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Improving support and self-management of ophthalmic patients using an artificial intelligence health coach
Ojasvi Sharma1, Bhavesh Sharma2, Vivek Gupta3
1Department of Ophthalmology, Worcestershire Acute Hospitals NHS Trust, Worcester, United Kingdom.
Abstract:
This study evaluates patient engagement and satisfaction with Everyday Medical Monitoring Ally (E.M.M.A), a purpose-trained artificial intelligence (AI)-powered health coach delivered via WhatsApp. E.M.M.A integrates AI-driven symptom tracking, personalized medical information, and lifestyle guidance to support eye health management in a real-world clinical setting. This pilot study enrolled patients from a UK-based ophthalmology clinic managing chronic eye conditions. Patient interactions with E.M.M.A were logged over a 2-month period. Data collected included chat frequency, temporal patterns, and interaction modality (text or audio). A post-study satisfaction survey was conducted. Human validation of AI-generated question-answer pairs was performed independently by two glaucoma consultants. Ninety-one patients consented to participate, of whom 83 interacted with E.M.M.A, generating 446 analyzed chat sessions. Audio interactions accounted for 28% of chats. A subgroup of 39 users (42%) generated nearly 75% of all chats, while 52% of users were repeat users. Most patient queries related to general eye health and symptoms, comprising 39% of questions. Symptom-related content accounted for 26% of response classifications. The satisfaction survey was completed by 66 users, with 88% reporting being satisfied or very satisfied. A total of 65% would definitely recommend E.M.M.A, while 9% reported mild to moderate anxiety during use. Human expert validation scores exceeded 95% across all assessed domains. Qualitative feedback indicated acceptance of E.M.M.A as a reassuring and valuable adjunct when immediate clinical support was unavailable. AI-driven health coaches such as E.M.M.A may help bridge gaps in ophthalmic care between clinical visits by providing continuous, personalized, and medical record-informed patient support.
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