Resilience in the Surgical Scheduling to Support Adaptive Scheduling System.

Operating Room (OR) managers frequently encounter uncertainties related to real-time scheduling, especially on the day of surgery. It is necessary to enable earlier identification of uncertainties occurring in the perioperative environment. This study aims to propose a framework for resilient surgical scheduling by identifying uncertainty factors affecting the real-time surgical scheduling through a mixed-methods study. We collected the pre- and post-surgical scheduling data for twenty days and a one-day observation data in a top-tier general university hospital in South Korea. Data were compared and analyzed for any changes related to the dimensions of uncertainty. The observations in situ of surgical scheduling were performed to confirm our findings from the quantitative data. Analysis was divided into two phases of fundamental uncertainties categorization (conceptual, technical and personal) and uncertainties leveling for effective decision-making strategies. Pre- and post-surgical scheduling data analysis showed that unconfirmed patient medical conditions and emergency cases are the main causes of frequent same-day surgery schedule changes, with derived factors that affect the scheduling pattern (time of surgery, overtime surgery, surgical procedure changes and surgery duration). The observation revealed how the OR manager controlled the unexpected events to prevent overtime surgeries. In conclusion, integrating resilience approach to identifying uncertainties and managing event changes can minimize potential risks that may compromise the surgical personnel and patients' safety, thereby promoting higher resilience in the current system. Furthermore, this strategy may improve coordination among personnel and increase surgical scheduling efficiency.

Managing uncertainties in the surgical scheduling.

Current surgical scheduling system has difficulties to handle unpredictable events or uncertainties. Source of uncertainties may come from the patient or the surgery itself, where several cases require immediate changes in data, such as when surgery delays or cancellation occurs on the same day. The study aimed to model the uncertainties for managing identified uncertainties during the continuous scheduling, framed by resilience concept to cope with the system fragility. In order to be able to control and adjust any changes which may affect the surgery schedule of the day, we provide alternatives of solution rather than strictly decide the best valued options. We identified dimensions of uncertainties and categorized them based on the resilience concept, computed the impact value of potentially conflicted resources as a result of schedule change. With the model applied, we would provide a list of most acceptable and less vulnerable alternatives for anesthesiologist as a scheduler to build resilience in the surgical scheduling.