MIPS-eligible clinicians use platform-agnostic, interoperable clinical decision support (CDS) tools—including artificial intelligence (AI)-enabled predictive decision-support interventions—to guide care-team workflow and support evidence-based, patient-centered decision-making. As part of this activity, clinicians prioritize open-source or freely available CDS tools where feasible and implement organizational policies to ensure the safe, appropriate, and effective use of these technologies. This activity may include: • Use of interoperable CDS tools, including AI-enabled technologies that meet the ONC definition of predictive decision-support interventions in 45 CFR 170.102: "technology that supports decision-making based on algorithms or models that derive relationships from training data and then produce an output that results in prediction, classification, recommendation, evaluation, or analysis" • Organizational policies for safe CDS and AI use, including processes to identify, review, and mitigate AI-related adverse events or near‑misses, and to address clinician concerns about liability, model reliability, and appropriate use • Evaluation of AI-enabled CDS tools using the following quality principles: ○ Fairness: outputs free from bias or undue risk ○ Appropriateness: relevance to the clinical context ○ Validity: accurate and reliable predictions or recommendations ○ Effectiveness: demonstrated benefit in real‑world use • Workflow integration practices showing that CDS recommendations—whether originally human‑curated or AI‑generated—are applied consistently in treatment planning, patient counseling, and follow-up • Periodic review and updating of CDS tools and related protocols to maintain alignment with best practices, organizational policies, and patient‑safety standards.