The DIADA project: A technology-based model of care for depression and risky alcohol use in primary care centres in Colombia.

introductionPeople with mental health conditions frequently attend primary care centers, but these conditions are underdiagnosed and undertreated. The objective of this paper is to describe the model and the findings of the implementation of a technology-based model of care for depression and unhealthy alcohol use in primary care centers in Colombia.

methodsBetween February 2018 and March 2020, we implemented a technology-based model of care for depression and unhealthy alcohol use, following a modified stepped wedge methodology, in six urban and rural primary care centers in Colombia. The model included a series of steps aimed at screening patients attending medical appointments with general practitioners and supporting the diagnosis and treatment given by the general practitioner. We describe the model, its implementation and the characteristics of the screened and assessed patients.

resultsDuring the implementation period, we conducted 22,354 screenings among 16,188 patients. The observed rate of general practitioner (GP)-confirmed depression diagnosis was 10.1% and of GP-confirmed diagnosis of unhealthy alcohol use was 1.3%. Patients with a depression diagnosis were primarily middle-aged women, while patients with unhealthy alcohol use were mainly young adult men. DISCUSSION: The provision of training and technology-based strategies to screen patients and support the decision-making of GPs during the medical appointment enhanced the diagnosis and care provision of patients with depression and unhealthy alcohol use. However, time constraints, as well as structural and cultural barriers, were challenges for the implementation of the model, and the model should take into account local values, policies and resources to guarantee its long-term sustainability. As such, the long-term sustainability of the model will depend on the alignment of different stakeholders, including decision-makers, institutions, insurers, GPs, patients and communities, to reduce the amount of patients seeking medical care whose mental health conditions remain undetected, and therefore untreated, and to ensure an appropriate response to the demand for mental healthcare that was revealed by the implementation of our model.