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openevidence verification workflow: how to trust (but verify) in under 3 minutes

a simple verification routine for ai medical search: citation hygiene, source triangulation, and a repeatable checklist for clinicians.

Most clinicians don’t need ‘more information’. They need higher confidence faster. This workflow is a lightweight verification habit: you use AI to retrieve and structure, then you validate the load-bearing points via primary sources.

The 3-minute verification routine

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Step 1 — Identify the 3 load-bearing claims

Pick the exact statements that would change what you do. Ignore the rest.
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Step 2 — Check citations are real and relevant

Verify the cited papers/guidelines exist, match the claim, and are not misapplied.
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Step 3 — Triangulate with at least one independent source

Look for a guideline or systematic review that supports (or challenges) the claim.
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Step 4 — Confirm recency for time-sensitive topics

If the topic changes frequently, check the publication date and whether the tool is relying on older material.
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Step 5 — Capture a one-line audit trail (optional)

If you need a record, note: ‘Checked X; confirmed via Y.’ Keep it professional and non-identifiable.
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Step 6 — If sources conflict, write ‘uncertain’ explicitly

Don’t let AI smooth over disagreement. When evidence conflicts, label it as such.
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Step 7 — Switch tools if you can’t verify fast

If you can’t validate key claims quickly, go direct to official sources or a trusted point-of-care reference.
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Step 8 — Never outsource accountability

AI can accelerate retrieval and summarisation; it cannot take responsibility for professional decisions.
SourceBrowse iatroX Knowledge Centre (structured answers built for fast verification)
Open Link

References

GMC: AI and innovative technologies (accountability principle)
OpenEvidence: Terms of Use (citations / content agreements context)
JAMA Network: OpenEvidence content agreement announcement