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Simulation and Optimization Models for Scheduling Multi-step Sequential Procedures in Nuclear Medicine

The rise in demand for specialized medical services in the U.S has been recognized
as one of the contributors to increased health care costs. Nuclear medicine is a specialized
service that uses relatively new technologies and radiopharmaceuticals with
a short half-life for diagnosis and treatment of patients. Nuclear medicine procedures
are multi-step and have to be performed under restrictive time constraints.
Consequently, managing patients in nuclear medicine clinics is a challenging problem
with little research attention. In this work we present simulation and optimization
models for improving patient and resource scheduling in health care specialty clinics
such as nuclear medicine departments. We rst derive a discrete event system
speci cation (DEVS) simulation model for nuclear medicine patient service management
that considers both patient and management perspectives. DEVS is a formal
modeling and simulation framework based on dynamical systems theory and provides
well de ned concepts for coupling components, hierarchical and modular model construction,
and an object-oriented substrate supporting repository reuse. Secondly, we
derive algorithms for scheduling nuclear medicine patients and resources and validate
our algorithms using the simulation model. We obtain computational results that
provide useful insights into patient service management in nuclear medicine. For example, the number of patients seen at the clinic during a year increases when a group
of stations are reserved to serve procedures with higher demand. Finally, we derive a
stochastic online scheduling (SOS) algorithm for patient and resource management in
nuclear medicine clinics. The algorithm performs scheduling decisions by taking into
account stochastic information about patient future arrivals. We compare the results
obtained using the SOS algorithm with the algorithms that do not take into consideration
stochastic information. The SOS algorithm provides a balanced utilization of
resources and a 10% improvement in the number of patients served.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2010-05-7958
Date2010 May 1900
CreatorsPerez Roman, Eduardo
ContributorsNtaimo, Lewis, Malave, Cesar O.
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
Typethesis, text
Formatapplication/pdf

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