2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
433
WC18
106A-MCC
DMA Healthcare
Contributed Session
Chair: Kaiye Yu, Tsinghua University, Room 615,Shunde Building,
Tsinghua University, Beijing, BJ100084, China,
1 - Optimal Reimbursement Schemes For Maternity Care Safety
And Quality
Cheng Zhu, McGill University, 701-801 Sherbrooke Est, Montreal,
QC, H2L 0B7, Canada, ,
Beste Kucukyazici
The amount of unnecessary C-Sections, which expose proven higher postpartum
complications of mothers and newborns as well as heavy economic burden, has
been increasing constantly and this growth raises great concerns for the policy
makers. This research focuses on optimizing payment mechanisms to reimburse
obstetricians, in order to reduce unnecessary C-sections while retain it for those
who need it, resulting in enhanced birth quality with alleviated economic burden
for overall health care system. The optimal reimbursement schemes are further
verified empirically with large datasets.
2 - Using Policy Flight Simulator To Evaluate Scalability Of Evidence
Based Practices
Zhongyuan Yu, Research Assistant Professor, Stevens Institute of
Technology, Hoboken, NJ, 07030, United States,
, William B Rouse, Michael Pennock, Kara Pepe
Numerous evidence-based practices have demonstrated reduced medical costs,
improved patient experiences and better quality of life. However, concern from
stakeholders in health system seems to be holding back adoption. Policy flight
simulator is proposed to find out what affects scalability of these practices, and
assess what needs to be adjusted in order to increase confidence of senior
administrators to expand these practices. Policy flight simulators fuse aspects of
traditional scientific analysis, engineering, social science, and visualization to
provide decision makers an immersive experience to increase comfort level with
simulation-based data-driven decision making processes.
4 - Modeling And Assessment Of The Risk Of Colorectal Polyp
Kaiye Yu, Tsinghua University, Room 615,Shunde Building,
Tsinghua University, Beijing, BJ100084, China,
, Jie Xing, Wenying Zhou,
Shutian Zhang, Xiaolei Xie, Nan Kong
Most colorectal cancer (CRC) arise from polyps. We identify colorectal polyps risk
factors and develop risk stratification model using machine learning approaches.
The individualized risk assessment tool could offer decision support to both
clinicians and patients.
WC19
106B-MCC
Open-Source Tools for Operations Research
Sponsored: Computing
Sponsored Session
Chair: Matthew J Saltzman, Clemson University, Clemson University,
Clemson, SC, 29634, United States,
1 - New Developments In Pyomo
William E Hart, Sandia National Laboratory,
Pyomo is a Python-based open-source software package that supports a diverse
set of optimization capabilities for formulating, solving, and analyzing
optimization models. In this presentation, we describe new capabilities in Pyomo,
including support for new versions of Python, installation with conda, and
updates for modeling capabilities (bilevel, sp, dae, etc). This talk will also highlight
new documentation resources for users.
2 - Jmarkov: An Integrated Java Framework For Stochastic Modeling
Daniel F Silva, Georgia Institute of Technology, Atlanta, GA,
United States, , Julio C Goez, Juan F Perez,
German Riano
jMarkov allows users to define stochastic models from the basic rules underlying
the system dynamics and then solve the models to obtain performance measures.
It is composed of four modules: (i) the main module supports Markov Chain
models with a finite state space; (ii) jQBD enables the modeling of Quasi-Birth-
and-Death processes; (iii) jMDP offers the capabilities to model and solve Markov
Decision Processes; and (iv) jPhase supports the manipulation and inclusion of
phase-type variables. In addition, jMarkov is highly extensible, allowing the users
to introduce new modeling abstractions and solvers. In this talk we give an
overview of jMarkov, as well as some examples.
WC20
106C-MCC
Understanding the US Index Futures Stock Market
using Research
Invited: Tutorial
Invited Session
Chair: William T. Ziemba, University of British Columbia, 1, Vancouver,
BC, 2, Canada,
1 - Understanding The US Index Futures Stock Market
Using Research
William T. Ziemba, University of Bristish Columbia, Vancouver,
BC, 2, Canada,
I begin with five views or camps of beliefs concerning the US stock market. There
are efficient markets where prices are correct except for transactions costs, risk
premium where excess returns can be made only by bearing additional risk,
efficient markets is hogwash, great investors exist but you cannot tell who they
are in advance and the study of anomalies and other research. Edges arise from
cash flows, institutional practices and behavioral biases. These include the turn of
the year effect, the turn of the month effect, presidential election effects and
mispriced options. I describe the effects and explain why they exist and then
discuss their use in trading considering operational risks, the effect of volatility,
prediction of stock market crashes, slippage, risk management, and optimal
betting sizing. I won the 2015 futures trading contest of the Battle of the Quants
in New York and have been able to obtain very good risk adjusted returns during
July 2013 to May 2016 in the Alpha Z Futures Fund.
WC21
107A-MCC
Healthcare Operations and Capacity Planning
Sponsored: Health Applications
Sponsored Session
Chair: Sukriye Nilay Argon, University of North Carolina, Hanes Hall
CB# 3260, Chapel Hill, NC, 27599, United States,
Co-Chair: Serhan Ziya, University of North Carolina, 356 Hanes Hall,
CB#3260, Chapel Hill, NC, 27599, United States,
1 - Admission, Routing And Early Discharge Decisions In A
Hospital Setting
Lerzan E Ormeci, Koc University, Nermin Kurt,
Amin Khoshkenar
We consider the problem of bed management in a hospital. The patients stay at
the hospital for a random length of time to recover after a surgery. Hence, the
operation schedule has a long-term effect on the occupancy levels, which
significantly affect the quality of care for the patients. To control the occupancy
levels, hospital management has a number of options: 1) New patients may be
rejected at high levels of occupancy, 2) Patients operated by a certain department
may stay in the ward of another department, 3) Patients staying at the hospital
may be discharged early. In this study, we analyze the effects of these decisions on
the hospital performance by modeling the system via Markov decision processes.
2 - Ambulance Redeployment And Dispatching Under Uncertainty
With Personnel Workload Limitations
Shakiba Enayati, North Carolina State University, Raleigh, NC,
United States, Osman Ozaltin,
Maria Esther Mayorga
Emergency Medical Services managers are concerned with providing maximum
possible coverage in a service area. Redeployment refers to dynamic relocation of
idle ambulances to compensate for the coverage loss due to busy ambulances.
Unsystematic redeployments, however, impose superfluous workload on the
personnel. We propose a two-stage stochastic programming model to redeploy
and dispatch ambulances to maximize expected coverage. Our model includes
personnel workload restrictions in a shift. We develop a decomposition algorithm
to determine an upper bound and apply a branch and bound algorithm to find the
optimal solution. We evaluate the performance using a largescale real dataset.
3 - An Optimization Approach For Coordinating Clinic And Surgery
Appointments To Meet Access Delay Service Levels
Esmaeil Keyvanshokooh, University of Michigan, Ann Arbor, Ann
Arbor, MI, United States, , Mark P. Van Oyen
Providing timely access to surgery is crucial for patients with high acuity diseases
like cancer. In this paper, we present an optimization approach for coordinating
clinic and surgery appointments to meet access delay service levels in Colorectal
surgery (CRS). The methodology is applied to historical patient data for CRS to
show its better performance than the current scheduling policy.
WC21