Perceived access to general and mental healthcare in primary care in Colombia during COVID-19: A cross-sectional study.

Introduction: The COVID-19 pandemic has had an impact both in general and mental healthcare, challenged the health systems worldwide, and affected their capacity to deliver essential health services. We aimed to describe perceived changes in ease of access to general and mental healthcare among patients with a diagnosis of depression and/or unhealthy alcohol use in Colombia. Methods: This study is embedded in the DIADA project, a multicenter implementation research study aimed at evaluating the integration of mental healthcare in primary care in Colombia. Between November 2020 and August 2021, we conducted a COVID-19 pandemic impact assessment in a cohort of participants with newly diagnosed depression and/or unhealthy alcohol use part of DIADA project. We assessed the ease of access and factors related to perceived ease of access to general or mental healthcare, during the COVID-19 pandemic. Results: 836 participants completed the COVID-19 pandemic impact assessment. About 30% of participants considered their mental health to be worse during the pandemic and 84.3% perceived access to general healthcare to be worse during the pandemic. Most of participants (85.8%) were unable to assess access to mental health services, but a significant proportion considered it to be worse. Experiencing worse ease of access to general healthcare was more frequent among women, patients with diagnosis of depression, and patients with comorbidities. Experiencing worse ease of access to mental healthcare was more frequent among patients aged between 30 and 49.9 years, from socioeconomic status between 4 and 6, affiliated to the contributive social security regime, attending urban study sites, and those who perceived their mental health was worse during the pandemic. Discussion: Despite the overall perception of worse mental health during the pandemic, the use of mental healthcare was low compared to general healthcare. Ease of access was perceived to be worse compared to pre-pandemic. Ease of access and access were affected by geographical study site, socioeconomic status, age and gender. Our findings highlight the need for improved communication between patients and institutions, tailored strategies to adapt the healthcare provision to patients' characteristics, and continued efforts to strengthen the role of mental healthcare provision in primary care.

A characterisation of social media users within the primary care system in Colombia and predictors of their social media use to understand their health.

INTRODUCTION: Social media use is growing in Latin America and is increasingly being used in innovative ways. This study sought to characterise the profile of social media users, among primary care patients in Colombia, and to assess predictors of their use of social media to search for health and mental health information (searching behaviour). METHODS: As part of a larger scale-up study, we surveyed 1580 patients across six primary care sites in Colombia about their social media use. We used chi-square and Student's t-tests to assess associations between demographic variables, social media use and searching behaviour, and a Chi-square Automatic Interaction Detector (CHAID) analysis to determine predictors of searching behaviour. RESULTS: In total, 44.4% of respondents reported that they were social media users. Of these, 35.7% used social media to search for health-related information and 6.6% used it to search for mental health-related information. While the profile of individuals who used social media to search for health-related information was similar to that of general social media users (the highest use was among women living in urban areas), the presence of mental health symptoms was a more important predictor of using social media to search for mental health-related information than demographic variables. Individuals with moderate-severe symptoms of anxiety reported a significantly higher percentage of searching than individuals without symptoms (12.5% vs. 5.2%). CONCLUSIONS: Given that some individuals with mental health disorders turn to social media to understand their illness, social media could be a successful medium for delivering mental health interventions in Colombia.

Barriers and facilitators to the diagnosis and treatment of depression in primary care in Colombia: Perspectives of providers, healthcare administrators, patients and community representatives.

INTRODUCTION: Depression represents a major disease burden in Colombia. To better understand opportunities to improve access to mental healthcare in Colombia, a research team at Javeriana University conducted formative qualitative research to explore stakeholders' experiences with the integration of mental healthcare into the primary care system. METHODS: The research team conducted 16 focus groups and 4 in-depth interviews with patients, providers, health administrators and representatives of community organisations at five primary care clinics in Colombia, and used thematic analysis to study the data. RESULTS: Themes were organised into barriers and facilitators at the level of patients, providers, organisations and facilities. Barriers to the treatment of depression included stigma, lack of mental health literacy at the patient and provider level, weak links between care levels, and continued need for mental health prioritization at the national level. Facilitators to the management of depression in primary care included patient support systems, strong patient-provider relationships, the targeting of depression interventions and national depression guidelines. DISCUSSION: This study elucidates the barriers to depression care in Colombia, and highlights action items for further integrating depression care into the primary care setting.

Perspectives, Experiences, and Practices in the Use of Digital Information Technologies in the Management of Depression and Alcohol Use Disorder in Health Care Systems in Colombia.

Digital information technologies are increasingly used in the treatment of mental health disorders. Through this qualitative study, researchers illuminated perspectives, experiences, and practices among diverse stakeholders in the use of digital information technologies in the management of depression and alcohol use disorders in Colombia. In-depth interviews and focus groups were conducted in five primary care institutions across Colombia. Thematic analysis was used to analyze the data. The use of technology in the treatment of mental health disorders can facilitate the evaluation and diagnosis, treatment, and promotion and prevention of mental health disorders, as well as multiple nonmental health applications in the primary care setting. Potential barriers to the use of technology in this setting include challenges of digital literacy, access to technology, confidentiality, and financing. This study can inform the implementation of digital information technologies in the care of depression and problematic alcohol use within health care systems in Colombia.

Assessing the Integration of Behavioral Health Services in Primary Care in Colombia.

Integration of behavioral health care into primary care can improve health and economic outcomes. This study adapted the Behavioral Health Integration in Medical Care (BHIMC) index to the Colombian context and assessed the baseline level of behavioral health integration in a sample of primary care organizations. The BHIMC was able to detect the capacity to provide integrated behavioral care in Colombian settings. Results indicate a minimal to partial integration level across all sites, and that it is possible to measure the degree of integrated care capacity and identify improvement areas for better behavioral health care provision.

Automated annotation and classification of BI-RADS assessment from radiology reports.

The Breast Imaging Reporting and Data System (BI-RADS) was developed to reduce variation in the descriptions of findings. Manual analysis of breast radiology report data is challenging but is necessary for clinical and healthcare quality assurance activities. The objective of this study is to develop a natural language processing (NLP) system for automated BI-RADS categories extraction from breast radiology reports. We evaluated an existing rule-based NLP algorithm, and then we developed and evaluated our own method using a supervised machine learning approach. We divided the BI-RADS category extraction task into two specific tasks: (1) annotation of all BI-RADS category values within a report, (2) classification of the laterality of each BI-RADS category value. We used one algorithm for task 1 and evaluated three algorithms for task 2. Across all evaluations and model training, we used a total of 2159 radiology reports from 18 hospitals, from 2003 to 2015. Performance with the existing rule-based algorithm was not satisfactory. Conditional random fields showed a high performance for task 1 with an F-1 measure of 0.95. Rules from partial decision trees (PART) algorithm showed the best performance across classes for task 2 with a weighted F-1 measure of 0.91 for BIRADS 0-6, and 0.93 for BIRADS 3-5. Classification performance by class showed that performance improved for all classes from Naïve Bayes to Support Vector Machine (SVM), and also from SVM to PART. Our system is able to annotate and classify all BI-RADS mentions present in a single radiology report and can serve as the foundation for future studies that will leverage automated BI-RADS annotation, to provide feedback to radiologists as part of a learning health system loop.