2016 INFORMS Annual Meeting Program

437 / 561

INFORMS Nashville – 2016
437
WC30
202B-MCC
Data-Driven Models in Healthcare
Sponsored: Manufacturing & Service Oper Mgmt,
Healthcare Operations
Sponsored Session
Chair: Yichuan Ding, University of British Columbia, 2053 Main Mall,
Sauder School of Business, Vancouver, BC, V6T1Z2, Canada,
1 - Bundled Payments And Value Based Delivery
Jillian B Jaeker, Boston University,
This study aims to understand the care pathways, both inpatient and outpatient
(i.e. end-to-end), for congestive heart failure (CHF) patients, and how these
pathways impact the costs and quality of care. Specifically, our objective is to
identify pathways that are associated with lower or higher than normal
readmission rates, and the associated financial costs of these pathways. Moreover,
we work with hospitals that are participating in the Bundled Payments for Care
Improvement (BPCI) initiative and explore if any recent interventions on behalf
of these hospitals affects the probability of 30 day readmission and total episode
costs.
2 - Dynamic Allocation Of Vaccine Stocks For Pandemic
Influenza Mitigation
Ozden O Dalgic, University of Waterloo, Waterloo, ON, Canada,
Vaccination is our best response against influenza pandemics. However, finding
effective vaccine allocation strategies with current modeling technics can be
challenging. In this study, we propose a hybrid approach combining simulation
and analytical modeling. We employ a model based on a chain-binomial
transition scheme calibrated to an existing agent-based simulation model. The
proposed approach efficiently evaluates the performance of a given vaccine
allocation strategy by reducing the number of random variates. Numerical
experiments show that the proposed approach results in effective dynamic
vaccine allocation strategies.
3 - Designing Personalized Anticoagulation Therapy
Rouba Ibrahim, University College London,
Vedat Verter, Beste Kucukyazici,
Michel Gendreau, Mark Blostein
We develop an analytical framework for personalizing the anticoagulation
therapy of patients who are taking warfarin, and present results from a case study
using data collected at the anticoagulation clinic of the Jewish General Hospital in
Montreal.
4 - Do Patients From Rural Areas Get Proper Referral For
Surgical Care
Yichuan Ding, University of British Columbia, 2053 Main Mall,
Vancouver, BC, V6T1Z2, Canada,
We examined surgical records throughout 98 hospitals in British Columbia during
year 1995-2004, and had two interesting observations: (1) hospitals in rural areas
are correlated with smaller likelihood of post-surgical complications, possibly
because those hospitals have less risky case mix groups; (2) patients from rural
areas, however, are correlated with lower risk of post-surgical complications. We
conduct further investigation and find that the reason for (2) to happen might be
the inefficient communication between the referral hospital and the one that the
surgery takes place.
WC31
202C-MCC
Consumer Behavior in Services
Sponsored: Manufacturing & Service Oper Mgmt,
Service Operations
Sponsored Session
Chair: Qiuping Yu, Assistant Professor, Kelley School of Business,
Indiana University, 1275 E 10th St, Bloomington, IN, 47401,
United States,
1 - Rational Abandonment From Observable Priority Queues
Philipp Afèche, Rotman School of Management, University of
Toronto, Toronto, ON, Canada, ,
Vahid Sarhangian
The literature on customer behavior in queueing systems largely focuses on
customers’ joining decisions and ignores their subsequent abandonment
decisions. Such abandonment behavior is important in priority queues, which are
prevalent in practice. We characterize the equilibrium joining and abandonment
behavior of utility-maximizing customers in an observable priority queue. We
then discuss how the abandonment process in our equilibrium model compares to
that under the standard exogenous abandonment model, and to its empirical
counterpart in a real system.
2 - Learning Quality Through Service Outcomes
Senthil Veeraraghavan, The Wharton School, University of
Pennsylvania, , Laurens G Debo
We study a new firm whose service value is unknown to arriving customers.
Service outcomes are random depending on the quality of the service provider.
Customers decide whether patronize the service based on the limited service
outcomes/reviews that they observe. We consider how service policies influence
consumer learning and social welfare.
3 - Design Of Discretionary Service Lines: An Operational Driver
Of Variety
Laurens Debo, Tuck School of Business, Dartmouth College, 100
Tuck Drive, Hanover, NH, 03755, United States,
Cuihong Li
For discretionary services, the longer the service time, the more value is created
for the customer. In the presence of variability, longer service times also create
more congestion. Hence, a service firm needs to trade off congestion costs with
value creation in service line design. We find that it is optimal to offer a service
line with multiple varieties (that differ in duration and price), even when
customers are homogeneous.
4 - Linking Customer Behavior And Delay Announcements:
Are Customers Really Rational?
Eric Webb, Kelley School of Business, Indiana University,
Bloomington, IN, United States, ,
Qiuping Yu, Kurt M Bretthauer
We empirically explore customer abandonment behavior in the presence of delay
information using data from a call center. Previous work has assumed that
customers are at least partially rational in responding to announcements. In
contrast, we relax all rationality assumptions. Our findings indicate that
customers exhibit loss aversion behavior. In addition, customers may update their
announcement-induced reference point as they hear subsequent announcements.
Our results also indicate that customers may fall for the sunk cost fallacy while
waiting in the queue. We show the impact of these effects on staffing decisions
using a classic staffing model.
WC32
203A-MCC
Risk Analysis III
Contributed Session
Chair: Dexiang Wu, Stockholm University, Stockholm Business School,
Stockholm, 106 91, Sweden,
1 - Modeling Behavior Of Attackers Against The Uncertainty Of
Cascading Failure
Sinan Tas, Assistant Professor, University of Wisconsin-Platteville,
1 University Plaza, Platteville, WI, 53818, United States,
Cascading failure is a common phenomenon in capacity-constrained networks
such as power grids. What if attackers consider manipulating the additional
impact of cascading failure to enhance the damage to the network? We analyze
various attacker types and corresponding defensive investments when cascading
failure is modeled stochastically in a game-theoretic setting.
2 - Analysis Of Intraday Data Effects On Two-stage Risk-averse
Portfolio Optimization
Sitki Gulten, Stockton University, School of Business,
101 Vera King Farris Drive, Galloway, NJ, 08205, United States,
This study examines the application of risk-averse optimization techniques to
daily portfolio management. First, I develop efficient clustering methods for
scenario tree construction. Then, I construct a two-stage stochastic programming
problem with conditional measures of risk, which is used to re-balance the
portfolio on a rolling horizon basis, with transaction costs included. Finally, I
present an extensive simulation study on both interday and high-frequency
intraday real-world data of the methodology.
3 - Exploring Multi-stage Recovery Resilience
Daniel Hernando Romero, University of South Florida, 4411 Shady
Terrace Ln, Unit A, Apt 212, Tampa, FL, 33613, United States,
, Alex Savachkin, Alvaro Sierra,
Weimar Ardila
Multi-stage recovery models enable resilience measurement in the scenarios
where the recovery time is long, so it is estimated en months or years. High
magnitude disruptive events severely affect communities and generate long
lasting consequences. These scenarios require model flexibility to capture different
recovery rates and transitions between recovery stages.
WC32