{
  "signal_id": "SIG-2026-010",
  "observed_date": "2026-08-08",
  "category": "AI Safety + Postmarket Evidence",
  "title": "FDA keeps real-world performance monitoring of AI-enabled medical devices as a major digital-health policy topic",
  "what_changed": "FDA's Digital Health Center of Excellence highlights real-world AI performance evaluation, including drift, clinical outcomes, user behavior, infrastructure, and post-deployment monitoring as core lifecycle issues.",
  "why_it_matters": "AI adoption increasingly requires a post-deployment evidence and monitoring architecture, not only premarket validation.",
  "affected_actors": [
    "FDA",
    "AI medical-device developers",
    "hospitals",
    "clinicians",
    "quality teams",
    "patients"
  ],
  "decision_implication": "Add real-world monitoring, drift detection, human-AI interaction, and response protocols to P4L's AI adoption/evidence standard.",
  "status": "Active policy/science topic",
  "evidence_class": "E5 — official FDA source",
  "impact": 5,
  "immediacy": 4,
  "relevance": 5,
  "novelty": 4,
  "adoption_leverage": 5,
  "priority_score": 94,
  "sources": [
    "https://www.fda.gov/medical-devices/digital-health-center-excellence/request-public-comment-measuring-and-evaluating-artificial-intelligence-enabled-medical-device"
  ],
  "public_slug": "/signal/2026-08-08-fda-ai-real-world-performance/",
  "watch_conditions": [
    "New guidance",
    "postmarket requirements",
    "performance-monitoring standards",
    "drift methodologies."
  ],
  "last_verified": "2026-08-08",
  "version": "1.0"
}