IDx-DR v2.3

K213037

Digital Diagnostics Inc. · cleared 2022-06-17 · product code PIB · Ophthalmic

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“The IDx-DR device is an autonomous, artificial intelligence (AI)-based system for the automated detection of more than mild diabetic retinopathy (mtmDR).”
Algorithmartificial intelligence (AI)-based system
source quote (p.4)
“The IDx-DR device is an autonomous, artificial intelligence (AI)-based system for the automated detection of more than mild diabetic retinopathy (mtmDR).”
Adaptive (vs locked)Yes
source quote (p.8)
“Future algorithm improvements will be made under a consistent medically relevant framework. A protocol was provided to mitigate the risk of algorithm changes leading to changes in the device technical specifications, which would lead to changes in false positive or false negative results.”
PCCPYes
source quote (p.8)
“Future algorithm improvements will be made under a consistent medically relevant framework. A protocol was provided to mitigate the risk of algorithm changes leading to changes in the device technical specifications, which would lead to changes in false positive or false negative results. These changes could significantly affect clinical functionality or performance specifications directly associated with the intended use of the device. The protocol specifies the level of change in device specifications that could significantly affect the safety or effectiveness of the device, triggering the requirement for a new 510(k) premarket notification submission before commercial introduction. The protocol incorporates a risk management approach and other approaches provided in the FDA guidance document Deciding When to Submit a 510(k) for a Software Change to an Existing Device: Guidance for Industry and FDA Staff in development, validation, and execution of the device changes.”
Cybersecurity addressedYes
source quote (p.8)
“The cybersecurity considerations of data confidentiality, data integrity, data availability, denial of service attacks, and malware were adequately addressed utilizing platform controls, application controls, and procedure controls, and evidence was provided for the intended performance of the controls.”

Validation studies (1)

Retrospective clinical

n=850 patients

endpoints: sensitivity; specificity; diagnosability; positive predictive value (PPV); negative predictive value (NPV)

Reported performance (4 observations)

sensitivity0.8769CI (82.24%, 91.95%)
source quote (p.10)
“87.69% (171/195) (82.24%, 91.95%)”
specificity0.9007CI (87.42%, 92.32%)
source quote (p.10)
“90.07% (553/614) (87.42%, 92.32%)”
ppvas written: “Positive Predictive Value”0.7371CI (67.55%, 79.25%)
source quote (p.11)
“73.71% (171/232) (67.55%, 79.25%)”
npvas written: “Negative Predictive Value”0.9584CI (93.87%, 97.32%)
source quote (p.11)
“95.84% (553/577) (93.87%, 97.32%)”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

0
recalls in product code, 24mo
0
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
0
drift signals on this device

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Ophthalmic panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K213037