Accuracy and safety of an autonomous artificial intelligence clinical assistant conducting telemedicine follow-up assessment for cataract surgery
- Edward Meinert 1,2,3,4, Madison Milne-Ives 1,2, Ernest Lim 5,6,7, Aisling Higham 5,8, Selina Boege 1,2, Nick de Pennington 5, Mamta Bajre 9, Guy Mole 5,8,10, Eduardo Normando 3, Kanmin Xue 8,10
- Edward Meinert 1,2,3,4, Madison Milne-Ives 1,2, Ernest Lim 5,6,7
- 1Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK.
- 2Centre for Health Technology, School of Nursing and Midwifery, University of Plymouth, Plymouth, UK.
- 3Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, UK.
- 4Faculty of Life Sciences and Medicine, King's College London, London, UK.
- 5Ufonia Limited, 104 Gloucester Green, Oxford, UK.
- 6Imperial College Healthcare NHS Trust, Western Eye Hospital, London, UK.
- 7Department of Computer Science, University of York, York, UK.
- 8Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
- 9Oxford Academic Health Science Network, Oxford Science Park, Robert Robinson Ave, Oxford, UK.
- 10Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
- 0Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK.
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View abstract on PubMed
Summary
This summary is machine-generated.An artificial intelligence (AI) system, Dora R1, accurately triages post-cataract surgery patients, showing high sensitivity and specificity. This AI tool offers a safe, cost-effective solution to expand clinical capacity and improve patient follow-up.
Area Of Science
- Ophthalmology
- Medical Artificial Intelligence
- Digital Health
Background
- Artificial intelligence (AI) can enhance patient triage post-cataract surgery, improving clinical capacity.
- This study evaluates Dora R1, an autonomous telemedicine system, for post-cataract surgery patient assessment.
- The AI's performance is compared against ophthalmic specialists.
Purpose Of The Study
- To assess the accuracy and safety of the Dora R1 AI system in identifying cataract surgery patients requiring further management.
- To compare Dora R1's triage decisions with those of human ophthalmic specialists.
- To evaluate the usability, acceptability, and cost-effectiveness of the AI system.
Main Methods
- 225 patients undergoing cataract surgery were recruited from UK teaching hospitals.
- Dora R1 conducted autonomous follow-up calls, supervised in real-time by an ophthalmologist.
- Primary analysis compared AI and clinician decisions; secondary analyses used mixed methods for usability, acceptability, and cost.
Main Results
- Dora R1 achieved 94% sensitivity and 86% specificity, with strong agreement (kappa: 0.758-0.970) with clinicians.
- The AI system demonstrated high feasibility (96.5% autonomous calls) and cost benefits (£35.18 per patient).
- Patient acceptability was generally good, though concerns about the lack of human interaction in complex cases were noted.
Conclusions
- The Dora R1 AI system shows preliminary evidence of safety, acceptability, feasibility, and cost-effectiveness for post-cataract surgery follow-up.
- AI-driven telemedicine offers a viable approach to expand clinical capacity and support patient care.
- Further real-world implementation studies are recommended to validate safety and effectiveness in diverse settings.
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