JMIR Nursing

Substance use disorders are chronic conditions with significant personal and social consequences. Nursing care plays a key role in outpatient and community-based rehabilitation programs, yet patients’ perspectives on this role remain underexplored.

Wound care is an increasing global challenge, with older adults among those most affected. As populations age, the demand for effective and efficient wound care increases. Over the years, various wound assessment and care techniques have been developed, including digital wound care technology (DWCT), which uses innovative artificial intelligence (AI). Many older adults, especially those living in rural and remote areas, face significant barriers in obtaining timely and effective wound care, leading to poorer health outcomes and increased health care costs related to wound care. These challenges underscore the urgent need to implement wound care models that equitably improve access to care and enhance clinical outcomes, particularly for older adults, to promote healthy aging and age-in-place. Based on evidence from the literature and the initial implementation of a DWCT in 2 community health systems in Ontario, this viewpoint paper encourages clinicians and health care leaders to embrace and expand the implementation of an AI-driven DWCT to address inequities in access to high-quality, timely care. The experiences from these implementations indicate that the use of AI can support clinical decision-making and extend access to care for individuals in rural and remote communities in Canada. By leveraging DWCT powered by AI, health care providers can enhance the accuracy and consistency of wound assessments, improve communication, streamline care processes, and more effectively allocate resources, ultimately aiming to reduce disparities in wound care outcomes.

In the past decade, the use of health technologies, such as telemonitoring, video consultations, and patient portals, has increased. However, it remains unclear how these technologies have influenced nurse-patient communication. Additionally, little is known about the role nurses play in recognizing and supporting limited (digital) health literacy patients.

Global nursing shortages require innovative care delivery models. Virtual nursing is a cutting-edge model being explored.

Aging populations and rising chronic illness prevalences are increasing demands for nursing care, while staff shortages threaten care quality. Robotics offer potential support, yet usability, workflow integration, and user acceptance remain major barriers.

Clinical decision support (CDS) tools embedded in electronic health records in the form of integrated clinical prediction rules provide a potentially effective intervention to reduce inappropriate antibiotic prescribing for acute respiratory infections. However, their effectiveness has been limited by workflow barriers and low adoption by health care providers. Nurses are well positioned to implement evidence-based protocols using CDS tools. In a multicenter randomized controlled trial, a nurse-led implementation strategy for acute respiratory infection integrated clinical prediction rules was evaluated for use in primary care and urgent care settings.

The integration of digital health technologies (DHTs) in clinical practice is accelerating, creating a need for nursing students to develop digital competencies aligned with professional expectations. In Quebec, curricular reforms aim to enhance digital health literacy, but data are limited on students’ preparedness.

Large language models (LLMs) have shown promising results on Japanese national medical and nursing examinations. However, no study has evaluated LLM performance on the Japanese Public Health Nurse National Examination, which requires specialized knowledge in community health and public health nursing practice.

Effective interprofessional collaboration (IPC) in patient discharge planning is essential for ensuring continuity of care, improving patient outcomes, and strengthening coordination among healthcare professionals. Nurses often serve as primary coordinators due to their continuous engagement in patient care. However, the implementation of IPC continues to face barriers at the individual, team, and organizational levels. Many hospitals have adopted digital tools, such as Integrated Patient Progress Notes (IPPN), to facilitate information sharing. Nevertheless, the use of these tools to support IPC remains suboptimal and has been insufficiently explored, particularly within the Indonesian digital health context.

The majority of diabetic wound patients live in the community, facing challenges like a shortage of nurses, limited access to healthcare, and insufficient resources. Strategies such as specialist networks, patient monitoring, and online care platforms are crucial to improving diabetic wound management in the community.

Patients undergoing cancer treatment experience significant symptom burden. The standard process of symptom management includes patient reporting and clinical response following symptom escalation. Emerging predictive symptom models utilize AI components of machine learning and deep learning to identify the risk of symptom deterioration, facilitating earlier intervention to prevent downstream effects. However, integrating predictive symptom models into clinical practice will require oncology nurses to adopt innovative approaches.