Target-D: Protocol for a randomised trial of a clinical prediction tool for targeting depression care

Problem

About a quarter of primary health care patients have depressive symptoms, but this is a heterogeneous group spanning mild symptoms which may spontaneously remit, to severe symptoms needing complex treatment approaches. There is no systematic approach to assist GPs in targeting depression management to individual severity and function.

Approach

We designed an individually randomised controlled trial to determine if using a clinical prediction tool to triage individuals with depressive symptoms into tailored management plans is efficacious at reducing depression symptoms and improving cost-effectiveness of depression care at 3 and 12 months, compared to usual care. 570 patients (285 in each arm) aged 18-65 be recruited from primary care practice waiting rooms in Victoria, Australia. Eligibility criteria include having current depressive symptoms, being able to speak and read English, not currently receiving psychological therapy, not currently taking antipsychotics, and having had no change to antidepressant medication for 3 or more months. All participants will complete a clinical prediction tool (CPT) on a purpose built website. The CPT uses a novel algorithm to assess individual risk for persistent depressive symptoms and then allocates the individual to current best evidence treatment. Only intervention arm participants receive this treatment recommendation.

Findings

The primary outcome measure is depression severity measured on the Patient Health Questionnaire-9 (PHQ-9). Secondary outcomes include cost-efficacy, quality of life, anxiety, self-efficacy, and health service use at 3 and 12 months.

Consequences

If the Target-D model for depression management is efficacious and cost-effective, implementation into practice could reduce unnecessary treatment burden and improve allocation of treatment resources.