Date of Award:

5-2014

Document Type:

Thesis

Degree Name:

Master of Arts (MA)

Department:

Psychology

Committee Chair(s)

M. Scott DeBerard

Committee

M. Scott DeBerard

Committee

Edward M. Heath

Committee

JoAnn T. Tschanz

Abstract

Back pain is one of the most expensive medical conditions to treat. There has been a great deal of research showing that back pain surgery is expensive, but less is known about the costs of less-invasive spine procedures such as radiofrequency neurotomy. Radiofrequency neurotomy is used to treat facet joint pain and typically offers temporary pain relief by coagulating the affected nerve with radiofrequency waves to block pain messages from reaching the brain. This study aimed to document the costs of radiofrequency neurotomy in a group of participants who received the procedure through the Workers’ Compensation Fund of Utah (WCFU). Another goal of the study was to determine if any biopsychosocial variables of participants predicted costs. Biopsychosocial variables include biological (e.g., age), psychological (e.g., depression), and social (e.g., hiring a lawyer) characteristics about participants. Costs and characteristics were collected from participant medical records.

Compensation and medical costs were collected; compensation costs were wage payouts as a result of an on-the-job injury, and medical costs were direct medical costs. Both compensation and medical costs were substantial and similar to other more invasive procedures. Furthermore, three biopsychosocial characteristics predicted high costs. A high number of prior back and neck surgery and lawyer involvement predicted high compensation costs. Those same variables plus history of depression predicted high medical costs.

This was the first known study to document medical and compensation costs associated with spinal radiofrequency neurotomy. The findings add to the line of research suggesting that a biopsychosocial framework can be used to predict costs in spine care. Discovering participant characteristics that may predict high costs can inform policy-level decisions for insurers, and can be used by medical providers to influence patient care decisions. More research on the presurgical variables may lead to interventions at the patient level that can reduce high cost outcomes which could benefit both patients and payers.

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