Abstract/Details

Adaptive pain management decision support system


2010 2010

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Abstract (summary)

Pain management is an international health issue. The Eugene McDermott Center for Pain Management at the University of Texas Southwestern MedicalCenter at Dallas conducts a two-stage interdisciplinary pain management program that considers a wide variety of treatments. Prior to treatment (stage 1), an evaluation records the patient's pain characteristics, medical history and related health parameters. A treatment regime is then determined. At the midpoint of their program (stage 2), an evaluation is conducted to determine if an adjustment in the treatment should be made. A final evaluation is conducted at the end of the program to assess final outcomes.

The structure of this decision-making process uses dynamic programming (DP) to generate adaptive treatment strategies for this two-stage program. Our stochastic DP formulation considers the expected final outcomes when determining treatment. An approximate DP solution method is employed in which state transition models are constructed empirically based on data from the pain management program, and the future value function is approximated using state space discretization based on a Latin hypercube. The state transition probabilistically models how a patient's pain characteristics change from stage 1 to stage 2. The optimization seeks to minimize pain while penalizing excessive.

Indexing (details)


Subject
Industrial engineering
Classification
0546: Industrial engineering
Identifier / keyword
Applied sciences; Adaptive treatment strategies; Decision support system; Decision-making process; Pain management; Stochastic dynamic programming
Title
Adaptive pain management decision support system
Author
Lin, Ching-Feng
Number of pages
171
Publication year
2010
Degree date
2010
School code
2502
Source
DAI-B 72/03, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9781124446943
Advisor
Chen, Victoria C.P.
Committee member
Corley, Bill H. W.; Gatchel, Robert J.; Sundaramoorthi, Durai
University/institution
The University of Texas at Arlington
Department
Industrial & Manufacturing Engineering
University location
United States -- Texas
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3439514
ProQuest document ID
851546353
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/851546353
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