Effectiveness of a Large Language Model-Based Educational Tool on Intraocular Lens Options

Effectiveness of a Large Language Model-Based Educational Tool on Intraocular Lens Options: A Randomized Controlled Trial

Patients with cataracts disease need to choose what type of artificial lens will go into their eye prior to surgery date. Some lenses are standard and are usually covered by insurance. Other "premium" lenses have various benefits such as reducing the need for glasses but usually require out-of-pocket costs.

The combined busy outpatient clinic and complexity of artificial lens choices in the ever-changing world of cataract surgery tends to lead patients confused about their available lens options. There is an abundance of educational material present in premium lenses, however these are limited by accessibility and are standardized at single educational levels.

Therefore in the present study, we want to test whether giving patients a short LLM powered AI-guided explanation from Custom GPT from OpenAI of lens options prior to their consultation with their doctor can improve visit efficiency, physician explanation and patient understanding of lens options. We will compare two groups: standard of care versus standard of care plus AI education.

The LLM in this study is intended to provide supplemental information about premium intraocular lens(IOLs) options to study participants, and is no means supposed to replace a health care professional in the diagnosis, cure, treatment, and/or mitigation of disease. Study is analogous to giving a verified health pamphlet to a patient for them to view and learn different IOL options, in other words, facilitating patient understanding of their options.

The LLM will be trained by several health care professionals and MD specialists to provide sufficient instructions. Sources will include verified online resources and MD information.

The investigators hope to learn if a large language model-based educational tool can improve visit efficiency, physician explanation and patient understanding of intraocular lens options. New knowledge of this study could guide how cataract counseling is delivered in the future and may help clinics spend more time on individualized questions instead of repeating generic information.

Study Overview

• Status: Enrolling by invitation
• Conditions: Intraocular Lens; Cataract Extraction; Cataract Surgery; Eye Disorders; Cataract and IOL Surgery; Cataract Surgery Experience
• Intervention / Treatment: Other: LLM-based Education

• Study Type: Interventional
• Enrollment (Estimated): 70
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • California
    • Palo Alto, California, United States, 94303
      • Byers Eye Institute

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Age 18 or older
• Presenting for cataract evaluation or preoperative cataract counseling in the ophthalmology clinic
• Able to provide informed consent
• English-speaking
• No prior cataract surgery in either eye (so that all patients are making a first-eye IOL decision)

Exclusion Criteria:

• Any cognitive impairment or hearing impairment that prevents meaningful counseling or survey completion
• Urgent ocular condition requiring immediate attention that would override routine cataract counseling (for example, acute retinal detachment)
• Patient declines or is unable to complete the brief post-visit survey
• Has ocular conditions that would impact eligibility of non-monofocal lens options

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: LLM-based Education + Standard of Care; Before seeing the fellow, the participant will listen to a short, structured LLM powered AI-delivered educational session with Custom GPT (10 minutes or less). The intractable AI script explains standard monofocal IOLs and premium options (toric, extended depth of focus, multifocal, light adjustable lens), including benefits, trade-offs, and out-of-pocket costs.; The AI module may allow the patient to ask clarifying questions within scope of that script. This AI session is not currently part of standard care and is considered the experimental intervention.; The participant takes a patient satisfaction (CSQ-8) after their clinical visit with the fellow and attending	Other: LLM-based Education; Participants will receive audio education powered by a large language model (LLM) before seeing the fellow or attending physician. The LLM will be presented using a 10 inch tablet or laptop device by a trained research team member. The interaction is intended to be self-guided, with no interference from the staff unless the LLM displays incorrect or "hallucinated" content. In such cases, the research staff will immediately correct any misinformation and record the occurrence, including details and frequency of the hallucination, for quality monitoring. The LLM module will deliver educational material about intraocular lens options and answer any questions the study participant has. This LLM-based education is for research purposes only. Afterward, participants will proceed to their scheduled visit.
No Intervention: Standard of Care; The participant skips the AI module and proceeds directly to routine fellow and attending counseling, which reflects current standard of care practice.; The participant takes a patient satisfaction (CSQ-8) after their clinical visit with the fellow and attending physician

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Total Consultation Time	Total consultation time of both fellow and attending physician in their visit with the study participant will be recorded in minutes.	Same Day of Enrollment up to 2 hours

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Patient satisfaction scale score as measured by Client Satisfaction Questionnaire-8 (CSQ-8)	4-point ordinal Likert-type response options. The total CSQ 8 score will be used as a continuous outcome, with higher scores indicating greater satisfaction.	Same Day of Enrollment up to 2 hours
Percentage of Monofocal Lens Chosen as IOL of Choice Between Arms	The intraocular lens chosen on day of surgery, grouped as monofocal or non-monofocal, will be documented post-surgery implantation.	Up to 4 weeks post enrollment

Collaborators and Investigators

• Sponsor: Stanford University
• Investigators: Principal Investigator: Robert T Chang, MD, Stanford University

Study record dates

Study Major Dates

• Study Start (Estimated): January 1, 2026
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): June 1, 2026

Study Registration Dates

• First Submitted: December 19, 2025
• First Submitted That Met QC Criteria: December 19, 2025
• First Posted (Actual): January 5, 2026

Study Record Updates

• Last Update Posted (Actual): January 5, 2026
• Last Update Submitted That Met QC Criteria: December 19, 2025
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Keywords: education; AI; LLM; GPT; ChatGPT; Custom GPT; CustomGPT; LLM-based education
• Additional Relevant MeSH Terms: Lens Diseases; Eye Diseases; Cataract
• Other Study ID Numbers: 82807

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No