# Artificial Intelligence–Enhanced Wound Care to Improve Access, Efficacy, and Equity in Wound Care for Older Adults in Rural and Remote Regions of Canada

**Authors:** Courtney Genge, Basnama Ayaz, Shannon Freeman, Heba Tallah Mohammed, Robert D J Fraser, Ibukun-Oluwa Omolade Abejirinde, Deirdre O’Sullivan-Drombolis, Rebecca Brookham

PMC · DOI: 10.2196/85644 · JMIR Nursing · 2026-03-30

## TL;DR

This paper discusses using AI-powered wound care technology to improve access and outcomes for older adults in rural Canada.

## Contribution

The paper advocates for expanding AI-driven digital wound care technology to address inequities in rural and remote regions.

## Key findings

- AI can support clinical decision-making and extend access to care in rural communities.
- Digital wound care technology improves accuracy, communication, and resource allocation.
- Initial implementations in Ontario show promise for reducing disparities in wound care outcomes.

## Abstract

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.

## Full-text entities

- **Diseases:** erythema (MESH:D004890), PAST (MESH:D003668), cancer (MESH:D009369), necrotic tissue (MESH:D017695), venous ulcers (MESH:D014647), diabetic foot ulcer (MESH:D017719), peripheral arterial disease (MESH:D058729), infection (MESH:D007239), NSWOC (MESH:D014947), death (MESH:D003643), pain (MESH:D010146), diabetes (MESH:D003920), physical and mental trauma (MESH:D000070617)
- **Chemicals:** DWCT (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]
- **Cell lines:** SWAN — Ginglymostoma cirratum (Nurse shark), Spontaneously immortalized cell line (CVCL_B7QE)

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC13035484/full.md

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC13035484/full.md

## References

60 references — full list in the complete paper: https://tomesphere.com/paper/PMC13035484/full.md

---
Source: https://tomesphere.com/paper/PMC13035484