Informs 2015

135 / 552

INFORMS Philadelphia – 2015
133
SD41
41-Room 102A, CC
Healthcare Capacity and Patient Flow Analytics
Sponsor: Manufacturing & Service Oper
Mgmt/Healthcare Operations
Sponsored Session
Chair: Retsef Levi, J. Spencer Standish (1945) Professor of Operations
Management, Sloan School of Management, MIT, 100 Main Street,
BDG E62-562, Cambridge, MA, 02142, United States of America,
1 - The Impact of Delays in Transfer out of the Intensive Care Unit
David Scheinker, Postdoctoral Research Fellow, MIT Sloan School
of Management, 50 Memorial Dr, E52-289, Cambridge, MA,
02142, United States of America, , Sara
Dolcetti, Benjamin Christensen, Ulrich Schmidt, Retsef Levi,
Peter Dunn
Few studies examine delays in transfer out of the ICU. We studied four years of
patient flow through six ICUs at a large academic medical center. Over 36% of
ICU patients transferring to a general care unit experienced a non-clinical delay of
over 12 hours. Each day a patient was delayed added approximately a full day to
their total hospital length of stay. These results have direct implications for
hospital capacity design, bed assignments, and care processes across units within
the hospital.
2 - Using Data Analytics and Systems Modeling to Inform Hospital
Obstetrics Capacity Planning
Nan Liu, Columbia University, 722 W. 168th. St., New York, NY,
United States of America, , Linda Green
Using a recent large data set that contains all hospital obstetrics units (n=40) in
NYC, we demonstrate and validate the use of data analytics and systems modeling
for planning hospital bed capacity. We estimate capacity needs based on the
probability of delay experienced by patients in getting a bed. Our analysis reveals
significant variation in obstetrics capacity utilization in NYC; and shows that the
whole city can save $26.5M a year with an appropriate reallocation of obstetrics
capacity.
3 - Optimization-driven Framework to Understand Healthcare
Networks Cost and Resource Allocation
Fernanda Bravo, Assistant Professor, UCLA-Anderson, 110
Westwood Plaza, Los Angeles, CA, United States of America,
, Retsef Levi, Marcus Braun, Vivek Farias
Consolidation in the HC industry has resulted in the creation of large delivery
networks. Traditional practices in cost accounting, e.g., overhead and labor cost
allocation to activities, are not suitable for addressing network challenges. We
develop an optimization-driven framework inspired by network revenue
management to better understand network costs and support strategic network
design and capacity allocation decisions. We report the application of this
approach on a real case study.
SD42
42-Room 102B, CC
Patient Scheduling under Resource Constraints
Sponsor: Manufacturing & Service Oper
Mgmt/Healthcare Operations
Sponsored Session
Chair: Hossein Abouee Mehrizi, University of Waterloo, 200 University
Avenue West, Department of Management Sciences, Waterloo, ON,
N2L 3G1, Canada,
1 - Optimal Mix of Elective Surgical Procedures under Stochastic
Patient Length of Stay
Hessam Bavafa, Assistant Professor, Wisconsin School of Business,
Madison, WI, United States of America,
We consider the problem of allocating daily hospital service capacity among
several types of elective surgical procedures. Our focus is on the interaction
between two major constraining hospital resources: operating room and bed
capacity. In our model, each type of surgical procedure has an associated revenue,
deterministic procedure duration and stochastic hospital length of stay.
2 - Appointment Scheduling Problem when the Server Responds to
Congestion
Zheng Zhang, University of Michigan, 1205 Beal Ave, Ann Arbor,
MI, 48105, United States of America,
Brian Denton, Xiaolan Xie
We describe a stochastic programming model for appointment scheduling that
incorporates server response to congestion, i.e., the server increases the service
rate as the workload grows. It materially differs from previous studies in the sense
that the uncertainty in appointment systems is endogenous with respect to the
decision variables. We describe properties of the model, methods to solve it
efficiently, and results that illustrate the impact of congestion in practice.
3 - Multi-priority Online Scheduling with Cancellations
Van-Anh Truong, Columbia University, 500 West 120th St,
New York, NY, 10027, United States of America,
Xinshang Wang
We study a fundamental model of resource allocation in which a finite amount of
service capacity must be allocated to a stream of jobs of different priorities arriving
randomly over time. Jobs incur costs and may also cancel while waiting for
service. To increase the rate of service, overtime capacity can be used at a cost.
This model has application in healthcare scheduling, server applications, make-to-
order manufacturing systems, general service systems, and green computing.
4 - Multi-speciality Surgery Scheduling under Hospital
Resource Constraints
Shrutivandana Sharma, Singapore University of Technology and
Design, 8 Somapah Road, Singapore, 487372, Singapore,
Hossein Abouee Mehrizi
We consider a surgery scheduling problem, where the decision is to schedule
surgeries of two different types over a finite planning horizon. The number of
surgeries of each type that can be performed in any period is bounded by the
availability of operating resources and the availability of beds. We formulate the
problem as a multi-period inventory problem, and characterize the optimal
solution.
SD43
43-Room 103A, CC
Data-Driven Revenue Management
Sponsor: Revenue Management and Pricing
Sponsored Session
Chair: Pelin Pekgun, Assistant Professor, University of South Carolina,
1014 Greene Street, Columbia, SC, 29208, United States of America,
1 - Resource Pricing in Hospitality Industry
Xiaodong Yao, SAS Institute Inc, SAS Campus Drive, Cary, NC,
27519, United States of America,
Tugrul Sanli, Matt Maxwell, Jason Chen
Best Available Rate (BAR) pricing is probably the most important pricing decision
for hotels. There are two forms: BAR by Day, and BAR by LOS(Length of stay). In
BAR by Day, prices are set for each resource, i.e., a pair of (room type,stay night),
and a LOS price is just the sum of prices on each resource. While in BAR by LOS,
prices are set for each product, a triple of (room type, arrival date, LOS). In this
talk, we discuss several methods for solving the resource pricing problem.
2 - Estimating Revenue Variance in the Pricing Models
Darius Walczak, Principal Research Scientist, PROS Inc., 3100
Main Street, Suite 900, Houston, TX, 77002, United States of
America, , David Mccaffrey
Variance and other distributional moments are important in modeling risk in
optimization problem. They are more challenging computationally than linear
load metrics such as load factor. We adopt an approach found in the Markov
Decision Process literature to calculate variance of revenue under dynamic
policies in single-resource pricing problems. We discuss possible extensions to
network problems.
3 - Advanced Behavioral Models in Integer Optimization
Shadi Sharif Azadeh, EPFL, EPFL ENAC TRANSP-OR GC B3 444,
(Batiment GC) Station 18, Lausanne, Switzerland,
Bilge Atasoy, Moshe Ben-akiva,
Michel Bierlaire
We are interested in discrete optimization models where supply and demand
closely interact (airlines). We propose a general methodology leading to an
integrated supply and demand model, based on discrete choice that is linear in its
decision variables. We illustrate it with an example where a supplier (such as an
airline, or a chain of movie theaters) needs to decide to offer some services, and
to decide about the price of each slot of the available capacity in order to
maximize its revenues.
SD43