SEMINAR:Optimizing Surveillance Testing Protocols for Hospital-Acquired.

Guest: Esma Akgün

Title: Optimizing Surveillance Testing Protocols for Hospital-Acquired Infections: Case of MRSA

Date/Time: February 18, 2025 13:40 Online(Zoom),

Location: Online(Zoom)

Join Zoom Meeting: https://sabanciuniv.zoom.us/j/95614106094?pwd=d09zZHd3c3dReW8zcEFncEhZTHBXQT09

Meeting ID: 956 1410 6094

Passcode: susu2020

Abstract:Roommates of nosocomial methicillin-resistant Staphylococcus aureus (MRSA) cases have a high risk of MRSA acquisition. Guidelines recommend that these individuals be isolated and undergo surveillance testing; however, the optimal surveillance testing and isolation strategies are unknown. We develop a Markov decision process model to optimize the testing decisions for the contacts of index MRSA cases in hospitals to minimize the loss of quality-adjusted life years and the number of MRSA colonizations. We solve the model optimally using clinical data from a local hospital and literature, and conduct sensitivity analyses on key parameters, including disutility values and disease parameters, such as prevalence and transmission probability. We computationally analyze the structure of the optimal testing decisions, which recommend varying both the frequency and timing of tests based on initial test results and room configurations. Although they have complex structures and may be hard to implement, the optimal testing decisions offer valuable insights for policymakers to improve health outcomes while reducing associated costs compared to current guidelines and practices. In addition, we compare the performances of various practical MRSA testing protocols using the proposed modeling framework and determine those with close-to-optimal performance and balancing the clinical efficacy and cost-effectiveness. The proposed modeling framework is general and applicable to other infectious diseases.

Bio: Esma Akgün is a Ph.D. candidate in the Department of Management Science and Engineering at the University of Waterloo, under the supervision of Prof. Safa Erenay and Prof. Sibel Alumur Alev. She earned her bachelor’s degree in Industrial Engineering with high honors from Bilkent University. Her research focuses on the application of operations research models and optimization techniques to medical decision-making to improve health systems and outcomes. She is particularly interested in stochastic dynamic modeling and data-driven optimization, with applications in healthcare delivery for screening and testing operations. Her research and teaching contributions have been recognized with the Fraser Award for the best graduate research paper and the Teaching Assistantship Excellence Award.