The Influence of Pain Self-Management Education on the Prevalence of Opioid Prescription among Patients with Chronic Non-Cancer Pain: An Agent-Based Modeling Simulation

Persistent Link:
http://hdl.handle.net/10150/594392
Title:
The Influence of Pain Self-Management Education on the Prevalence of Opioid Prescription among Patients with Chronic Non-Cancer Pain: An Agent-Based Modeling Simulation
Author:
Samuel-Ojo, Catherine Olubunmi
Issue Date:
2015
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Chronic pain has no cure. It is a lifelong condition presenting a growing concern due to its high occurrence and effects on every facet of life. It cost about $635 billion each year in medical treatment and lost productivity (IOM, 2011). The management of chronic pain using prescription painkiller opioids has increased drastically in the last two decades, leading to a consequential increase in deaths from chronic opioid use. This Plan-Do-Study-Act quality improvement project investigates the problem of the prevalence of opioid prescription using agent-based computational modeling method. The simulation models the interaction of 50 patient-agents with pain self-management messages in an episode of 50 patient iterations (visits) for 10 simulated years. This interaction generates health benefit and risk outcomes represented by wellness data obtained when messages are processed. As the simulation runs, data are dynamically captured and visualized using wellness charts, time series plots, and benefit and risk regression plots. The result of the project provides evidence for research and practice on the process of achieving more impact of programs based on administering pain self-management education to patients with chronic non-cancer pain who are currently on opioid therapy and on the process of customizing interventions that might take advantage of the conditions of behavior change driven by pain self-management messages. The tools and the evidences in this project are highly recommended to nurse practitioners primary care providers involve with providing care to the vulnerable groups of patient with chronic non-cancer pain. These evidences might inform the formation of self-management interventions that might lead to a decline in opioid use and prescription and accelerate the acceptance of self-management practices.
Type:
text; Electronic Dissertation
Keywords:
Chronic non-cancer pain; Opioid prescription; Pain Self-management; Pain Self-Management Education; Self-management education; Nursing; Agent-based modeling simulation
Degree Name:
D.N.P.
Degree Level:
doctoral
Degree Program:
Graduate College; Nursing
Degree Grantor:
University of Arizona
Advisor:
Shea, Kimberly D.
Committee Chair:
Shea, Kimberly D.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.titleThe Influence of Pain Self-Management Education on the Prevalence of Opioid Prescription among Patients with Chronic Non-Cancer Pain: An Agent-Based Modeling Simulationen_US
dc.creatorSamuel-Ojo, Catherine Olubunmien
dc.contributor.authorSamuel-Ojo, Catherine Olubunmien
dc.date.issued2015en
dc.publisherThe University of Arizona.en
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en
dc.description.abstractChronic pain has no cure. It is a lifelong condition presenting a growing concern due to its high occurrence and effects on every facet of life. It cost about $635 billion each year in medical treatment and lost productivity (IOM, 2011). The management of chronic pain using prescription painkiller opioids has increased drastically in the last two decades, leading to a consequential increase in deaths from chronic opioid use. This Plan-Do-Study-Act quality improvement project investigates the problem of the prevalence of opioid prescription using agent-based computational modeling method. The simulation models the interaction of 50 patient-agents with pain self-management messages in an episode of 50 patient iterations (visits) for 10 simulated years. This interaction generates health benefit and risk outcomes represented by wellness data obtained when messages are processed. As the simulation runs, data are dynamically captured and visualized using wellness charts, time series plots, and benefit and risk regression plots. The result of the project provides evidence for research and practice on the process of achieving more impact of programs based on administering pain self-management education to patients with chronic non-cancer pain who are currently on opioid therapy and on the process of customizing interventions that might take advantage of the conditions of behavior change driven by pain self-management messages. The tools and the evidences in this project are highly recommended to nurse practitioners primary care providers involve with providing care to the vulnerable groups of patient with chronic non-cancer pain. These evidences might inform the formation of self-management interventions that might lead to a decline in opioid use and prescription and accelerate the acceptance of self-management practices.en
dc.typetexten
dc.typeElectronic Dissertationen
dc.subjectChronic non-cancer painen
dc.subjectOpioid prescriptionen
dc.subjectPain Self-managementen
dc.subjectPain Self-Management Educationen
dc.subjectSelf-management educationen
dc.subjectNursingen
dc.subjectAgent-based modeling simulationen
thesis.degree.nameD.N.P.en
thesis.degree.leveldoctoralen
thesis.degree.disciplineGraduate Collegeen
thesis.degree.disciplineNursingen
thesis.degree.grantorUniversity of Arizonaen
dc.contributor.advisorShea, Kimberly D.en
dc.contributor.chairShea, Kimberly D.en
dc.contributor.committeememberShea, Kimberly D.en
dc.contributor.committeememberDuBois, Janet C.en
dc.contributor.committeememberMartin-Plank, Lori M.en
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