Trial reportBMJ open2026
Exploring patient and NHS staff acceptability of artificial intelligence-supported surgical wound monitoring within the WISDOM feasibility study: a multi-centre qualitative interview study.
Trial report in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06475703 (Wound Imaging Software and Digital platfOrM to Detect and Prioritise Non-healing Surgical Wounds), which is not on this map. Not yet cited in PubMed.
What it found
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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.
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.
Wound Imaging Software and Digital platfOrM to Detect and Prioritise Non-healing Surgical Wounds (WISDOM)
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveArtificial intelligence (AI) is beginning to be used within digital surgical wound monitoring to facilitate implementation at scale. AI acceptability is essential to its success. This study aimed to explore patient and staff acceptability of an AI-based digital surgical wound monitoring platform.
designQualitative interviews
settingTwo hospitals performing cardiac surgery in England.
participants20 patients undergoing cardiac surgery and 10 clinical staff participating in a randomised feasibility trial of surgical wound monitoring with AI.
interventionsSemi-structured interviews were conducted focusing on participants' experiences or perceptions of AI-based digital surgical wound monitoring. Data were analysed, guided by the theoretical framework of acceptability. PRIMARY MEASURE: Patient and staff acceptability of AI within surgical wound monitoring.
resultsPatients and staff were supportive of the use of AI within surgical wound monitoring and felt safety was improved, access was increased and efficiency was improved. AI monitoring was perceived to allow the early detection and treatment of surgical wound complications and facilitate the implementation of monitoring at scale for all patients. Some participants were concerned about data security risks, staff over-reliance on AI and the loss of human interaction.
conclusionAI-supported digital surgical wound monitoring appeared acceptable to participants within this feasibility study. Further research is needed to evaluate implementation in broader settings. TRIAL REGISTRATION NUMBER: ISRCTN16900119 and NCT06475703.
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