Nilabh Ohol

ORCID Identifier(s)

0000-0001-6269-2485

Graduation Semester and Year

2018

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Industrial Engineering

Department

Industrial and Manufacturing Systems Engineering

First Advisor

Victoria Chen

Abstract

Interdisciplinary pain management combines multiple disciplines of professionals to understand the biological and psychosocial factors causing a patient's pain and to determine the best treatments among many to administer. The Eugene McDermott Center of Pain at University of Texas at Southwestern Medical Center in Dallas runs a two stage adaptive interdisciplinary pain management program with the aim to improve current and future pain outcomes. The sequential treatment regime for the pain and the observational nature of data yield to time varying confounding and a form of endogeneity. This yields biased estimates of the treatment effects which is undesirable. Our adaptive interdisciplinary pain management framework employs state transition and outcome models estimated from actual patient data in the program. This research develops a framework based on the inverse probability of treatment weighting technique to address endogeneity while estimating state transition and outcome models. The parameter estimates obtained from these models are unbiased and can be interpreted as causal effects of the treatments.

Keywords

Time varying confounding, Inverse probability of treatment weighting, Adaptive treatment strategies, Pain management

Disciplines

Engineering | Operations Research, Systems Engineering and Industrial Engineering

Comments

Degree granted by The University of Texas at Arlington

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