ArticleClinical & experimental ophthalmology
Barriers and Enablers Influencing the Implementation of Artificial Intelligence for Diabetic Retinopathy Screening in Clinical Practice: A Scoping Review.
Article in Clinical & experimental ophthalmology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Using the Normalization Process Theory to study facilitators and barriers to sustainable implementation of artificial intelligence-based diabetic retinopathy screening in Rwanda.Dialogues in health · 2026Article
- Applications of Tailored Mesoporous Silicate Nanomaterials in Regenerative Medicine and Theranostics.International journal of molecular sciences · 2025Review
- The augmentative role of artificial intelligence in medical education and healthcare practices: an integrative review.Sudanese journal of paediatrics · 2025Review
- Barriers and Enablers Influencing the Implementation of Artificial Intelligence for Diabetic Retinopathy Screening in Clinical Practice: A Scoping Review.Clinical & experimental ophthalmologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDiabetic retinopathy is a leading cause of preventable blindness worldwide. Meanwhile, artificial intelligence is rapidly growing in clinical utility within medicine. This scoping review aims to identify and summarise existing literature on the barriers and enablers of clinical applications of artificial intelligence systems for the screening of diabetic retinopathy.
methodsUtilising a systematic approach and the PRISMA-ScR protocol for conducting scoping reviews, searches were performed in MEDLINE, Embase, Emcare, Cochrane, CINAHL, ProQuest, Scopus and grey literature (Australian Indigenous Health InfoNet). Two reviewers independently reviewed the records. A third reviewer provided consensus. Data extraction and synthesis in narrative form ensued.
resultsA total of 3844 articles were screened, of which 18 were selected. Published between 2018 and 2023, the selected studies varied in study design and were conducted across 10 countries. Several barriers and enablers were identified and categorised into four domains: healthcare system, healthcare professional, healthcare user and information technology. Within the healthcare system, clinical efficiency was reported on most frequently. Concerning the healthcare professional, education was most frequently discussed. Within healthcare user, studies most frequently identified factors pertaining to patient outcomes, while diagnostic performance was most frequently explored under the information technology domain.
conclusionsAs evidence for the efficacy of artificial intelligence for diabetic retinopathy screening grows, barriers to and enablers for its uptake in clinical practice are paramount considerations. Translating the knowledge of systems, provider, consumer and technological factors informs clinical strategies, ultimately facilitating the sustainable and effective implementation of this novel technology for screening practices.
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Identifiers
What Socratic holds
Registered trials
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 Socratic graph.