Feasibility and safety of an AI-driven postoperative telephone system for cataract surgery follow-up in Canada

To evaluate the safety and effectiveness of an artificial intelligence (AI) telephone agent, Dora-CA1, in managing routine postoperative follow-up after cataract surgery. Prospective, single-centre study including patients undergoing routine cataract surgery at a high-volume surgical center in Ontario, Canada. All participants received a Dora-CA1 call one day before their scheduled postoperative week 1 (POW1) visit. The AI system assessed symptoms, addressed patient questions, and provided care recommendations. At POW1, patients were invited to complete a survey on demographics, usability, acceptability, and travel burden. The primary outcome was agreement between Dora-CA1’s recommendations and optometric clinical evaluations. Secondary outcomes included patient satisfaction and usability. Of 326 patients, 272 answered the call, and 161 (59%) completed the full interaction. Non-completion was 51%, mainly due to missed or unreceived calls. Sensitivity and specificity for detecting clinically relevant concerns (elevated IOP, iritis, or other findings requiring review) were 96% and 76.6%, respectively. Patients reported high acceptability of the system, giving a mean of 8.22 (SD 1.96) when asked, “between 1 and 10, with 10 being the highest, how likely would you be to recommend this automated system to a friend or colleague?” Only 29.57% felt the system matched in-person care, despite generally positive usability scores. Dora-CA1 demonstrated strong alignment with clinician assessments and was well received by patients who completed the call. However, real-world implementation challenges, including early hang-ups and onboarding barriers, limit its current reach. Further refinement and integration could allow Dora-CA1 to play a valuable role in cataract surgery follow-up, easing the burden on clinical teams. A key limitation is the exclusion of non-English-speaking participants, which limits the applicability of the system in multicultural populations.

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Publication Details

Journal
AJO International
Published
2026-01-30
DOI
https://doi.org/10.1016/j.ajoint.2026.100232
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Feasibility and safety of an AI-driven postoperative telephone system for cataract surgery follow-up in Canada

Sohel Somani, A R C Higham, Nick de Pennington, Eric S. Tam et al.
AJO International
Artificial Intelligence in Healthcare and Education
article

Feasibility and safety of an AI-driven postoperative telephone system for cataract surgery follow-up in Canada

Sohel Somani, A R C Higham, Nick de Pennington, Eric S. Tam, Ernest Lim, Amin Hatamnejad, Hannah H. Chiu
article en

Abstract

To evaluate the safety and effectiveness of an artificial intelligence (AI) telephone agent, Dora-CA1, in managing routine postoperative follow-up after cataract surgery. Prospective, single-centre study including patients undergoing routine cataract surgery at a high-volume surgical center in Ontario, Canada. All participants received a Dora-CA1 call one day before their scheduled postoperative week 1 (POW1) visit. The AI system assessed symptoms, addressed patient questions, and provided care recommendations. At POW1, patients were invited to complete a survey on demographics, usability, acceptability, and travel burden. The primary outcome was agreement between Dora-CA1’s recommendations and optometric clinical evaluations. Secondary outcomes included patient satisfaction and usability. Of 326 patients, 272 answered the call, and 161 (59%) completed the full interaction. Non-completion was 51%, mainly due to missed or unreceived calls. Sensitivity and specificity for detecting clinically relevant concerns (elevated IOP, iritis, or other findings requiring review) were 96% and 76.6%, respectively. Patients reported high acceptability of the system, giving a mean of 8.22 (SD 1.96) when asked, “between 1 and 10, with 10 being the highest, how likely would you be to recommend this automated system to a friend or colleague?” Only 29.57% felt the system matched in-person care, despite generally positive usability scores. Dora-CA1 demonstrated strong alignment with clinician assessments and was well received by patients who completed the call. However, real-world implementation challenges, including early hang-ups and onboarding barriers, limit its current reach. Further refinement and integration could allow Dora-CA1 to play a valuable role in cataract surgery follow-up, easing the burden on clinical teams. A key limitation is the exclusion of non-English-speaking participants, which limits the applicability of the system in multicultural populations.

AJO InternationalVol. 3(1)
Moorfields Eye Hospital NHS Foundation Trust (GB), University of Toronto (CA), ITS Electronics (Canada) (CA), William Osler Health System (CA), Moorfields Eye Hospital (GB), University College London (GB), McMaster University (CA)
Reduced inequalities
Openalex Percentile: Top 75%
Artificial Intelligence in Healthcare and Education
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