JMIR Nursing
Virtualizing care from hospital to community: Mobile health, telehealth, and digital patient care.
Editor-in-Chief:
Elizabeth Borycki, RN, PhD, FIAHIS, FACMI, FCAHS, Social Dimensions of Health Program Director, Health and Society Program Director, Office of Interdisciplinary Studies; Professor, School of Health Information Science, University of Victoria, Canada
Impact Factor 4.0 CiteScore 5.1
Recent Articles

Diabetes has become a significant global health issue, particularly imposing a deep economic burden on developing countries. Innovative and integrated digital solutions can reduce the impact of diabetes and enhance the quality of care. However, digital solutions have not been utilized before in Myanmar.

Background: Unplanned Extubation(UEX) is a critical indicator of nursing quality.Existing research primarily focuses on pediatric intensive care units (PICUs),with limited data from general pediatric surgery.Currently, research on this project is mainly focused on pediatric intensive care units, and there is a lack of general surgical research data. Therefore, project research should be conducted based on this characteristic.


Each year nursing informatics researchers contribute to nursing and health informatics knowledge. 2024 has emerged as yet another year of significant advances. In this editorial I describe and highlight some of the key trends in nursing informatics research as published in JMIR Nursing in 2024. Artificial intelligence (AI), data science, mHealth, and integrating technology into nursing education and practice remain key research themes in the literature. Nursing informatics publications continue to grow in number. A greater number of AI and data science articles are being published while at the same time mHealth and technology research continues to be conducted in nursing education and practice contexts.

Older adults manage multiple impacts on health, including chronic conditions and adverse external events. Smart homes are positioned to have a positive impact on older adults’ health by allowing (1) new understandings of behavior change so risks associated with external events can be assessed, (2) quantifying of impact of social determinates on health, and (3) designing interventions that respond appropriately to detected behavior changes. Information derived from smart home sensors can provide objective data about behavior changes to support a learning healthcare system. In this paper, we introduce a smart home capable of detecting behavior changes that occur during adverse external events like pandemics and wildfires.

The COVID-19 pandemic placed unprecedented pressure on health care systems worldwide, significantly impacting frontline health care workers, especially nurses. These professionals faced considerable psychological stress from caring for patients with COVID-19 and the fear of spreading the virus to their families. Studies report that more than 60% (132/220) of nurses experience anxiety, depression, and emotional exhaustion, which adversely affect their mental health and the quality of care they provide.

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.