{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T05:55:17Z","timestamp":1781502917667,"version":"3.54.1"},"reference-count":51,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T00:00:00Z","timestamp":1781481600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Digit. Health"],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Chronic, hard-to-heal, wounds such as diabetes-related foot ulcers, venous leg ulcers, and pressure injuries, represent a growing global burden, contributing to high morbidity, and increased healthcare costs and demands on clinical capacity. These challenges are amplified in rural and remote settings, where limited resources and availability of services, workforce shortages, and geographical barriers restrict access to specialised wound care. Artificial intelligence (AI)-enabled tools offer potential to enhance wound assessment, standardise documentation, and expand access to wound specialists. However, their real-world implementation in rural environments remains under-evaluated, particularly regarding contextual factors that influence adoption, sustainability, and equitable impact.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This study aimed to develop an evaluation framework to guide the implementation of Swift Medical's technology across Brightshores, a rural multi-site health system. A literature scan was conducted to identify key performance indicators related to wound care experience and outcomes, which were refined through ongoing implementation partner meetings. To supplement these findings, semi-structured interviews were conducted with frontline staff (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20092) and senior leaders (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20094), focusing on alignment with organizational priorities, anticipated impacts on clinical practice, and potential challenges related to scaling and sustaining the technology.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Findings from the literature scan, interviews, and implementation meetings were triangulated to identify core value propositions and priority outcomes for evaluation. The literature scan provided a foundational set of validated metrics. Interview findings revealed contextual insights regarding technology use in rural care settings, in which three key themes emerged: (1) expectations of the wound care technology; (2) considerations for implementation; and (3) potential barriers to adoption and implementation. Implementation meetings supported feasibility assessment and refinement of indicators within the implementation context. These insights informed the development of a Monitoring and Evaluation framework grounded in the Quintuple Aim, integrating process, outcome, and contextual indicators that reflect the realities of rural health system implementation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>By grounding evaluation design in the lived experiences and decision-making needs of those closest to implementation, this work demonstrates how context-sensitive evaluation frameworks can strengthen digital health decision making in rural systems. The findings offer practical guidance for health organizations considering the adoption, sustainability, and scale-up of AI-enabled wound care technologies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fdgth.2026.1774616","type":"journal-article","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T05:36:53Z","timestamp":1781501813000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Monitoring and evaluation of an artificial intelligence-enhanced wound care intervention in a rural health network: defining stakeholder expectations and shared priorities"],"prefix":"10.3389","volume":"8","author":[{"given":"Ibukun-Oluwa Omolade","family":"Abejirinde","sequence":"first","affiliation":[{"name":"Institute for Better Health, Trillium Health Partners","place":["Mississauga, Ontario, Canada"]},{"name":"Dalla Lana School of Public Health, University of Toronto","place":["Toronto, Ontario, 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