Evidence map›Paper›PMID 41911415›Full record

ArticleJMIR nursing2026

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

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

Abstract read
In one paragraph

Article in JMIR nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Courtney GengeAging in Place Challenge Program, National Research Council Canada, 1200 Montréal Rd, Gloucester, Ottawa, ON, K1A 0R6, Canada, 1 2898861656.ORCID 0000-0001-9181-6336
Basnama AyazDalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-1385-3048
Shannon FreemanSchool of Nursing, University of Northern British Columbia, Prince George, BC, Canada.ORCID 0000-0002-8129-6696
Heba Tallah MohammedSwift Medical, Toronto, ON, Canada.ORCID 0000-0002-0848-8384
Robert D J FraserSwift Medical, Toronto, ON, Canada.ORCID 0000-0003-2279-4203
Ibukun-Oluwa Omolade AbejirindeDalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-0139-0541
Deirdre O'Sullivan-DrombolisGiishkaandago'Ikwe Health Services, Fort Frances, ON, Canada.ORCID 0009-0004-7191-5811
Rebecca BrookhamBrightshores Health System, Owen Sound, ON, Canada.ORCID 0009-0001-8449-484X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unlabelled: 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. .

Indexed as

Artificial IntelligenceHealth Services AccessibilityWounds and InjuriesAgedCanadaHumansOntarioRural PopulationAIartificial intelligenceequitywound care

Identifiers

PMID41911415
PMCPMC13035484

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.