Understanding clinical risk decision making regarding development of depression during interferon-alpha treatment for hepatitis-C: a qualitative interview study

Background: Hepatitis C virus (HCV) affects 170 million worldwide. Currently, around 30% of patients receiving interferon-alpha (IFN-α) treatment for HCV experience clinically significant depression. Effective and timely detection of depression is crucial to ensuring appropriate treatment and support. However, little is known about how clinical nurse specialists identify patients at risk of developing interferon-alpha-induced depression, and monitor those receiving antiviral treatment for the occurrence of depression.

Objective: This study aimed to gain an in-depth understanding of staff experience of, and attitudes towards, the identification and monitoring of interferon-alpha-induced-depression and the decision-making process concerning the use of liaison psychiatry and other clinical services.

Design: A qualitative interview study was conducted among clinical staff involved in the care of patients with hepatitis C, using the perspective of naturalistic decision making.

Settings: Outpatient liver clinics in three large teaching hospitals in South London, the United Kingdom.

Participants: All clinical nurse specialists from the three outpatient liver clinics were included. All were involved directly in the care of patients receiving interferon-alpha treatment and had at least one year experience (mean 6.4 years, range 1-11 years) in this field.

Methods: Semi-structured face-to-face interviews were conducted between 2010 and 2011. Data collection and analysis were carried out iteratively to ensure the reliability of the analysis using the constant comparison method.

Results: Staff used verbal and non-verbal cues when assessing risks of patients developing depression before and during IFN-α treatment. Major sources of uncertainty were patient engagement and familiarity, referrals to psychiatrists, language barriers, and distinguishing between psychological and physical symptoms. Good rapport with patients and good communication among multidisciplinary professional groups were key strategies identified to reduce uncertainty.

Conclusion: Current methods of identifying vulnerable patients rely on the availability of clinical experts and good communication within a multidisciplinary team. Detection and management of depression in this population is complex, however, various strategies are employed by nurses to overcome difficulties when making decisions regarding patient welfare. Current clinical practices should be taken into account when developing new tools and methods.