Abstract
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. We structure this decision-making process using dynamic programming (DP) to generate adaptive treatment strategies for this two-stage program. An approximate DP solution method is proposed in which state transition models are constructed based on data from the pain management program. The state transition probabilistically models how a patient's pain characteristics change from Stage 1 to Stage 2. The objective is to select the minimal treatment necessary to achieve acceptable (lower) pain outcomes. We present here the framework with some details on the modeling of state transitions and the optimization objective.
Original language | English |
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State | Published - 1 Jan 2010 |
Event | IIE Annual Conference and Expo 2010 - Cancun, Mexico Duration: 5 Jun 2010 → 9 Jun 2010 |
Other
Other | IIE Annual Conference and Expo 2010 |
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Country/Territory | Mexico |
City | Cancun |
Period | 5/06/10 → 9/06/10 |
Keywords
- Dynamic programming
- Pain management
- Statistical modeling