Checklist

The Ophthalmology AI Readiness Checklist: 14 Things to Look for Before You Adopt AI in Your Practice

A practical checklist for ophthalmology practices evaluating AI documentation tools, covering clinical intelligence, documentation automation, coding accuracy, workflow integration, and physician control.

Overview

This infographic offers a 14-point checklist to help ophthalmology practices evaluate AI tools before adoption, organized into five categories:

  • Clinical Intelligence – Whether the tool is built specifically for ophthalmic exam structure and subspecialty charting (glaucoma, retina, cataract, cornea), and populates findings directly into correct chart fields.
  • Documentation Automation – Whether it offers multiple levels of AI support, can generate a complete structured note from the patient conversation, and uses prior visit history to inform follow-up notes.
  • Coding & Billing Accuracy – Whether it ties assessments to billable ICD-10 codes and generates ready-to-send prescriptions and orders.
  • Workflow & Integration – Whether it works natively inside the existing EMR, applies to the chart in one click, and connects to diagnostic imaging (OCT, fundus, visual field).
  • Physician Control – Whether every note is reviewed before submission and whether field-by-field control is available.

A final section, Room to Grow, addresses whether the tool allows practices to add automation over time without switching vendors.

The guide closes with scoring guidance: most tools on the market cover only a handful of these criteria, while a platform built specifically for ophthalmology should check all 14.