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               Models of efficiency in the operating room
               Efficiency models within operating rooms primarily focus on optimizing workflow, enhancing patient care,
               and maximizing resource utilization. Several models have been proposed and implemented to improve
               operational efficiency in surgical settings. These efficiency models aim to streamline operations, enhance
               quality, reduce costs, and ultimately improve patient outcomes in surgical settings.

               Four disciplines of execution
               The 4 Disciplines of Execution (4DX) model is a performance management strategy developed by Sean
               Covey, Chris McChesney, and Jim Huling, designed to assist organizations in achieving their wildly
               important goals (WIGs) amidst the whirlwind of daily operations . This model is structured around four
                                                                       [29]
               key disciplines. First, it emphasizes the identification of clear and compelling WIGs, defining specific
               outcomes that require exceptional focus. Second, it advocates the establishment of lead measures,
               quantifiable predictors of goal achievement, allowing teams to proactively influence results. Third, it
               underscores creating a scoreboard, enabling teams to visually track progress and engage in a consistent
               feedback loop. Finally, the model establishes a cadence of accountability through regular team meetings
               where members commit to actions, review progress, and hold each other accountable for results. The 4DX
               model acts as a systematic approach to drive focus, engagement, and accountability within organizations,
               enhancing their ability to accomplish their most critical objectives in the face of competing priorities. The
               4DX model has been implemented in MABR. Easton et al. demonstrated a significant reduction in operative
               time,  from  828  min  pre-intervention  to  619  min  post-intervention  for  a  bilateral  DIEP  breast
               reconstruction . Length of stay was decreased, and no increase in complications was identified.
                           [30]

               Lean and six sigma
               Taiichi Ohno first described the Lean methodology in his role at Toyota. He described the “seven wastes”,
               later expanded to eight: waiting/idle time, inventory, defects, transportation, motion, overproduction, over-
               processing, and untapped potential. By reducing these wastes, the goal of streamlined production, improved
               quality, and increased efficiency can be achieved. The Lean methodology has been adapted to healthcare,
               including the MABR system [31-33] . Its principles, including value stream mapping and continuous
               improvement, have been applied to identify and rectify inefficiencies in operating room processes.


               Lean methodology aims to eliminate waste within processes, while the Six Sigma methodology is aimed at
               reducing variability in processes and eliminating defects. Lean focuses on speed and efficiency, whereas Six
               Sigma emphasizes quality and precision by reducing variability. The core idea of Six Sigma is to use data
               analysis to pinpoint problems and variability, and then use specific techniques to systematically remove
               these. This is accomplished through the DMAIC (Define, Measure, Analyze, Improve, Control) cycle for
               existing processes, or the DMADV (Define, Measure, Analyze, Design, Verify) for creating new product or
               process designs.

               Over the last twenty years, the two concepts have been combined into a hybrid improvement process called
               “Lean Six Sigma”. By combining the elimination of waste and defects within a given system, Lean Six Sigma
               seeks to streamline surgical processes, improve quality, and minimize variation in outcomes. This model
               employs data-driven decision making, process mapping, and statistical tools to measure, analyze, and
               improve the efficiency of surgical procedures, ultimately leading to reduced costs, shorter cycle times,
               improved patient satisfaction, and superior clinical outcomes in the operating room. This framework has
               also been adopted in MABR by multiple groups. In 2016, Hultman et al. reported their results of pre-, intra-,
               and post-intervention in a group of patients undergoing DIEP flap breast reconstruction, demonstrating a
               significant reduction in operative times (714 to 607 min) and length of stay (6.3 to 5.2 days) . In 2021,
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