Examination of objective methods of assessment of treatment response in in-patient depression

Severe depression may result in admission to hospital because of the severity of functional impairment or because of risk of suicide. Admission to an in-patient unit represents the most severe form of depression and results in separation from whanau and other sources of support. Rapid response to treatment is important. The in-patient environment represents a situation in which more intensive monitoring should be possible but this does not always occur because of the busyness of the ward and because methods to monitor response to treatment have not been well researched. Indeed research in busy in-patient wards is rare and nursing staff are not usually exposed to research. In Canterbury, approximately 190 people per year are admitted to an in-patient unit because of depression. Following discharge from hospital, relapse and suicide are common. In Canterbury, following discharge from hospital, 40% of patients are re-admitted within 1 year. Evidence suggests that patients admitted with depression have poor employment outcomes and poor general functioning. Patients are also often discharged taking high doses of combinations of medications, something which may be avoided if indications of early response can be measured early in treatment.
The proposed inpatient study aims to identify simple, objective, adjunctive measures to support clinical assessment of treatment response in the inpatient setting. The provision of better tools for use by nurses and other clinical staff would provide facility for earlier detection of improvement (or lack of it) in mood disorder. This would in turn support decision making around the need for earlier intervention, for example change of treatment, augmentation, or continuance. Improved depression severity assessment tools directly benefit the patient (quicker recovery), the nurses (by empowering their assessment and hence improving morale), and the treating institution (shorter admission time, cost savings, and greater confidence in clinical treatment decision making).