Close MIPS #117 Gap: How PCPs Screen for Diabetic Eye Disease with Autonomous AI
- Adi Haupt
- Jul 23
- 4 min read
For primary care practices, Merit-based Incentive Payment System (MIPS) Quality ID #117 (Diabetes: Eye Exam) is often one of the most frustrating performance metrics to manage.
Ensuring every patient with diabetes receives an annual retinal screening is more than a MIPS requirement; it is a critical clinical priority. With over 40 million Americans living with diabetes, diabetic retinopathy continues to be the leading cause of blindness in working-age adults. Fortunately, early detection can prevent at least 95% of this vision loss, which is precisely why CMS places such high strategic weight on this measure.
Implementing point-of-care fully autonomous AI with AEYE-DS enables practices to screen every patient during their routine visit in under a minute, closing the care gap on the spot and maximizing MIPS #117 performance scores.
1. The MIPS #117 Dilemma: The Referral Loop Failure
Under traditional care pathways, meeting MIPS Measure #117 requires a PCP to:
Identify a diabetic care gap during an office visit.
Refer the patient to an outside optometrist or ophthalmologist for a dilated eye exam.
Track down the external diagnostic report, confirm its findings, and manually log it into the EHR to satisfy MIPS criteria.
The Friction Points
Low Patient Follow-Through: Over 60% of patients with diabetes fail to complete their annual eye exam due to scheduling friction, transit challenges, or reluctance to undergo hours of post-dilation vision blur.
Administrative Blind Spots: Specialist reports rarely make it back to the primary care provider automatically. Staff spend hours manually chasing records, leaving care gaps wide open.
The Cost of Low Scores: Under MIPS, falling into lower performance deciles directly impacts your final Composite Performance Score (CPS), exposing practices to Medicare reimbursement penalties of up to -9%.
2. CMS Rules: Autonomous AI Fills the Care Gap
Recognizing the systemic barriers of external referrals, the Centers for Medicare & Medicaid Services (CMS) updated Quality ID #117 numerator specifications to explicitly include autonomous AI point-of-care screening.
The measure guidelines state that the numerator is satisfied when fundus imaging is analyzed by an autonomous AI system and documented as with or without diabetic retinopathy, specifically citing CPT code 92229.
This policy update allows primary care teams to complete the entire diagnostic loop during the routine diabetic wellness visit without requiring an off-site eye care professional or manual reading delay.
3. How AEYE-DS Solves the Point-of-Care Equation
To help close care gaps during routine visits, clinics use AEYE-DS, the first and only FDA-cleared portable autonomous AI solution for diabetic retinopathy. It is also the only AI that requires just 1-image-per-eye for the analysis.
The 1-minute exam requires a single image per eye without requiring pupil dilation, providing instant results.
With up to 99%, imageabiltiy, ensuring virtually every patient gets an accurate result on the spot.
The 1-Minute Seamless EHR Workflow
AEYE-DS embeds directly into major EHR platforms (like Epic), creating an end-to-end automated process:
EHR Alert & Direct Order: The EHR flags an open diabetic eye exam care gap at check-in.
Rapid Single-Image Capture: Clinic staff capture one image per eye with no dilation.
Instant Diagnosis & Automated Documentation: The FDA-cleared AI returns instant results, populated into the EHR automatically, closing the care gap without manual data entry.
Automated Billing via CPT 92229: Billing is auto-populated with CPT 92229. Because the analysis is autonomous at the point of care, the practice retains 100% of the reimbursement.
On-the-Spot Results & Compliant Referral Pathways
During the visit, the provider reviews results directly with the patient. Patients with positive findings discuss the results in real time and receive an immediate specialist referral.
This referral pathway fulfills explicit CMS and American Diabetes Association (ADA) requirements. It turns point-of-care AI into a complete, compliant screening strategy that simultaneously boosts HEDIS scores, Star ratings, and ACO quality targets.
4. Financial & Quality Impact Comparison
Autonomous AI turns diabetic eye screening from a cost center into a financial win across four areas:
Direct reimbursement: Each screening is billable under CPT 92229. Because the analysis is autonomous at the point of care, the practice keeps the full reimbursement.
MIPS #117 incentives: Completing screenings in-clinic maximizes Quality points on Measure #117, protecting the Composite Performance Score and avoiding downward payment adjustments.
Saved staff time: Instant results with structured EHR documentation eliminates the days-to-months of chasing specialist reports, freeing staff hours.
Value-based care: A single screening simultaneously closes the HEDIS gap, feeds Medicare Star Ratings, and supports ACO quality targets, compounding the value across every program the practice participates in.
Key Takeaway
MIPS Measure #117 doesn't have to be a drag on your practice performance. By shifting from passive specialty referrals to active point-of-care autonomous screening with AEYE-DS, PCPs turn a costly administrative headache into a streamlined, reimbursable clinical success. It becomes a seamless part of the routine visit and a new standard of care, closing gaps the moment they're identified.
Key Resources & References
CMS Quality Payment Program: Quality ID #117 (CMS131v14) Specification |
National Eye Institute (NEI): Diabetic Retinopathy Data & Prevention
American Diabetes Association (ADA): Standards of Care in Diabetes
eCQI Resource Center (HealthIT.gov): CMS131: Diabetes: Eye Exam
FDA 510(k) Premarket Notification: AEYE-DS (K221183)
FDA 510(k) Premarket Notification: AEYE-DS (K240058), April 23, 2024
American Academy of Ophthalmology: "Six Out of 10 People with Diabetes Skip a Sight-Saving Exam," 2024.
Diabetic Eye Disease Resources, National Eye Institute (NIH)
