2015 Informs Annual Meeting

SB37

INFORMS Philadelphia – 2015

SB35 35-Room 412, Marriott Joint Session HAS/Analytics: Predictive Models for Clinical and Public Health Decision Making Sponsor: Health Applications Sponsored Session Chair: Ozgur Araz, University of Nebraska Lincoln, College of Business Administration, Lincoln, United States of America, ozgur.araz@unmc.edu 1 - Risk Factors for Disease Progression in Sepsis Patients: A Retrospective Cohort Study Benjamin Whitsitt, University of Nebraska Medical Center, 42nd and Emile, Omaha, NE, 68198, United States of America, benjamin.whitsitt@unmc.edu, Micah Beachy, Lorena Baccaglini, Gleb Haynatzki, Michael Ash, Ozgur Araz In this study we identify risk factors associated with the progression of sepsis to severe sepsis and/or septic shock and estimate the likelihood of disease progression for different patient groups. We also assess the probability of death and readmission amongst a sepsis population at two area hospitals in Omaha, Nebraska. Multiple logistic regression model is used to determine the likelihood of disease progression, mortality, and readmission. 2 - The Impact of Geographic Localization of Patients on Hospital Performance Paul Cronin, PhD Student, University of Texas at Austin, 2110 Speedway Stop B6500, Austin, TX, 78712, United States of America, paul.cronin@utexas.edu, Douglas Morrice, Jonathan Bard, Luci Leykum We study the impact of geographic localization of patients on hospital performance using patient-level data from a Texas teaching hospital. Performance is measured by length of stay in ED and hospital, waiting time for bed assignments, patient transfers between teams, and hour of discharge. The results of this study inform admission decision-making including patient allocation to medical teams and admission capacity planning. 3 - A Dynamic Model for Population Screening: Risk Perception and Feedback in Screening Decision Ozge Karanfil, PhD Candidate, MIT Sloan School of Management, 100 Main Street, E62-379, Cambridge, MA, 02142, United States of America, karanfil@mit.edu, John D. Sterman In this study we built a behaviorally realistic, bounded simulation model to explain changes in policy action thresholds of clinical practice guidelines, and to document evidence of gaps between scientific evidence-based guidelines and actual practice. This is the first theory building piece for cancer screening dynamics in the US that takes into account the broader cognitive and socio- political environment in which screening decisions are embedded. 4 - Modeling the Impact of Chronic Disease Combinations on 30-day Hospital Readmissions Sabrina Casucci, University at Buffalo (SUNY), 339B Bell Hall, Amherst, NY, 14260, United States of America, scasucci@buffalo.edu, Alexander Nikolaev, Li Lin, Sharon Hewner Individuals with chronic disease are at high risk for hospital readmission. There is significant opportunity to reduce utilization and costs by developing new readmission reducing interventions for this population. This work reveals and quantifies the causal impacts of specific chronic disease combinations on hospital readmissions. The results are reported for a subset of the New York State adult Medicaid population using observational causal inference methods and tools.

logistical issues related to communication, transportation, managing donors and volunteers arise .Depending upon the phase of the disaster the blood products required to treat the victims vary. Safety of the blood supply and adherence to regulations is crucial. 2 - Humanitarian Logistics in the Philippines: Case of Typhoon Haiyan Brian Gozun, La Salle - Universitat Ramon Lull, Carrer de Sant Joan de La Salle 42, Barcelona, Spain, bcgozun@gmail.com, Francesc Miralles The study applied a humanitarian logistics framework through a deductive approach on the experiences of various stakeholders in the Philippines after the onslaught of Super Typhoon Haiyan in November 2013. The researchers made use of primary and secondary data in order to explore humanitarian operations management challenges before, during and after the onslaught of the typhoon by analyzing the current humanitarian logistics practices in the country. 3 - Vehicle Management Policies under Stochastic Budget for Humanitarian Development Programs Milad Keshvari Fard, ESSEC Business School, 1 Avenue Bernard Hirsch, Cergy, France, milad.keshvarifard@essec.edu, Mahyar Eftekhar, Felix Papier In this paper we attempt to find the optimal fleet management policies in a humanitarian organization running development programs. As the budget of these organizations - mostly financed through donations- is uncertain, the transportation planning is challenging. We try to identify the optimal number of vehicles to be purchased, the fraction of demand to be satisfied, and the fraction of budget that should be saved for future periods with low levels of donations. 4 - A Stochastic Programming Model for Prepositioning and Distributing Emergency Supplies Xiaofeng Nie, Assistant Professor, Nanyang Technological University, 50 Nanyang Avenue, Singapore, Singapore, xiaofengnie@ntu.edu.sg, Aakil Caunhye, Yidong Zhang, Mingzhe Li We propose a two-stage stochastic program to preposition and distribute emergency supplies. In the first stage the model decides where to locate warehouses and how many quantities to stock for prepositioning purposes, while in the second stage the model decides how many quantities to transport to demand sites and the corresponding routing. A case study is provided to illustrate our model and compare with other benchmark models. SB37 37-Room 414, Marriott Health Care Modeling and Optimization II Contributed Session Chair: Dongping Du, University of SOuth Florda, Tampa, FL, 33613, United States of America, dongpingdu@mail.usf.edu 1 - A Network Heuristic for Stochastic Healthcare Facilities Location and Configuration in Sequence Xue Han, Assistant Professor, Southeast Missouri State University, 1933 Rock Creek Ln, Cape Girardeau, MO, 63701, United States of America, xhan@semo.edu, Wilbert Wilhelm This research aims on finding the best locations and capacities for new healthcare facilities providing multiple services over a 10-20 years planning horizon under stochastic demand in a competitive environment. We develop a heuristic algorithm for introducing new facilities in the market in sequence by solving resource constrained shortest path problem iteratively on a specially-constructed network. This heuristic preserves the advantages in solution time and linearity in objective function. 2 - Simulation Optimization for Reconstructing Rhythmic Mechanisms in Atrial Fibrillation Dongping Du, University of SOuth Florda, Tampa, FL, 33613, United States of America, dongpingdu@mail.usf.edu, Hui Yang Atrial fibrillation (AF) is a common cardiac arrhythmia that affects more than 5 million Americans. The understanding of AF initiation and maintenance has remained sketchy due to the inability of reconstructing rhythmic mechanisms. This study develops a multi-scale atrial model and an optimization algorithm to reconstruct fibrillatory conduction and replicate patterns in clinical recordings. The research will produce a computer-aided decision support tool for optimizing AF surgical treatments.

SB36 36-Room 413, Marriott Humanitarian Applications II Sponsor: Public Sector OR Sponsored Session

Chair: Mahyar Eftekhar, Arizona State University, P.O. Box 874706, Tempe, AZ, 85287, United States of America, eftekhar@asu.edu 1 - Blood Storage and Transportation: An Important Component of Humanitarian Logistics Divya Nagilla, Faculty Asociate, Institute of Management Technology, Survey No.38, Cherlaguda Village, Shamshabad, RR District, Hyderabad, 501218, India, ndivya@imthyderabad.edu.in, Sourabh Bhattacharya Supply of blood during and after disasters is a major part in humanitarian logistics.The major problem during disasters is not the lack of blood supply but disruption of the blood distribution system .A large number of practical and

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