JMIR Nursing

The demand for home health care and nursing visits has steadily increased, requiring significant allocation of resources for wound care. Many home health agencies operate below capacity due to clinician shortages, meeting only 61% to 70% of demand and frequently declining wound care referrals. Implementing artificial intelligence–powered digital wound care solutions (DWCSs) offers an opportunity to enhance wound care programs by improving scalability and effectiveness through better monitoring and risk identification.

Information and Communications Technology can be utilized in telenursing to facilitate remote service delivery, thereby helping mitigate the general global nursing shortage as well as particular applications (e.g., in geographically remote communities). Telenursing can thus bring services closer to end users, offering patient convenience and reduced hospitalization and health system costs, enabling more effective resource allocation.

The healthcare sector faces a projected shortfall of 10 million workers by 2030. AI automation in areas such as patient education and initial therapy screening presents a strategic response to mitigate this shortage and reallocate medical staff to higher-priority tasks. However, current methods of evaluating early-stage healthcare AI chatbots are highly limited due to safety concerns and the amount of time and effort that goes into evaluating them.

The digitalization of health care in Germany holds great potential to improve patient care, resource management, and efficiency. However, strict data protection regulations, fragmented infrastructures, and resistance to change hinder progress. These challenges leave care institutions reliant on outdated paper-based workflows, particularly for patient data transmission, despite the pressing need for efficient tools to support health care professionals amid a nursing shortage and rising demand for care.

This review investigates the relationship between artificial intelligence (AI) use and the role of nurses in patient care. AI exists in health care for clinical decision support, disease management, patient engagement, and operational improvement and will continue to grow in popularity, especially in the nursing field.

This Research Letter discusses the impact of different file formats on ChatGPT-4's performance in the Japanese National Nursing Examination, highlighting the need for standardized reporting protocols to enhance the integration of AI in nursing education and practice.

Professionals in caring disciplines have been pivotal in advancing virtual care, which leverages remote technologies to deliver effective support and services from a distance. Educators in these caring professions are required to teach students the skills and competencies needed to provide high-quality and effective care. As virtual care becomes more integral, educators must equip students in these fields with both interpersonal and technological skills, bridging traditional hands-on learning with digital literacy. However, there is a gap in evidence exploring educators’ perceptions and experiences of teaching caring profession students about virtual caring skills within online environments.

The rising prevalence of urinary incontinence (UI) among older adults, particularly those living in nursing homes (NHs), underscores the need for innovative continence care solutions. The implementation of an unobtrusive sensor system may support nighttime monitoring of nursing home residents' movements and, more specifically, the agitation possibly associated with voiding events.

Globally, the rate at which the aging population and the prevalence of chronic diseases are increasing is remarkable. With declining birth rates and a growing percentage of elderly individuals, the demand for nursing staff is steadily rising. However, the shortage of nursing personnel has been a longstanding issue. In recent years, numerous researchers have advocated implementing nursing robots as a substitute for traditional human labour.

Optimal nurse staffing levels have been shown to impact patients’ prognoses and safety, as well as staff burnout. The predominant method for calculating staffing levels has been Patient-to-Nurse (P/N) ratios and Nursing Hours Per Patient Day (NHPPD). However, both methods fall short in addressing the dynamic nature of staffing needs that often fluctuate throughout the day as patients' clinical status changes, and new patients are admitted or discharged from the unit.

Background: Effective communication is vital in healthcare, especially for nursing students who are the future of healthcare delivery. In Iraq's nursing education landscape, characterized by challenges like resource constraints and infrastructural limitations, understanding communication modalities is crucial.

During the pandemic, health care providers implemented remote patient monitoring (RPM) for patients experiencing COVID-19. RPM is an interaction between health care professionals and patients who are in different locations, in which certain patient functioning parameters are assessed and followed up for a certain duration of time. The implementation of RPM in these patients aimed to reduce the strain on hospitals and primary care.