Scaling Up Science-Based Care for Depression and Unhealthy Alcohol Use in Colombia: An Implementation Science Project

BACKGROUND

Mental disorders are a major cause of the global burden of disease and significantly contribute to disability and death. This challenge is particularly evident in low- and middle-income countries (LMICs), where >85% of the world's population live. Latin America is one region comprising LMICs where the burden of mental disorders is high and the availability of mental health services is low. This is particularly evident in Colombia, a country with a long-standing history of violence and associated mental health problems.

METHODS

This article describes the design of a multisite implementation science project, "Scaling Up Science-Based Mental Health Interventions in Latin America" (also known as the DIADA project), that is being conducted in six primary care systems in Colombia. This project, funded via a cooperative agreement from the National Institute of Mental Health, seeks to implement and assess the impact of a new model for promoting widespread access to mental health care for depression and unhealthy alcohol use within primary care settings and building an infrastructure to support research capacity and sustainability of the new service delivery model in Colombia. This care model centrally harnesses mobile health technology to increase the reach of science-based mental health care for depression and unhealthy alcohol use.

RESULTS

This initiative offers great promise to increase capacity for providing and sustaining evidence-based treatment for depression and unhealthy alcohol use in Colombia.

NEXT STEPS

This project may inform models of care that can extend to other regions of Latin America or other LMICs.

Perspectives on the Implementation of Screening and Treatment for Depression and Alcohol Use Disorder in Primary Care in Colombia

Depression and alcohol use disorder (AUD) greatly contribute to the burden of disease worldwide, and have large impact on Colombia's population. In this study, a qualitative analysis evaluates the implementation of a technology-supported model for screening, decision support, and digital therapy for depression and AUD in Colombian primary care clinics. Patient, provider, and administrator interviews were conducted, exploring attitudes towards depression and AUD, attitudes towards technology, and implementation successes and challenges. Researchers used qualitative methods to analyze interview themes. Despite stigma around depression and AUD, the model improved provider capacity to diagnose and manage patients, helped patients feel supported, and provided useful prevalence data for administrators. Challenges included limited provider time and questions about sustainability. The implementation facilitated the identification, diagnosis, and care of patients with depression and AUD. There is ongoing need to decrease stigma, create stronger networks of mental health professionals, and transition intervention ownership to the healthcare center.

Characterizing the perceived stigma towards mental health in the early implementation of an integrated services model in primary care in Colombia. A qualitative analysis

BACKGROUND

Stigma is a sociocultural barrier to accessing mental health services and prevents individuals with mental health disorders from receiving mental health care. The Ministry of Health and Social Protection of Colombia acknowledges that a great number of people with mental disorders do not seek medical aid due to stigma.

OBJECTIVES

Characterise the perceived stigma towards mental health among the stakeholders involved in the early implementation of the DIADA project [Detección y Atención Integral de Depresión y Abuso de Alcohol en Atención Primaria (Detection and Integrated Care for Depression and Alcohol Use in Primary Care)]. Explore whether the implementation of this model can decrease stigma. Describe the impact of the implementation on the lives of patients and medical practice.

MATERIALS AND METHODS

Eighteen stakeholders (7 patients, 5 physicians and 6 administrative staff) were interviewed and a secondary data analysis of 24 interview transcripts was conducted using a rapid analysis technique.

RESULTS

The main effects of stigma towards mental health disorders included refusing medical attention, ignoring illness, shame and labelling. Half of the stakeholders reported that the implementation of mental health care in primary care could decrease stigma. All of the stakeholders said that the implementation had a positive impact.

CONCLUSIONS

The perceived stigma was characterised as social and aesthetic in nature. Communication and awareness about mental health is improving, which could facilitate access to mental health treatment and strengthen the doctor-patient relationship. Culture is important for understanding stigma towards mental health in the population studied.

Technology-based mental healthcare models: A systematic review of the literature

INTRODUCTION

This systematic review summarises the existing evidence on the implementation of technology-based mental healthcare models in the primary care setting.

METHODS

A systematic search was conducted (MEDLINE, Embase, CENTRAL) in August 2019 and studies were selected according to predefined eligibility criteria. The main outcomes were clinical effectiveness, adherence to primary treatment and cost of implementation.

SELECTION CRITERIA

Studies with an experimental or quasi-experimental design that evaluated the implementation of technology-based mental healthcare models were included.

RESULTS

Five articles met the inclusion criteria. The models included technological devices such as tablets, cellphones and computers, with programs and mobile apps that supported decision-making in the care pathway. These decisions took place at different times, from the universal screening phase to the follow-up of patients with specific conditions. In general, the studies showed a decrease in the reported symptoms. However, there was great heterogeneity in both the health conditions and the outcomes, which hindered a quantitative synthesis. The assessment of risk of bias showed low quality of evidence.

CONCLUSION

There is not enough evidence to support the implementation of a technology-based mental healthcare model. High quality studies that focus on implementation and effectiveness outcomes are needed to evaluate the impact of technology-based mental healthcare models in the primary care setting.