Editorial policy

How this content is made.

RemoteNurse teaches review-nursing workflows through synthetic practice cases, lessons, and a glossary. This page states plainly how that content is produced, what it is grounded in, what we check before it goes live, and - just as plainly - what we do not do. If anything here reads as a hedge, it is not one; it is the method.

Last updated July 2026

Content is drafted with AI

RemoteNurse practice content is AI-generated. Cases, lessons, and glossary entries are drafted with AI and then put through the automated checks described below. We state this openly because how content is made is something you deserve to know before you rely on it.

Cases are grounded in synthetic patient data

Every case is built on open-source synthetic patient data - Synthea, in the FHIR R4 format. Synthetic means the people in our cases are generated, not real. There are no real patients behind any case, and no protected health information ever enters RemoteNurse. Do not enter real patient data into any field; this is a practice environment, not a clinical or payer system.

Facts are grounded in cited authoritative sources

Regulatory and clinical facts are tied to a tiered registry of authoritative sources rather than to a model’s memory. The tiers run from law and regulation (the eCFR) through federal agencies (CMS, HHS OIG, AHRQ), to standards and accreditation bodies (NCQA, URAC, NCSBN, ANA) and the certification bodies that grant review-nursing credentials. When content states a rule, that rule is cited to its source, and the source registry itself is public on our evidence page.

What we check before release

Before any content is published, it must pass a stack of automated checks:

  • Schema checks that the content is well-formed and complete.
  • A content-safety gate.
  • An accuracy lint pinned to the regulated values, so time limits and clocks match the rules that set them.
  • A forbidden-claims lint that blocks overclaims and uncited deadlines.
  • A concept-canon check that flags text contradicting the verified facts it references.
  • Source-registry checks that every cited domain is on the allowlist and every source link is still live.
  • A Case-Judge solvability check, so every case can actually be worked to a verdict.
  • Golden-fixture replay, so known-good cases keep scoring the way they should.
Not individually reviewed by a licensed clinician

This content is not individually reviewed by a licensed clinician. It is drafted with AI, grounded in synthetic data and cited sources, and cleared by the automated checks above - but no clinician signs off on each item. We do not tell you it is expert-reviewed, because it is not. If we ever add a consenting, licensed reviewer, the items they review will carry that reviewer’s name and the date they reviewed it; until then, no such byline appears anywhere on RemoteNurse, and its absence is the honest signal.

What RemoteNurse is - and is not

RemoteNurse is education and practice. It is not medical advice, and nothing here should be used to make a decision about a real patient. It is not a certification, a credential, or a qualification, and completing cases does not confer one. It is not a determination of your clinical competency or your fitness to be hired. The cases are synthetic throughout, and any resemblance to a specific real person or event is coincidental.

Proprietary criteria

Commercial review criteria such as MCG and InterQual are named only as neutral concepts, so you know they exist and what role they play. Their proprietary content is never reproduced, paraphrased, or taught here.

Report a possible inaccuracy

If something reads wrong, tell us. Use the support page and pick “Case content feedback” or “Report an issue,” or write to us directly at hello@remotenurse.org. We read every report and correct what we get wrong.