2015 Informs Annual Meeting

MD38

INFORMS Philadelphia – 2015

MD37 37-Room 414, Marriott Health Care Modeling and Optimization VIII Contributed Session Chair: Yunzhe Qiu, Peking University, NO. 298 Chengfu Road, Haidian District, Beijing, China, qiuyunzhe92@163.com 1 - Improving Surgical Instrument Delivery using Optimization and Process Flow Modeling Rama Mwenesi, Center for Healthcare Engineering and Patient Safety, University of Michigan, IOE Building, 1205 Beal Avenue, Efficiency in surgical instrument reprocessing is a key challenge for high-volume surgical centers. Insufficiently cleaned or maintained instruments adversely impact patient safety and surgical outcomes. This study examines how i) instrument cleanability and ii) instrument-set configurations impact efficiencies in reprocessing as well as quality of care and costs of delivery. We evaluate process flow variations in the delivery of instruments and present optimization-based models for improvement. 2 - A Queueing Model of Critical Care Outreach Team in Hospitals Ali Haji Vahabzadeh, PhD Student, The University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand, a.vahabzadeh@auckland.ac.nz, Valery Pavlov The considerable evidence of failed CCOT implementations in hospitals demonstrate a lack of genuine understanding of the CCOT roles and capabilities. Such an evidence suggests that many times implementations follow, in effect, trial and error approach. To allow hospitals making better informed decisions this research proposes a queueing model for understanding the effectiveness of the CCOT on the intensive care unit performance and patient outcomes. 3 - Optimal Incentives for HIV Prevention Funds Allocation under Asymmetric Information Monali Malvankar, Assistant Professor, Western University, St. Joseph’s Hospital, 268 Grosvenor St., London, ON, N6A 4V2, Canada, mmalvan@uwo.ca, Gregory Zaric, Xinghao Yan Resource allocation models often require cost and effectiveness data on the results of an intervention. However, these data may not be available in practice due to several reasons. We model information asymmetry in a multi-level HIV/AIDS resource allocation process with an attempt to answer the following questions. What is the impact of incentives if the preferences and infections prevented at the lower level are unknown at the upper level? 4 - Elective Surgery Scheduling for Multiple Operating Rooms Considering Patient Health Condition Joonyup Eun, PhD Candidate, Purdue University, 315 N. Grant Street, West Lafayette, IN, 47907-2023, United States of America, eunj@purdue.edu, Sang-phil Kim, Yuehwern Yih This research is motivated by the fact that surgery scheduling considering patient condition can contribute to improving patient safety. Surgeons and patients may want to schedule their surgeries early in order to escape from the risk of worsening patient condition. However, the resource limitation on surgeons, operating rooms, etc., forces surgical schedulers to prioritize surgeries. This research suggests a systematic mathematical model to consider patient condition in surgery scheduling. 5 - Who is the Right Kid for the Next Service? A Real Time Access Control Policy in the Pediatric Clinic Ann Arbor, MI, 48109-2117, United States of America, rmwenesi@umich.edu, Joseph Derosier, James Bagian, Shawn Murphy, Amy Cohn

MD38 38-Room 415, Marriott Dynamic Programming and Control II Contributed Session

Chair: Akram Khaleghei, University of Toronto, 1706, 35 Charles Street West, Toronto, ON, M4Y 1R6, Canada, akhalegh@mie.utoronto.ca 1 - Tractable Sampling Strategies for Ordinal Optimization Dongwook Shin, PhD Candidate, Columbia Business School, 612 W 114th Street, Apt. 4R, New York, NY, 10025, United States of America, dshin17@gsb.columbia.edu, Assaf Zeevi, Mark Broadie We consider the problem of selecting one of several competing configurations (systems), where probability distributions are not known, but can be learned via sampling. The objective is to dynamically allocate a finite sampling budget to ultimately select the best system. We introduce a tractable performance criterion and a sampling policy that seeks to optimize it. 2 - Analysis and Modeling of the Aggregate Production Planning via Control Oriented Approaches Yasser A. Davizón, Professor, Universidad Politécnica de Sinaloa, Carretera Libre Mazatlán, Mazatlan, Mexico, ydavizon@asu.edu, César Martínez-Olvera This research work addresses the application of control oriented approaches for the analysis and modeling of the Aggregate Production Planning problem. Analysis is provided for second order dynamical systems with the interest to model Capacity, Inventory level, Work force costs, production rate and demand along the Supply Chain Management by a novel mathematical formulation. Control oriented approaches considered in this paper are: Model Predictive Control and Linear Quadratic Regulator. 3 - Conditional-based Maintenance Policy for a System Subject to Random Failure Akram Khaleghei, University of Toronto, 1706, 35 Charles Street The maintenance optimization of a partially observable degrading system subject to condition monitoring and observable random failure is investigated considering cost minimization. The deterioration process is modeled as a continuous time hidden semi-Markov model with three states: healthy, warning and failure. Only the failure state is observable. Bayesian control chart is designed to prevent the costly system failure. 4 - Capacity Allocation of Appointment Admission Control in a Hierarchical Healthcare System Xin Pan, College of Engineering, PKU, Founder Building 512, Chengfu Street 298, Beijing, 100871, China, paxi_91@126.com, Jie Song, Bo Zhang Motivated by unbalanced demand between General Hospital (GH) and Community Healthcare center (CHC) in a hierarchical healthcare system, we proposed a MDP model where multi-class slots are allocated to multi-class patients. We derive a policy that blocks slots in GH for low-class patients so as to satisfy high-class patients. The policy finally intends to lower the mismatching level in the hierarchical healthcare system, maximizing both the system’s and patients’ revenue in the long-term. 5 - Identification of Parameters in Mathematical Biology Ugur Abdulla, Professor of Mathematics, Florida Institute of Technology, 3627 Mount Carmel Lane, Melbourne, FL, 32901, United States of America, abdulla@fit.edu, Roby Poteau We consider inverse problems for the identification of constant and functional parameters for systems of nonlinear ODEs arising in mathematical biology. We implement a numerical method suggested in U.G.Abdulla,JOTA,85,3(1995). The idea of the method is based on the combination of quasilinearization with sensitivity analysis and Tikhonov’s regularization. We apply the method to various biological models such as the bistable switch model in genetic regulatory networks and angiogenesis model. West, Toronto, ON, M4Y 1R6, Canada, akhalegh@mie.utoronto.ca, Viliam Makis

Yunzhe Qiu, Peking University, No. 298 Chengfu Road, Haidian District, Beijing, China, qiuyunzhe92@163.com, Zekun Liu, Jie Song

This paper develops a real-time appointment scheduling policy considering both the difference and fairness of waiting time among heterogeneous patients. We use the utility theory to measure service satisfaction, which is integrated with CTMDP model. A myopic policy considering heterogeneous patients’ waiting patience is provided to minimize the overall disutility. A case based on the collaborated hospital is investigated, where the results confirm the effectiveness of the policy.

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