Opioid use behaviors, mental health and pain--development of a typology of chronic pain patients

Abstract

Background: The intersection of pain, addiction and mental health has not been adequately described. We describe the roles of these three conditions in a chronic pain patient population using opioid analgesics. Aims were to improve our understanding of this population as well as to explore ways of identifying different types of patients.

Methods: We conducted a retrospective cohort study in a large integrated group medical practice in Washington State with persons using opioids chronically (n=704). Patient classes were derived with latent class analysis using factors representing DSM-IV opioid abuse and dependence, opioid misuse, pain, anxiety and depression. Regression analyses explored the utility of automated and interview data to distinguish the empirically derived patient groups.

Results: Three classes were identified: a Typical group, the substantial majority that had persistent, moderate mental health and pain symptoms; an Addictive Behaviors group with elevated mental health symptoms and opioid problems, but pain similar to the Typical class; and a Pain Dysfunction class with significantly higher pain interference as well as elevated mental health and opioid problems. Prescribed average daily dose of opioids was three times higher for those in the two atypical groups and was strongly associated with class membership after adjusting for other variables.

Conclusion: We describe three distinct types of patient classes as well as data elements that could help identify the two atypical types. Further research is needed to confirm these findings and determine the utility of this approach in other clinical settings.

Figure 1

Diagram of study aims, Aim 1 to develop a patient typology, Aim 2 to identify patient types.

Figure 2

Factor scores by most likely class: Typical (n=580), Addictive Behaviors (n=82) and Pain Dysfunction (n=42), statistical tests of differences in factor scores by most likely class and effect sizes of differences in factor scores by most likely class.