Informs 2015

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INFORMS Philadelphia – 2015
357
TD34
34-Room 411, Marriott
Joint Session HAS/MSOM-Healthcare: Operational
Issues and Information Sharing in Healthcare
Sponsor: Health Applications
Sponsored Session
Chair: Subodha Kumar, Carol And G. David Van Houten, Jr. ‘71
Professor, Mays Business School, Texas A&M University, Wehner 301F
- 4217 TAMU, College Station, TX, 77843, United States of America,
1 - Sustainability Planning for Healthcare Information Exchanges
Tharanga Rajapakshe, Assistant Professor,
University of Florida, W. University Ave, Gainesville, FL, 32611,
United States of America,
We develop an analytical framework to study sustainability of Healthcare
Information Exchanges and to demonstrate its use when the revenue is generated
(i) under one revenue model (like membership fee), and (ii) under a combination
of multiple revenue models (like membership fee and rebate structure for the
practice from supporting vendors).
2 - The Impacts of Healthcare Information Exchanges:
An Empirical Investigation
Emre Demirezen, Assistant Professor, Binghamton University
SUNY, 4400 Vestal Parkway East, AA-242, Binghamton, NY,
13902, United States of America, ,
Subodha Kumar, Ramkumar Janakiraman
In the last decade, the U.S. government has been aggressively promoting the use
of electronic health records and the establishment of regional healthcare
information exchanges (HIEs). HIEs facilitate electronic health information
exchange among healthcare providers that is considered to be beneficial for the
society. However, the real benefits of HIEs are not well understood. Hence, in this
study, we work with an HIE provider based in the state of New York to investigate
the benefits of HIEs.
3 - Chance Constrained Operating Room Scheduling with Uncertain
and Ambiguous Information
Zheng Zhang, University of Michigan, 1205 Beal Ave, Ann Arbor,
MI, 48105, United States of America,
Brian Denton, Xiaolan Xie
We describe stochastic programming and distributionally robust optimization
models that allow for uncertain or ambiguous surgery duration data, respectively.
Each of the models considers surgery-to-OR allocation decisions in the context of
probabilistic constraints on completion time that vary by OR. We describe column
generation approaches that are tailored to these two model formulations. Results
are presented to illustrate the potential use of these models in practice.
4 - Bundled Payments for Healthcare Services: A Framework for the
Healthcare Provider Selection Problem
Seokjun Youn, PhD Student, Research Asistant, Mays Business
School, Texas A&M University, 320R Wehner Building,, 4217
Texas A&M University, College Station, TX, 77843, United States
of America, , Chelliah Sriskandarajah,
Subodha Kumar
Identifying competitive healthcare providers is an important issue for the
successful operation of bundled payments. We develop a selection framework via
data envelopment analysis and combinatorial auction (CA). Based on efficiency
and effectiveness measures, outstanding performers are pre-selected. Finally, CA
determines winners. To evaluate the impact of design issues on the CA
performance, we combine and utilize several real dataset from the healthcare
sector.
TD35
35-Room 412, Marriott
Disaster and Emergency Management II
Contributed Session
Chair: Shaligram Pokharel, Professor, Qatar University, Doha, Qatar,
1 - Solution Methodologies for Debris Removal in Disaster Response
Bahar Y. Kara, Associate Professor, Bilkent University, Industrial
Engineering, Ankara, Turkey, ,
Oya E. Karasan, Nihal Berktas
In this study we provide solution methodologies for debris removal problem in
the response phase. Debris removal activities on certain blocked arcs have to be
scheduled in order to reach a set of critical nodes such as schools and hospitals.
Two mathematical models are developed with different objectives. The models are
tested over real data from districts of Istanbul.
2 - Service-based Distribution Network Model for Location of
Temporary Relief Facilities
Shaligram Pokharel, Professor, Qatar University, Doha, Qatar,
, Rojee Pradhananga, Fatih Mutlu,
Jose Holguin-Veras
A supply allocation and distribution model is proposed to minimize the total
waiting times at the demand points by considering the possibilities of transferring
excess resources between the temporary facilities and backordering of demand in
different time periods. Model is applied on a test instance to analyze the service
and cost trade-offs. (This research is made possible by a NPRP Award NPRP 5-200-
5-027 from the Qatar National Research Fund (a member of the Qatar
Foundation). The statements herein are solely the responsibility of the authors.)
3 - The Network Structure: What it Can Tell About Disaster Warning
Effectiveness?
Xiangyang Guan, University of Washington, 201 More Hall,
Box 352700, Seattle, WA, 98195-2700, United States of America,
, Cynthia Chen
Knowing how public awareness and action change after disaster warning is
critical for effectiveness of warning issuance. Multiple data sources – social media,
taxi trips and subway ridership – are leveraged. Temporal evolutions of the
structure (motifs) of social media network and subway network are established as
measures of public awareness and action. Our result identified a lag of one day in
average between warning issuance and public awareness, and between public
awareness and action.
TD36
36-Room 413, Marriott
Fire and Emergency Medical Services
Sponsor: Public Sector OR
Sponsored Session
Chair: Laura Mclay, Associate Professor, University of Wisconsin,
1513 University Ave, ISYE Department, Madison, WI, 53706,
United States of America,
1 - Predicting the Spatial Distribution of Heart Attack Incidence
in Alberta
Armann Ingolfsson, University of Alberta, Edmonton, Canada,
Amir Rastpour, Reidar Hagtvedt
We use Poisson regression with a linear-without-intercept link function to predict
the incidence of heart attacks by geographic region, as a function of age, gender,
education, and income characteristics. We discuss model specification and
validation and we present results based on 10 years of empirical data.
2 - Dynamic Ambulance Allocation Utilizing Demand Data Analytics
for Pre-hospital EMS
Yu-Ching Lee, Assistant Professor, Department of Industrial
Engineering and Engineering Management, National Tsing Hua
University, No. 101, Section 2, Kuang-Fu Road, Hsinchu, Taiwan
- ROC, , Albert Chen, Yu-shih Chen
Pre-hospital Emergency Medical Services (EMS) provide the critical function of
on-site medical treatment and stabilization of patients. The quality of EMS affects
the survival of patients in emergency situations. A better management of
ambulances could potentially improve the effectiveness and efficiency of EMS.
We study a real-time decision support system featuring demand prediction,
distribution estimation, scenario generation, robust ambulance deployment, and
the optimal ambulance dispatching
3 - A Simulation Optimization Method for Emergency
Service Location
Rozhin Doroudi, PhD Student, Northeastern University, 260
Washington St. Apt. 305, Malden, MA, 02148, United States of
America, Gerald Evans, Gail Depuy
A fire department with an available fleet wants to determine the location of its
fire stations and how to distribute its fleet among those locations. An iterative
approach involving the use of a linear program and a simulation model is
proposed for the problem
TD36