Abstract
Optimizing surgical capacity while maintaining high-quality patient care is an ongoing challenge in the operating room, particularly for complex procedures requiring significant resources such as robotic hysterectomy.
Lean methodology is a systematic method to identify and eliminate waste in a process without sacrificing productivity. 1 Waste is considered any step in a process that does not increase value for the customer or patient. Ideally, as waste is eliminated, quality improves while costs are reduced.2,3 The Lean toolkit includes various strategies to minimize waste and ensure continuous quality improvement. Process mapping is a quality improvement (QI) strategy that can identify common barriers to surgical process efficiency and quality of care by dividing a process into its individual components and analyzing each step separately. 1
The aim of the study was to utilize QI methodology to design an ideal state intraoperative pathway for robotic hysterectomy in order to improve surgical efficiency and minimize case cancellations.
A current state process map for robotic hysterectomy was developed with input from the intraoperative care team, which consisted of gynecologists, anesthesiologists, and nursing staff. This pathway represented the current flow of process steps during robotic hysterectomy for all 3 care teams. Surgical care team members were then invited to a meeting during which the process steps were discussed and evaluated, and suggestions for improvements were identified. Various QI/Lean methodologies were utilized for this evaluation including affinity diagrams with multi-voting, parallel processing strategies, and checklist development. Following the initial exercise, the group’s suggestions were consolidated and the final output consisted of the design of a future state/ideal state process map incorporating the proposed strategies for improved efficiency for each of the multidisciplinary teams.
Data regarding mean robotic hysterectomy case time and second case cancellation rate were collected after introduction of the ideal state process map. These data were compared to a retrospective control group from the 12 months prior to the process mapping exercise. In the 6 months following introduction of the ideal state process map, mean surgical case time for robotic hysterectomy decreased by 28 minutes (11%) from 241 minutes to 213 minutes, and second case cancellation rate decreased by 70%. Mean case time, case cancellation rates, and the acceptability of the proposed interventions will be analyzed in a recurring fashion as part of a Plan-Do-Study-Act cycle.
Creation and implementation of an ideal state process map was successful in decreasing the mean case time for robotic hysterectomy and minimizing second case cancellations. A multidisciplinary approach to improving operating room efficiency allowed for sharing of responsibility and improved communication between team members. Engagement of all stakeholders is fundamental to ensuring accurate analysis of current process flow and successful deployment of QI strategies. This process mapping exercise can easily be applied to other surgical procedures and expanded for use in surgical teaching and education.