Events Calendar

Epstein Institute / ISE 651 Seminar Series

Speaker: Maria E. Mayorga, Associate Professor, Department of Industrial Engineering, Clemson University

Talk Title: "A Model for Optimally Dispatching Ambulances to Emergency Calls with Classification Errors in Patient Priorities"

Series: Epstein Institute Seminar Series

Abstract: The decision of which servers to dispatch to which customers is an important aspect of service systems. Such decisions are complicated when servers have different operating characteristics, customers are prioritized, and there are errors in assessing customer priorities. We formulate a Markov Decision Process (MDP) model that captures how to optimally dispatch ambulances to prioritized patients in an emergency medical service (EMS) system. It is assumed that patients arrive sequentially, with the location and perceived priority of each patient becoming known upon arrival. The proposed model determines how to optimally dispatch ambulances to patients to maximize the long-run average utility of the system, defined as the expected coverage of true high-risk patients. The utilities and transition probabilities are location dependent, with respect to both the ambulance and patient locations. The analysis considers two cases for approaching the classification errors that correspond to over- and under-responding to perceived patient risk. The optimal policies under different classification strategies are compared to a myopic policy and the effect that classification errors have on the performance of these policies is examined.

Since EMS systems are a public process, expectations of equity arise. Thus we build on the basic model by introducing a set of equity constraints. Four types of equity constraints are considered—two of which reflect customer equity and two of which reflect server equity—all of which draw upon the decision analytic and social science literature to compare the effects of different notions of equity on the resulting dispatching policies. The Markov decision processes are formulated as equity-constrained linear programming models. For both the basic and equity-constrained models, a computational example is applied to an EMS system and simulation is used to confirm that the policies remain effective when they are applied to more realistic situations.


Biography:
Maria E. Mayorga is an Associate Professor of Industrial Engineering at Clemson University. She received her Ph.D. in Industrial Engineering & Operations Research from the University of California, Berkeley. She has research and teaching interests in probability models and stochastic processes and optimization, with applications to healthcare systems engineering. She has authored over a forty publications in archival journals and refereed proceedings. Her research has also been supported by the National Science Foundation (NSF), the National Institutes of Health (NIH) and industry partners, among others. She is a member of INFORMS and the Institute of Industrial Engineers; area editor for the journals Health Systems and Transactions on Healthcare Systems Engineering; and associate editor for IIE Transactions.

Host: Daniel J. Epstein Department of Industrial and Systems Engineering

More Information: Seminar-Mayorga.doc

Location: Von Kleinsmid Center For International & Public Affairs (VKC) - Room 100

Audiences: Everyone Is Invited

Contact: Georgia Lum