What a Legacy CER Gap Analysis Actually Checks
"Gap analysis" gets used loosely in regulatory affairs. Used properly, it means checking a specific document against a specific standard, clause by clause, and recording exactly where it falls short. For a legacy Clinical Evaluation Report (CER), that standard is MDR Annex XIV — and the clearest view of how a Notified Body will read your CER against it comes from MDCG 2020-13, the Clinical Evaluation Assessment Report (CEAR) template that Notified Body assessors themselves use.
Why use a Notified Body's own template as the checklist?
MDCG 2020-13 was written for assessors, not manufacturers — it tells a Notified Body reviewer what to check and how to document their findings when they assess a clinical evaluation. That is exactly what makes it useful on the manufacturer's side of the table: it is the closest thing to seeing the exam questions before the exam. A gap analysis built around it checks your CER against the same structure, evidence and reasoning a reviewer will actually look for, not a generic compliance checklist.
What does the analysis actually look at?
A proper gap analysis works through the CER section by section, against three things in parallel:
| Area | What's being checked |
|---|---|
| Structure and scope | Does the CER cover the device's intended purpose, claims and clinical background the way Annex XIV expects? Is the clinical evaluation plan still consistent with what the CER actually contains? |
| Evidence and traceability | Is every clinical claim backed by a cited, appraised source? Is the literature search protocol documented and repeatable, and is the search date defensible given how long ago it ran? Where equivalence is claimed, does it meet the Article 61(5) conditions — including, for implantable and class III devices, contractual access to the equivalent device's technical documentation? |
| Benefit-risk and PMCF | Does the benefit-risk conclusion reflect the latest post-market data? Is there an executed PMCF plan, or just a plan on paper? Has PMCF/PMS data actually been folded back into the CER's conclusions, as MDR Article 61(11) requires? |
Each finding gets mapped back to the specific Annex XIV or MDCG 2020-13 clause it relates to — not a vague "this section is weak," but a specific, defensible gap.
What do the three outputs actually contain?
A gap analysis is only useful if it ends in something you can act on. That's three documents, not one:
- Gap report. Section-by-section findings, each tied to the specific MDR Annex XIV or MDCG 2020-13 requirement it fails to meet, with a plain-language explanation of why it matters.
- Claims-to-evidence map. Every clinical claim in the CER traced to its supporting evidence — or flagged where no evidence exists. This is usually where the sharpest surprises show up, because a claim can read confidently in the text while having nothing solid behind it.
- Remediation plan. A prioritized list of what needs fixing before the device's MDR transition deadline, separating what blocks certification from what can wait for the next PMCF cycle.
Where does AI help, and where doesn't it?
Comparing a 60-page CER against dozens of Annex XIV and MDCG 2020-13 requirements, line by line, is exactly the kind of structured, repetitive comparison AI is good at accelerating — extracting claims, flagging missing citations, checking whether a literature search date is stale, drafting the first version of the gap report.
What AI does not do is decide whether an equivalence argument actually holds, whether a benefit-risk conclusion is defensible, or whether a gap is serious enough to block submission. That judgment call — and the sign-off on every finding — stays with a qualified human reviewer before anything reaches you. We go into more detail on what that division of labor should look like in our article on responsible AI in CER drafting.
Key takeaways
- MDCG 2020-13 is written for Notified Body assessors, which is exactly why it's the right checklist for a manufacturer's own gap analysis — it shows what a reviewer will actually look for.
- A proper gap analysis checks structure/scope, evidence traceability, and benefit-risk/PMCF integration — not just whether the document "looks complete."
- The output should be three things: a gap report mapped to specific clauses, a claims-to-evidence map, and a prioritized remediation plan.
- AI can accelerate the comparison; a qualified human has to own every finding and sign-off.
Want to know where your own CER stands? Our Legacy CER Gap Analysis covers all three outputs above, delivered in 10 working days — see how it fits against your MDR transition deadline.
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