Freed’s Clinical Evidence offering is designed to provide clinicians with reliable, high-quality clinical guidance while maintaining strong safety guardrails. Freed’s approach to clinical evidence is grounded in trusted clinical knowledge, clinically meaningful human review, careful use of patient and note context, and clear governance around how AI-generated guidance is surfaced.

Freed’s Clinical Evidence is designed to use only evidence-based clinical information from trusted sources, reducing the risk that low-confidence, outdated, or non-authoritative information is surfaced in clinical contexts. Freed also has a key advantage in its ability to incorporate patient-specific and note-level context when surfacing evidence.

Because this context remains within Freed’s HIPAA-compliant environment, the system can generate more relevant and clinically useful support without requiring patient data to leave the protected workflow. This allows Clinical Evidence to reflect the most important clinical context available to the provider but still maintaining strong privacy protections.

Freed's Clinical Evidence foundation was built and is continually refined with human annotation and clinical review in the loop. Clinical and domain experts helped shape how information is identified, interpreted, and surfaced to clinicians. This human-guided design process helped ensure that the system aligns with real clinical workflows, appropriate clinical reasoning standards, and the practical needs of providers at the point of care.

Clinical Evidence is also designed to be transparent and source-oriented. Clinicians can understand the basis for recommendations, review supporting information, and apply their own clinical judgment. Freed’s role is to augment clinician decision-making, not replace it.

Freed does not include advertising in provided answers, ensuring that clinical guidance is not influenced by sponsored content or commercial placement.

Freed's Clinical Evidence uses structured safeguards to control how the LLM can generate clinical guidance. These safeguards include rules requiring source grounding, restrictions on inappropriate or prohibited outputs, and guardrails that prevent the system from acting as an autonomous clinical decision-maker.

Freed’s privacy architecture further supports safe delivery. Patient data is handled within Freed’s HIPAA-compliant environment, and data is scrubbed before being sent anywhere outside that environment when applicable. This helps preserve patient confidentiality while allowing the system to use clinically relevant context appropriately.

Freed's Clinical Evidence is intended to support, not substitute for, clinician judgment. The tool’s intended use and limitations should be clearly documented so clinicians understand how to interpret and apply outputs. Human review remains meaningful, users should be able to identify when AI contributed to recommendations, and governance and monitoring processes should be in place to evaluate performance, safety, and clinical appropriateness over time.

Clinical Evidence is therefore best understood as a clinically grounded support layer: it helps surface relevant guidance from trusted sources, incorporates patient and note context within a protected workflow, and maintains safety through disciplined sourcing, privacy safeguards, human oversight, and clear limitations rather than autonomous clinical judgment.

Answers provided through Freed's Clinical Evidence are grounded only in the sources below — evidence-based, clinically vetted references spanning primary literature, specialty societies, and clinical guideline bodies.

If you need further help or have questions, you can get in touch with our Clinician Support team in the method that works best for you: