TITLE: Analytics Approaches for Strategic & Operational Decision-Making in Healthcare
ABSTRACT: This talk will showcase the use of some of operations research methods by providing cases in analyzing healthcare systems and studying disease progression and control.
The first part of the talk will focus on breast cancer screening policies in the high-risk population. The performance of mammography is not satisfactory for women at high-risk for breast cancer. Other technologies such as ultrasound and MRI might address some of the limitations of mammography. Currently, there is no consensus on optimal use of these technologies. Çağlayan will present the optimization model they developed to identify optimal, practical and cost-effective screening policies and their main findings.
The second part of the talk will present a novel method to optimize staffing levels in complex healthcare delivery systems such as Emergency Department (ED). Keeping waiting times at acceptable levels is not only important for patient satisfaction but also a patient safety concern in EDs. However, optimizing physician staffing levels is not an easy task for a system with unscheduled time-varying arrivals, medium-to-long service times, multiple patient classes and multiple treatment stages. In this talk, Çağlayan will introduce their novel network model to tackle the physician-staffing problem in ED.
Keywords: mixed-integer linear program, disease management, queuing theory, staffing
BIO: Çağlar Çağlayan is a Ph.D. candidate in the Operations Research program at Georgia Institute of Technology. His research interests include mathematical modeling, optimization, and data- and decision-centric healthcare analytics. He utilizes a broad range of analytical methods and collaborates with healthcare providers and researchers to conduct data-driven research with methodological contributions and clinically impactful findings.