2016 INFORMS Annual Meeting Program

490 / 561

INFORMS Nashville – 2016
490
2 - Determinants Of Meaningful Usage Of Health
Information Technology
Jingyun Li, Assistant Professor, California State University -
Stanislaus, 1 University Circle, Turlock, CA, 95382, United States,
, Indranil R Bardhan, Steves Ring
Meaningful use (MU) is a new, government-funded initiative to improve health
care system via adoption and usage of HIT. The first stage of MU focuses on
capturing and sharing of electronic patient health information. In this study, we
explore the characteristics of hospitals that are likely to be associated with
achievement of MU. Using archival, hospital-level data gathered from several
sources, we observe that hospitals with greater IT leadership are more likely to
achieve meaningful use. We also observe that standalone hospitals are less likely
to achieve meaningful use. Our findings indicate that hospitals with greater levels
of EMR support are also more likely to achieve meaningful use.
WE21
107A-MCC
Joint Session MSOM-HC/HAS: Healthcare Operations
Sponsored: Health Applications
Sponsored Session
Chair: Tolga Tezcan, London Business School, Regent’s Park, O,
London, TX, NW1 4SA, United Kingdom,
1 - The Role Of Non-clinical Workforce On Patient Service:
Evidence From NHS Helpline
Bilal Gokpinar, UCL, London, United Kingdom,
, Emmanouil Avgerinos
Although non-clinical workers are vital in many healthcare delivery settings, their
impact on efficiency and quality of patient service has not been examined in the
OM literature. In this study, making use of a novel dataset based on NHS’s 111
non-emergency helpline in England, we quantify and demonstrate trade-offs
associated with employing non-clinical personnel in delivering patient service.
Our results indicate that while non-clinical workforce increases the efficiency of
patient service by reducing abandoned calls, it may lead to new inefficiencies
through misuse of critical resources (i.e., unnecessary ambulance dispatches) and
it may reduce the quality outcome of the patient service.
2 - Physiology-based Anticipative Icu Management
Yasin Ulukus, University of Pittsburgh,
Guodong Pang, Andrew J Schaefer, Gilles Clermont
The efficient operation of ICUs is crucial to providing high quality of care while
controlling costs. We consider transfer operations from an ICU to a downstream
unit. In current practice, downstream beds are requested only when a patient is
clinically ready for transfer. We investigate anticipative bed requests that can be
made before a patient is clinically ready for transfer, and show that such policy
combined with effective use of clinical markers can significantly improve the
system performance. We present a Markov Decision Process (MDP) model and
solve it via approximations. We further investigate the sensitivity of policy change
upon cost parameter estimation errors via robust models.
3 - New Empirical Evidence For The Clinical Effectiveness And
Process Implications Of Managing Migraine Care Via
Telemedicine: Interim Results
Abraham Seidmann, University of Rochester, Simon Business
School, Dir of OR Dept, Rochester, NY, 14627, United States,
Balaraman Rajan,
Deborah Friedman
Telemedicine has been proved to increase access to patients and reduce travel
burden. In the context of an ongoing pilot study of telemedicine for individuals
with migraine, we completed in-person baseline assessments and follow-up visits
via telemedicine to test the hypothesis that follow-up care delivered by
telemedicine is as effective as with in-office visits. We then investigate ways in
which telemedicine could add economic value to patients through convenience
and better compliance, and benefit specialists through a higher productivity.
4 - Adaptive Monitoring Of Depression Treatment Population:
A Data-driven Approach
Ying Lin, University of Washington, ,
Shan Liu, Shuai Huang
30 million Americans use antidepressant medication. Inadequate follow-up
monitoring has been identified as a main challenge in managing the depression
patient population. We developed a decision support algorithm to create patient-
specific adaptive monitoring schedules and dynamically allocate limited sensing
resources to detect high risk individuals of severe depression. The proposed
method integrates depression trajectory modeling, prognosis, and selective
sensing into a unified framework. The effectiveness of the proposed method is
demonstrated on a depression treatment population.
WE22
107B-MCC
Joint Session MSOM-HC/HAS: Modeling and
Optimization for Organ Allocation and
Donation Networks
Sponsored: Health Applications
Sponsored Session
Chair: Murat Kurt, Merck Research Labs, 351 N. Sumneytown Pike,
North Wales, PA, 19454, United States,
Co-Chair: David Kaufman, Assistant Professor, University of Michigan-
Dearborn, 19000 Hubbard Dr, Dearborn, MI, 48126, United States,
1 - Designing an Efficient And Fair Heart Allocation Rule
For Transplantation
Farhad Hasankhani, Clemson University, 278 Freeman Hall,
Clemson, SC, 29634, United States,
Amin Khademi
The optimal allocation of limited donated hearts to patients on the waiting list is
one of the top priorities in heart transplantation management. To design an
efficient and fair system for allocating donor hearts to patients waiting for
transplantation, we model the waiting list as a fluid model of overloaded queues.
The fluid model is an optimal control problem with vector valued state variable
defined as number of patients waiting for transplantation in each class and control
variable defined as number of hearts to be allocated to patients of each class.
2 - Cherrypicking Kidneys And Patients:
Incentives In Transplant Centers
Mazhar Arikan, University of Kansas, 931 Drum Dr, Lawrence, KS,
66049, United States, , Baris Ata,
Rodney Parker
In 2007 the Centers for Medicare and Medicaid Services implemented a set of
regulations for transplant centers. These rules evaluate transplant centers based
on one-year patient and organ survival rates post transplantation. Using actual
transplant data, we empirically analyze some potential unintended consequences
of these regulations such that more risk averse centers choose healthier patients
and higher quality organs to transplant.
3 - Modeling Of The United States Liver Allocation System Policy To
Reduce Disparity Using Novel Approaches
Sanjay Mehrotra, Northwestern University,
, Vikram Kilambi
We propose and study a DSA-centered linking approach for organ sharing. This
approach was tested in and out-of-sample by using different demand generation
procedures. We show that, under suitable conditions, the known redistricting and
concentric circle approaches for organ sharing are retrievable from our more
general modeling framework. We will present results comparing the proposed
approach with alternatives.
4 - Redesigning The National Network For Deceased Donor Organ
Extraction In The Netherlands
Joris van de Klundert, Erasmus University Rotterdam,
, Kristiaan Michel Glorie,
Thije Van Barneveld, Sylvia Elkhuizen, Kirsten Ooms
End Stage Renal Disease is a fatal condition, for which a choice of costly
treatment exists. Kidney transplantation is the most cost-effective treatment. In
The Netherlands, kidney extraction for transplantation is nationally coordinated
to ensure high quality transplantation. This requires responsive deployment of
highly specialized teams, which forms a costly service process in itself. In this talk,
we consider the present regional structure and operating mode, and consider the
problem of finding improved structures and operating procedures. We present
results of the simulation analysis, and consider practical requirements taken into
account in the implementation which starts in 2017.
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