Albert Y Huang1,2, Guillaume Joerger3, Remi Salmon4, Brian Dunkin5,6, Vadim Sherman5, Barbara L Bass5, Marc Garbey4,6,3. 1. Department of Surgery, Houston Methodist Hospital, 6550 Fannin St, Suite 1661, Houston, TX, 77030, USA. ayhuang@houstonmethodist.org. 2. Methodist Institute of Technology Innovation and Education, Houston, TX, USA. ayhuang@houstonmethodist.org. 3. LASIE UMR CNRS, Univ., La Rochelle, France. 4. University of Houston, Houston, TX, USA. 5. Department of Surgery, Houston Methodist Hospital, 6550 Fannin St, Suite 1661, Houston, TX, 77030, USA. 6. Methodist Institute of Technology Innovation and Education, Houston, TX, USA.
Abstract
BACKGROUND: Optimization of OR management is a complex problem as each OR has different procedures throughout the day inevitably resulting in scheduling delays, variations in time durations and overall suboptimal performance. There exists a need for a system that automatically tracks procedural progress in real time in the OR. This would allow for efficient monitoring of operating room states and target sources of inefficiency and points of improvement. STUDY DESIGN: We placed three wireless sensors (floor-mounted pressure sensor, ventilator-mounted bellows motion sensor and ambient light detector, and a general room motion detector) in two ORs at our institution and tracked cases 24 h a day for over 4 months. RESULTS: We collected data on 238 total cases (107 laparoscopic cases). A total of 176 turnover times were also captured, and we found that the average turnover time between cases was 35 min while the institutional goal was 30 min. Deeper examination showed that 38 % of laparoscopic cases had some aspect of suboptimal activity with the time between extubation and patient exiting the OR being the biggest contributor (16 %). CONCLUSION: Our automated system allows for robust, wireless real-time OR monitoring as well as data collection and retrospective data analyses. We plan to continue expanding our system and to project the data in real time for all OR personnel to see. At the same time, we plan on adding key pieces of technology such as RFID and other radio-frequency systems to track patients and physicians to further increase efficiency and patient safety.
BACKGROUND: Optimization of OR management is a complex problem as each OR has different procedures throughout the day inevitably resulting in scheduling delays, variations in time durations and overall suboptimal performance. There exists a need for a system that automatically tracks procedural progress in real time in the OR. This would allow for efficient monitoring of operating room states and target sources of inefficiency and points of improvement. STUDY DESIGN: We placed three wireless sensors (floor-mounted pressure sensor, ventilator-mounted bellows motion sensor and ambient light detector, and a general room motion detector) in two ORs at our institution and tracked cases 24 h a day for over 4 months. RESULTS: We collected data on 238 total cases (107 laparoscopic cases). A total of 176 turnover times were also captured, and we found that the average turnover time between cases was 35 min while the institutional goal was 30 min. Deeper examination showed that 38 % of laparoscopic cases had some aspect of suboptimal activity with the time between extubation and patient exiting the OR being the biggest contributor (16 %). CONCLUSION: Our automated system allows for robust, wireless real-time OR monitoring as well as data collection and retrospective data analyses. We plan to continue expanding our system and to project the data in real time for all OR personnel to see. At the same time, we plan on adding key pieces of technology such as RFID and other radio-frequency systems to track patients and physicians to further increase efficiency and patient safety.
Authors: Franklin Dexter; Amr E Abouleish; Richard H Epstein; Charles W Whitten; David A Lubarsky Journal: Anesth Analg Date: 2003-10 Impact factor: 5.108
Authors: James S Harrop; John C Styliaras; Yinn Cher Ooi; Kristen E Radcliff; Alexander R Vaccaro; Chengyuan Wu Journal: J Am Acad Orthop Surg Date: 2012-02 Impact factor: 3.020
Authors: Martin Schuster; Marco Pezzella; Christian Taube; Enno Bialas; Matthias Diemer; Martin Bauer Journal: Dtsch Arztebl Int Date: 2013-04-05 Impact factor: 5.594
Authors: Timothy D Jackson; Jeffrey J Wannares; R Todd Lancaster; David W Rattner; Matthew M Hutter Journal: Surg Endosc Date: 2011-02-07 Impact factor: 4.584
Authors: Kris E Radcliff; Mohammad R Rasouli; Alex Neusner; Christopher K Kepler; Todd J Albert; Jeffrey A Rihn; Alan S Hilibrand; Alexander R Vaccaro Journal: Spine (Phila Pa 1976) Date: 2013-07-01 Impact factor: 3.468
Authors: Albert Y Huang; Guillaume Joerger; Vid Fikfak; Remi Salmon; Brian J Dunkin; Barbara L Bass; Marc Garbey Journal: Surg Endosc Date: 2017-02-24 Impact factor: 4.584