Abstract
PURPOSE: To understand the efficiency, safety, and patient acceptability of using an artificial intelligence-based conversational agent Dora R2 (Ufonia Limited, UK) in the cataract pathway. PATIENTS AND METHODS: This mixed methods cohort-based service evaluation included both prospective and retrospective data collection from two UK public hospitals: Oxford University Hospitals National Health Service (NHS) Foundation Trust and Buckinghamshire Healthcare NHS Trust. Patients undergoing cataract surgery of mixed complexity were included. All patients who had postoperative calls with Dora R2 between October 2022 and April 2023 were included. Dora R2 calls patients three weeks after routine cataract surgery to assess symptoms and answer patient queries. Patient demographics and clinical outcomes were reviewed, and statistical analyses were performed to identify any differences based on age, gender and ethnicity. RESULTS: Of 1580 eligible patients, 1269 (78%) completed the Dora R2 call. About 767 (63%) had "no clinical concerns" identified by Dora. The median patient age was 77 years, with 84% identifying as white. There were no significant differences in call outcomes based on demographic factors (at 5% significance level). The Net Promoter Score for patient acceptability was 47, indicating high satisfaction. Regarding safety, only 0.3% of patients required unplanned management changes within two weeks of a Dora call with a "no concerns identified" outcome. CONCLUSION: Dora R2 effectively supports postoperative follow-up for cataract surgery, demonstrating high efficiency, safety, and patient acceptability. The technology successfully supports clinicians in identifying uncomplicated cases, reduces the need for clinician-led consultations, and does not exacerbate digital inequalities, showing promise for broader implementation.