Workflow Analysis in Operating Rooms: A System-Theoretic Approach

Improving workflow efficacy in operating rooms (ORs) is of significant importance for hospital management. Safe delivery of surgical procedures, better utilization of staff and medical resources, as well as enhanced efficiency and satisfactory patient outcome are expected. To achieve this, quick and accurate analysis of surgery workflow becomes a critical enabler. Although extensive studies have been carried out in OR scheduling, efficient methods for detailed workflow analysis in ORs are missing in the current literature. To bridge the gap, a system-theoretic approach is introduced to study surgical workflow in ORs. Specifically, a Markov chain-based analytical model is presented to evaluate the performance of surgical processes. To mitigate the curse of dimensionality, an iterative algorithm is introduced for large surgical centers. Using this model, system properties, such as monotonicities, are investigated. Numerical experiments indicate that such a method can provide efficient analysis with acceptable accuracy. In addition, a case study in a large public hospital illustrates the applicability of the method.
Note to Practitioners
—Operating room is one of the most expensive and critical units in a hospital, and the associated surgical processes are complex and random. Therefore, accurate and efficient analysis of surgery workflow is needed to better plan and schedule surgery activities for improved quality of care and patient outcomes. This paper presents a system-theoretic approach to study OR workflow, which can quickly and effectively evaluate OR performance, such as throughput, length of OR stay, staff and OR utilizations, and investigate the impacts of changes in settings and demands. To avoid state space explosion in Markov chain analysis, an iterative method is presented to significantly reduce computation intensity. Finally, an application in a public hospital illustrates that such a method provides an efficient quantitative tool for OR management.