Improving support and self-management of ophthalmic patients using an artificial intelligence health coach

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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Publication Details

Journal
Indian Journal of Ophthalmology
Published
2026-03-26
DOI
https://doi.org/10.4103/ijo.ijo_2205_25
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
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article

Improving support and self-management of ophthalmic patients using an artificial intelligence health coach

Ojasvi Sharma, Vivek Gupta, Tarun Sharma, Bhavesh Sharma et al.
Indian Journal of Ophthalmology
Gaze Tracking and Assistive Technology
article

Improving support and self-management of ophthalmic patients using an artificial intelligence health coach

Ojasvi Sharma, Vivek Gupta, Tarun Sharma, Bhavesh Sharma, Ajay Bakshi, Tanuj Dada, Rohit Gupta
article en

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.

Indian Journal of OphthalmologyVol. 74(4)
Dr. Rajendra Prasad Central Agriculture University (IN), Worcestershire Acute Hospitals NHS Trust (GB), University of Manchester (GB), Texas Instruments (India) (IN)
Quality Education
Openalex Percentile: Top 9%
Gaze Tracking and Assistive Technology
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