Clinical decision support
OpenEvidence
OpenEvidence is an AI medical knowledge and clinical decision-support platform for healthcare professionals. It may improve clinician access to evidence and help produce clearer patient-facing materials, but it is HCP-gated and clinician-controlled. CAIHL review should focus on patient notice, refusal, correction, patient access to reasoning and sources, advertising separation, and how patient-specific record context is governed.
Public-source research has been drafted; final human publication review and change-log detail are still required.
Summary judgment · 18% toward patient-directed
Institution-directed, patient-affecting
OpenEvidence is built for clinicians and health systems, while its answers, patient-context workflows, notes, handouts, and after-visit summaries can affect patients who do not directly choose or govern the tool.
Patient agency
How this tool changes agency
Patient handouts and after-visit summaries can support understanding, but they remain clinician-mediated outputs rather than patient-controlled research or advocacy tools.
The patient generally does not appear to choose whether the clinician uses OpenEvidence; recording, EHR-context use, and patient-specific AI analysis require deployment review.
Patient-facing signals
Who does this AI serve?
Official materials repeatedly frame OpenEvidence as intended for physicians, clinicians, verified HCPs, and healthcare-professional workflows.
Can patients tell AI is involved?
Buyer and user-facing pages are transparent to clinicians, but patient-facing notice for evidence answers, patient handouts, after-visit summaries, visit recording, or EHR-integrated use was not visible in this pass.
Can patients meaningfully choose?
The patient generally does not appear to choose whether the clinician uses OpenEvidence; recording, EHR-context use, and patient-specific AI analysis require deployment review.
Can patients correct or challenge what the AI produces?
Clinicians can review and edit notes/summaries, but public materials do not show a patient-accessible route to inspect prompts, sources, reasoning, extracted patient context, or AI-shaped outputs.
Does it help patients understand or act?
Patient handouts and after-visit summaries can support understanding, but they remain clinician-mediated outputs rather than patient-controlled research or advocacy tools.
Text findings
Who is left out or burdened?
Patients are outside the primary access model
HCP-gated access may improve clinician evidence work while preserving a knowledge asymmetry for patients who cannot ask the same questions or inspect the same synthesis.
What happens to patient data?
Detailed public claims, unclear patient control
Privacy and Visits materials say questions/conversations are not shared, PHI is not used to train AI models, data is HIPAA-secured, and audio/note deletion is configurable; patient rights and deployment-specific retention need review.
Are the clinical boundaries clear?
Clear clinician-responsibility wording
Terms state the service is educational/informational, not a diagnostic service or substitute for clinical judgment. That does not answer patient notice, consent, or correction questions.
Who defined what good looks like?
Mostly vendor, clinician, society, investor, and health-system-defined
Content partnerships and clinician adoption are prominent; patient-partnered evaluation, patient agency measures, and patient-facing governance are not prominent in public materials.
Review method
Deep public-source review of official product pages, user guide, Visits documentation, patient handout and after-visit summary documentation, privacy policy, terms of use, and official partnership announcements; no vendor interview, clinician account testing, patient-facing deployment review, security audit, or independent accuracy evaluation.
Draft profile · Medium draft, official sources only