–5.
Stepaniak PS, Vrijland WW, de Quelerij M et al. Working with a fixed operating room team on consecutive similar cases and the effect on case duration and turnover time. Arch Surg 2010;145:1165–70.
Lai HM, Lin IC, Tseng LT. High-level managers’ considerations for RFID adoption in hospitals: an empirical study in Taiwan. J Med Syst 2014;38:3.
Acknowledgments
The authors wish to thank Bruce D. Butler, Ph.D., Vice President Research and Technology. University of Texas Health Science Center at Houston, for assistance in the English redaction of this manuscript.
Conflict of interest
The authors don’t have any conflict of interest in relation with the topic. Radio frequency identification device was bought to Kheops Tech Corp™ with institutional funds.
Author information
Authors and Affiliations
Corresponding author
Additional information
This work was presented as an abstract at the French National Society of Anesthesiology meeting in Sept 2013.
This article is part of the Topical Collection on Systems-Level Quality Improvement
Rights and permissions
About this article
Cite this article
Marchand-Maillet, F., Debes, C., Garnier, F. et al. Accuracy of Patient’s Turnover Time Prediction Using RFID Technology in an Academic Ambulatory Surgery Center. J Med Syst 39, 12 (2015). https://doi.org/10.1007/s10916-015-0192-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10916-015-0192-8