The influence of patient's sex, race and depression on clinician pain treatment decisions.

Hirsh AT, Hollingshead NA, Bair MJ, Matthias MS, Wu J, Kroenke K. The influence of patient's sex, race and depression on clinician pain treatment decisions. European journal of pain (London, England). 2013 Nov 1; 17(10):1569-79.

Related HSR&D Project(s)

• CDA 10-034 – Identifying Strategies to Improve Communication in Chronic Pain Care

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Abstract:

BACKGROUND: Pain treatments often vary across patients' demographic and mental health characteristics. Most research on this topic has been observational, has focused on opioid therapy exclusively and has not examined individual differences in clinician decision making. The current study examined the influence of patient's sex, race and depression on clinicians' chronic pain treatment decisions. METHODS: We used virtual human technology and lens model methodology to enhance study realism and facilitate a richer understanding of treatment decisions. Clinicians and trainees (n? = 100) made treatment decisions (opioid, antidepressant, pain specialty referral, mental health referral) for 16 computer-simulated patients with chronic low back pain. Patients' sex, race and depression status were manipulated across vignettes (image and text). RESULTS: Individual- and group-level analyses indicated that patient's depression status had the strongest and most consistent influence on treatment decisions. Although less influential overall, patient's sex and race were significantly influential for a subset of participants. Furthermore, the results indicated that participants who were influenced by patient's race had less experience in treating chronic pain than those who were not influenced by patient's race [t(11.59)? = 4.75; p? = 0.001; d? = 1.20]. CONCLUSIONS: The results of this study indicated considerable variability in participants' chronic pain treatment decisions. These data suggest that interventions to reduce variability in treatment decision making and improve pain care should be individually tailored according to clinicians' decision profiles.