Literature Collection

OBJECTIVES: The multidisciplinary team approach improves adverse drug reaction (ADR) reporting and management. Our study aims to integrate a pharmacovigilance (PV) and Response Team within the general medicine department to improve ADR reporting and management. MATERIALS AND METHODS: We conducted a prospective cross-sectional study for seven months in four general medicine wards. We proposed a PV and response unit team (PRUT), comprising a nursing student, and a Doctor of Pharmacy (intern). After the team received interventional educational training, we integrated them with the physician and head nurse of each general medicine inpatient ward. We then evaluated the effectiveness of the team in ADR reporting and management using a feedback survey. RESULTS: In this study, comorbidities (30.69%) and polypharmacy (≥5 drugs) (26.25%) were major predisposing factors. Among drug-related problems in 125 patients, inappropriate drug use (28.80%) and unclear dose timing (21.60%) were predominant. Gastrointestinal disorders were common (44.73%), with dose adjustment being the top management strategy (36.84%). Over 71% supported the PRUT for improving patient safety and reducing medication errors, noting high effectiveness in consultation (85.92%) and in reducing the ADR reporting burden (87.32%). There is a statistically significant association between the level of agreement on the effectiveness of PRUT among healthcare professionals (p<0.01). Most healthcare professionals agreed on PRUT's effectiveness without any reports of low agreement levels. CONCLUSION: The PRUT effectively reported and managed ADRs. A multidisciplinary approach improves ADR reporting and management.

Depression is a prevalent mental health disorder that significantly impacts primary care settings. This editorial explores the potential of artificial intelligence (AI)-powered chatbots in managing depression within primary care environments. AI chatbots offer innovative solutions to challenges faced by healthcare providers, including limited appointment times, delayed access to specialists, and stigma associated with mental health issues. These digital tools provide continuous support, personalized interactions, and early symptom detection, potentially improving accessibility and outcomes in depression management. The integration of AI chatbots in primary care presents opportunities for round-the-clock patient support, personalized interventions, and the reduction of mental health stigma. However, challenges persist, including concerns about assessment accuracy, data privacy, and integration with existing healthcare systems. Successful implementation requires systematic approaches, stakeholder engagement, and comprehensive training for healthcare providers. Ethical considerations, such as ensuring informed consent, managing algorithmic biases, and maintaining the human element in care, are crucial for responsible deployment. As AI technology evolves, future directions may include enhanced natural language processing, multimodal integration, and AI-augmented clinical decision support. This editorial emphasizes the need for a balanced approach that leverages the potential of AI while acknowledging its limitations and the irreplaceable value of human clinical judgment in depression management within primary care settings.

INTRODUCTION: Asthma is one of the most common chronic respiratory diseases globally. Despite national and international asthma care guidelines, gaps persist in primary care. Knowledge translation (KT) electronic tools (eTools) exist aiming to address these gaps, but their impact on practice patterns and patient outcomes is variable. We aimed to conduct a nonsystematic review of the literature for key asthma care gaps and identify limitations and future directions of KT eTools optimised for use in electronic medical records (EMRs). METHODS: The database OVID Medline was searched (1999-2024) using keywords such as asthma, KT, primary healthcare and EMRs. Primary research articles, systematic reviews and published international/national guidelines were included. Findings were interpreted within the knowledge-to-action framework. RESULTS: Key asthma care gaps in primary care include under-recognition of suboptimal control, underutilisation of pulmonary function tests, barriers to care delivery, provider attitudes/beliefs, limited access to asthma education and referral to asthma specialists. Various KT eTools have been validated, many with optimisation for use in EMRs. KT eTools within EMRs have been a recent focus, including asthma management systems, decision support algorithms, data standards initiatives and asthma case definition validation for EMRs. CONCLUSIONS: The knowledge-to-action cycle is a valuable framework for developing and implementing novel KT tools. Future research should integrate end-users into the process of KT tool development to improve the perceived utility of these tools. Additionally, the priorities of primary care physicians should be considered in future KT tool research to improve end-user uptake and overall asthma management practices.

BACKGROUND: Chronic diseases that drive morbidity, mortality, and health care costs are largely influenced by human behavior. Behavioral health conditions such as anxiety, depression, and substance use disorders can often be effectively managed. The majority of patients in need of behavioral health care are seen in primary care, which often has difficulty responding. Some primary care practices are providing integrated behavioral health care (IBH), where primary care and behavioral health providers work together, in one location, using a team-based approach. Research suggests there may be an association between IBH and improved patient outcomes. However, it is often difficult for practices to achieve high levels of integration. The Integrating Behavioral Health and Primary Care study responds to this need by testing the effectiveness of a comprehensive practice-level intervention designed to improve outcomes in patients with multiple chronic medical and behavioral health conditions by increasing the practice's degree of behavioral health integration. METHODS: Forty-five primary care practices, with existing onsite behavioral health care, will be recruited for this study. Forty-three practices will be randomized to the intervention or usual care arm, while 2 practices will be considered "Vanguard" (pilot) practices for developing the intervention. The intervention is a 24-month supported practice change process including an online curriculum, a practice redesign and implementation workbook, remote quality improvement coaching services, and an online learning community. Each practice's degree of behavioral health integration will be measured using the Practice Integration Profile. Approximately 75 patients with both chronic medical and behavioral health conditions from each practice will be asked to complete a series of surveys to measure patient-centered outcomes. Change in practice degree of behavioral health integration and patient-centered outcomes will be compared between the two groups. Practice-level case studies will be conducted to better understand the contextual factors influencing integration. DISCUSSION: As primary care practices are encouraged to provide IBH services, evidence-based interventions to increase practice integration will be needed. This study will demonstrate the effectiveness of one such intervention in a pragmatic, real-world setting. TRIAL REGISTRATION: ClinicalTrials.gov NCT02868983 . Registered on August 16, 2016.