ArticleDigital health
An automated, web-based triage tool may optimise referral pathways in elective orthopaedic surgery: A proof-of-concept study.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- [Use of artificial intelligence for next-gen anamnesis and communication in orthopedics & trauma surgery : From chatbots to ambient intelligence].Orthopadie (Heidelberg, Germany) · 2026Review
- Digitized Precision Corrective Osteotomy for Treating Knee Joint Deformities: Current Evidence and Future Perspectives.Orthopaedic surgery · 2025Review
- A radiographic artificial intelligence tool to identify candidates suitable for partial knee arthroplasty.Archives of orthopaedic and trauma surgery · 2024Article
- MRI use leading up to total knee arthroplasty: a retrospective cohort study.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2024Article
- Surgical Multidisciplinary Team Meetings Are Enhanced by Collaboration in the Metaverse.Journal of medical extended reality · 2024Article
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Authors and funding
5 authors.
Funding
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Abstract
Introduction: Knee pain is caused by various pathologies, making evaluation in primary-care challenging. Subsequently, an over-reliance on imaging, such as radiographs and MRI exists. Electronic-triage tools represent an innovative solution to this problem. The aims of this study were to establish the magnitude of unnecessary knee imaging prior to orthopaedic surgeon referral, and ascertain whether an e-triage tool outperforms existing clinical pathways to recommend correct imaging. Methods: Patients ≥18 years presenting with knee pain treated with arthroscopy or arthroplasty at a single academic hospital between 2015 and 2020 were retrospectively identified. The timing and appropriateness of imaging were assessed according to national guidelines, and classified as 'necessary', 'unnecessary' or 'required MRI'. Based on an eDelphi consensus study, a symptom-based e-triage tool was developed and piloted to preliminarily diagnose five common knee pathologies and suggest appropriate imaging. Results: 1462 patients were identified. 17.2% ( Conclusion: A substantial number of knee pain patients receive incorrect imaging, incurring delays and unnecessary costs. A symptom-based e-triage tool was developed, with promising performance and user feedback. With refinement using larger datasets, this tool has the potential to improve wait-times, referral quality and reduce cost.
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