Bottleneck analysis to reduce surgical flow disruptions: Theory and application

The work flow of surgical operations in emergency department and operating rooms can be interrupted due to various disruptions. Reducing such disruptions is of significant importance to ensure successful operations. In this paper, we introduce a continuous-time Markov chain model to analyze the disruptions and their impacts. Analytical formulas have been derived to evaluate the probabilities of normal operations and disruptions. A continuous improvement method has been developed to identify the disruption that impedes surgical operation in the strongest manner. Such a disruption is referred to as the bottleneck disruption. Specifically, the bottleneck disruption can be further categorized with respect to interruption time (BN-t) and frequency (BN-f), so that reducing the interruption time and frequency of the bottleneck, respectively, can lead to the largest improvement in normal operation. An application of the method at an emergency department of a large academic medical center is presented to illustrate the effectiveness of the model and the improvement approach. Note to Practitioners - Reducing the work flow disruptions on surgery in emergency care and operating rooms is of significant importance. Although many efforts have been devoted to observing and categorizing various disruption types, frequencies, and durations, how to identify the most critical disruptions which are impeding the normal operations in the strongestmanner has not been studied yet. In this paper, such disruptions are referred to as the bottleneck disruptions, whose reduction can lead to the largest improvement in ensuring normal status in surgical operations. However, the bottleneck disruption is a result of interactions among all factors in the system and may not be the one that has the longest disruption time or the highest frequency. To identify the bottleneck disruptions, a continuous-timeMarkov chain model has been developed to analyze the work flow. Using the observation data of disruptions collected in emergency care surgery, such as each disruption's time percentage, duration, and its resulting interruption time, etc., simple indicators have been derived to identify the bottleneck disruptions without complicated calculations of system performance and its sensitivities (i.e., partial derivatives). To illustrate the applicability of this study, such a model and indicators have been applied at an emergency department of a large academic medical center. It is discovered that the disruptions due to coordination problem and equipment failure are the system bottlenecks with respect to disruption time and frequency, respectively. In addition, such disruptions are not necessarily the disruption with the longest duration or the highest occurrence, respectively. © 2014 IEEE.