2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
389
WA75
Legends C- Omni
Health Care, Strategies III
Contributed Session
Chair: Neset Hikmet, Associate Professor, University of South Carolina,
1301 Gervais St, Suite 1010, Columbia, SC, 29208, United States,
1 - Hierarchical Response Model For Casualty Processing In Mass
Casualty Incidents
Alkis Vazacopoulos, Optimization Direct, Inc., 202 Parkway,
Harrington Park, NJ, 07640, United States,
, Nathaniel Hupert,
Dimitris Paraskevopoulos, Panagiotis Petros Repoussis,
Panagiotis Petros Repoussis
This work presents a response and resource allocation model in the aftermath of a
Mass-Casualty Incident. A mixed integer math programming formulation is
proposed for the combined ambulance dispatching, patient-to-hospital
assignment, and treatment ordering problem. The goal is to allocate effectively the
limited resources during the response effort so as to improve patient outcomes,
while the objectives are to minimize the overall response time and the total flow
time required to treat all patients. The model is solved via exact and MIP-based
heuristic methods. The applicability of the model and the performance of the new
optimization methods are challenged on realistic scenarios.
2 - Key Factors And Patterns In Employee Choice Of High Deductible
Health Plans
Qing Ye, Purdue University, 315 N Grant St, West Lafayette, IN,
47907, United States, , Bhagyashree Katare,
Yuehwern Yih
U.S. employers have increasingly provided high-deductible health plans in
response to the rising cost of health care. This study provides insight into selecting
and switching behavior of employees towards high-deductible health plans. Data
mining techniques are utilized to identify factors associated with their plan choice
mobility. A case study is presented using five years’ claims information.
3 - Hospital Information Technology Investment Impacts On
Patient Satisfaction, Clinical Performance, Efficiency,
And Patient Outcomes
Neset Hikmet, Associate Professor, University of South Carolina,
1301 Gervais St, Suite 1010, Columbia, SC, 29208,
United States, Benjamin Schooley
This study extends prior research on healthcare information technology (HIT)
investment impacts on hospital performance. We analyzed 102 different HIT
investment types; categorized them as clinical, administrative, strategic, and
infrastructure HIT investments; and examined relationships between these and
hospital performance scores. Combining secondary survey data from U.S.
hospitals and a separate data set from CMS, we found significant positive and
negative relationships between clinical and infrastructure HIT investment and
hospital total performance, clinical performance, patient satisfaction, and
efficiency scores - controlling for organizational factors.
WA76
Legends D- Omni
Applied Probability I
Contributed Session
Chair: Julian Sun, Cornell, Ithaca, NY, 14850, United States,
1 - Flexible Estimation Of Conway-maxwell Poisson Distribution
Suneel Babu Chatla, Doctoral Student, National Tsing Hua
University, Hsinchu, 30013, Taiwan,
, Galit Shmueli
The Conway-Maxwell Poisson (CMP) distribution is popularly used for its ability
to handle both overdispersed and underdispersed count data. Yet, there is no
efficient algorithm for estimating CMP regression models, especially with high-
dimensional data. Extant methods use either nonlinear optimization or MCMC
methods. We propose a flexible estimation framework for CMP regression based
on iterative reweighted least squares (IRLS). Because CMP belongs to the
exponential family, convergence is guaranteed and is more efficient. We also
extend this framework to allow estimation for additive models with smoothing
splines.
2 - Fast Approximate Policies For Large Networks
Ankur Mani, University of Minnesota, 808 Berry St. Apt. 410,
St. Paul, MN, 55114, United States,
Optimal policies for networks may be computationally hard and still may lead to
suboptimal outcomes if the network information is noisy. We present simple
heuristics with comparable performance. These policies are easy to compute and
we provide guarantees for their performance. As an example we study price
discrimination in networks and show that our heuristics give approximately
optimal expected profits for large random networks.
3 - Multivariate Subexponential Distributions And Their Applications
Julian Sun, Cornell, Ithaca, NY, 14850, United States,
, Gennady Samorodnitsky
We propose a new definition of a multivariate subexponential distribution. We
compare this definition with the two existing notions of multivariate
subexponentiality, and compute the asymptotic behavior of the ruin probability in
the context of an insurance portfolio, when multivariate subexponentiality holds.
Previously such results were available only in the case of multivariate regularly
varying claims.
WA77
Legends E- Omni
Opt, Integer Programing V
Contributed Session
Chair: Victoire Denoyel, PhD Candidate, ESSEC Business School,
Paris, France,
1 - Territory Design With Risk For A Micro Finance Institution
Tahir Ekin, Assistant Professor of Quantitative Methods, Texas
State University, 601 University Dr. Mccoy 411, San Marcos, TX,
78666, United States, , Fabian Lopez Perez,
Francis Mendez, Jesus Jimenez
Micro finance institutions (MFIs) play an important role in emerging economies
as part of programs that aim to reduce income inequality and poverty. This talk
addresses a territory planning problem for a MFI. We propose a mixed integer
programming model that lets the decision maker choose the location of the
branches to be designated as territory centers and allocate the customers to these
territory centers with respect to risk and planning criteria: the total workload,
monetary amount of loans and profit allocation. In order to solve this model for
the large size instances of the MFI, we utilize heuristics such as fixing variables,
perturbation, and dynamic relocation of territory centers.
2 - Model Of Ambulance Deployment And Dispatch Arrangement And
Simulation-based Assessment Of Mass Casualty Incident
Yu-Ching Lee, Assistant Professor, National Tsing Hua University,
Hsinchu, Taiwan, Yen-Ting Liu,
Albert Y. Chen, Yu-Shih Chen
A major focus of emergency medical service (EMS) systems is to save lives,
minimize response time and to increase the survival rate in both the cases of
stochastic events and extreme events. The extreme events, such as natural
disaster (earthquake) and man-made disaster (terrorist attacks), are usually not
predictable and need multiple rounds of ambulance dispatch. This paper is
committed to model the deployment and split dispatch of ambulances, and to
generate numerical results to assess the overall services, hoping to be an
optimization-model-aided support to the real world operations.
3 - Solving Utility-maximization Multinomial Choice Problems:
When Is The First-choice Model A Good Approximation?
Victoire Denoyel, PhD Candidate, ESSEC Business School, Paris,
France, Victoire Denoyel, PhD
Candidate, Brooklyn College, Brooklyn, NY, NY, United States,
Laurent Alfandari, Aurelie Thiele
For optimization problems with a utility maximization objective, it is common to
model consumer behavior with MNL logit. This can lead to high fractional
complexity when binary decision variables are involved. A first-choice or
assignment model is computationally simpler although less close to reality. We
design the first comparison of the two approaches in the context of optimization.
Our main contribution is to quantify which probabilistic assumptions allow the
use of the solution of the first-choice model as an approximation to the MNL logit
model. Applications vary from policy to retail or facility location.
WA77