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Related healthcare AI tools and resources.
Clinical Decision Support & Risk AI tools typically range from $2 - $15/patient/mo depending on practice size, features, and deployment model. Compare pricing across leading vendors in our comprehensive guide.
AI systems that analyze patient data to identify risks, predict outcomes, suggest diagnoses, and recommend evidence-based treatment options.
Per-provider or per-patient per month — the dominant model in clinical decision support & risk.
Custom enterprise licensing
| Vendor | Starting Price | Pricing Model | Free Trial | Notes |
|---|---|---|---|---|
| Tempus AI | Custom | Per-test / enterprise | -- | Precision medicine platform. Pricing varies by use case. |
Pricing data last verified February 2026. Contact vendors for the latest pricing and promotions.
Budget 20-40% above the subscription price for total cost of ownership in year one. Common hidden costs include:
Clinical Decision Support & Risk typically costs $2 - $15/patient/mo. The average price is $3-8/patient/mo or $300/provider/mo. Enterprise pricing ranges from Custom enterprise licensing. Pricing varies based on Patient panel size, Number of risk models deployed, Integration complexity with EMR.
The most common pricing model for clinical decision support & risk is per-provider or per-patient per month. There are currently no free tier options in this category. Enterprise volume discounts are standard.
Beyond the subscription price, common hidden costs include: Data normalization and ETL setup; Clinical validation study costs; Ongoing model tuning and validation; Regulatory compliance documentation. Budget 20-40% above the sticker price for total cost of ownership in year one.
Key ROI metrics for clinical decision support & risk include: Early risk identification: 30-50% improvement; Avoidable readmissions reduced: 15-25%; Time to diagnosis improvement: 20-40%; Annual savings per patient: $200-$1,500. Most organizations see positive ROI within 6-12 months of deployment.
Our experts can provide a personalized recommendation based on your practice size, EMR, and budget.