Clinical evaluation without pitfalls — Common errors in CER and how to avoid them

This blog post provides a concise and practical overview of the typical errors in clinical evaluations (CERs) under the MDR that repeatedly lead to audit findings and requests for further information, how these weaken the evidence for claims and the benefit-risk profile — and, most importantly, what concrete measures and priorities you can use to quickly and sustainably eliminate these pitfalls.

Abbreviations

CEP	Clinical evaluation plan
CERIUM	Clinical Evaluation Report
CIP	Clinical Investigation Plan
MDR	Medical Device Regulation (EU Ordinance 2017/745)
TD	Technical Documentation
Pmcf	Post-Market Clinical Follow-up
Pms	Post-Market Surveillance

Underlying regulations, standards and guidelines

EU Regulation 2017/745 (MDR)

MDCG 2020-1

MDCG 2020-5

MDCG 2020-6

MEDDEV Guideline 2.7/1 Revision 4

Draft of ISO/DIS 18969

1 Introduction

Errors in clinical evaluations (CERs) are not mere formalities; they have immediate regulatory and operational consequences. Inadequate methodology, lack of traceability, or outdated data regularly lead to audit findings, can trigger follow-up requirements, and, in the case of initial clinical evaluations, delay approval processes. Against the backdrop of the MDR requirements (especially Article 61 and the PMCF/PMS requirements), the clinical evaluation is therefore not just a "document," but a dynamic, evidence-based management tool that must be maintained throughout the entire product lifecycle.

In this article, we systematically summarize the most common errors we encounter in reviews and gap analyses: from unclearly formulated claims/endpoints and measurable parameters and missing CEPs, to unclear literature searches and insufficiently substantiated equivalence claims, to a lack of traceability between CER, IFU, and label, as well as unstructured benefit-risk analyses. For each identified problem, we provide practical countermeasures, concrete steps, template recommendations, and prioritizations for rapid benefit.

2. Error Overview — The Top Pitfalls at a Glance

Here is a concise summary of the most common pitfalls in clinical assessments — each with a brief description and a direct countermeasure, so you know immediately what to do.

pitfalls	Brief description	Quick fix / countermeasure
Treat CER as a one-time document	CER is only created for approval purposes and then "filed"	Introduce CER lifecycle: Review intervals (e.g., annually for Class III), PMS/PMCF triggers, versioning and release process
Unclear / missing clinical claims/endpoints	Safety/clinical performance/benefit not measurably defined	Formulate claims/endpoints in the CEP SMART and assign concrete measurable parameters to each claim/endpoint
Weak state-of-the-art analysis	SoTA remains descriptive without a comparative scale	Depict SoTA along measurable clinical/technical parameters and derive target values
Excessive reliance on equivalence	Equivalence is claimed, but not fully proven	Create a full equivalence dossier (technical/biological/clinical) or change route
Literature review without reproducibility	Search plan, inclusion/exclusion criteria or PRISMA flow are missing	Document the search log, screening workflow, and review report
PMS/PMCF data is not integrated	Field data remains in silos and does not flow into CER	Define PSUR/PMS/PMCF as central inputs; maintain the traceability matrix; set up the update workflow
No structured benefit-risk analysis	Benefits and risks are presented only narratively side by side	Introduce a benefit-risk matrix (quantitative parameters, CI, weighting) and derive measures
Inconsistent documents (CER vs. IFU vs. Claims)	IFU/Label/Marketing are not covered by CE	Traceability matrix (Claim ↔ CER ↔ IFU) & synchronized release management
Unclear clinical evaluation strategy	The evaluation methodology (study/equivalence/performance data) is missing or unfounded	Define the assessment route early in the CEP, define fallbacks and set milestones

This overview helps to set priorities: It is best to start with the points that have the greatest audit risk and the highest impact on claims — typically traceability, claims definition, SoTA (derive measurable parameters!) and PMS integration.

3. Detailed error analysis & countermeasures

Below, we'll go through each top pitfall individually: briefly outlining the problem, explaining why it's critical, providing concrete, immediately actionable countermeasures, and concluding each section with a short checklist of 3-5 items that you can quickly tick off. The recommendations are pragmatic—the goal is audit-proofness, traceability, and practical implementation.

3.1 Treat CER as a one-off document

Problem & Impact: The CER is only created for approval purposes and then "filed away." This results in the loss of new insights from PMS/PMCF or the literature; claims may become outdated, and auditors may criticize the lack of lifecycle processes.
Countermeasures (specific):

• Define a CER lifecycle in the CEP: Review intervals (e.g., annually for Class III/implantable, risk-based for other classes) and ad-hoc triggers (e.g., significant PSUR findings, new guidelines).
• Implement a change log: versioning, date, trigger, responsible party, brief description of the change.

Mini-check:

• Review interval documented? ✔
• Is a trigger list available? ✔
• Change log/versioning available? ✔

3.2. Unclear or missing clinical claims/endpoints

Problem & Impact: Without clear, measurable claims, you cannot gather targeted evidence or meaningfully define endpoints.

Countermeasures (specifically):

• Formulate claims using the SMART criteria (Specific, Measurable, Achievable, Relevant, Time-bound). Example: "Reduces A-rate by X% within 30 days vs. standard.".
• Assign specific measurable parameters, metrics (numerator/denominator) and acceptance criteria to each claim/endpoint.
• Define the claim formulations in the CEP and maintain a claim/endpoint register file (claim/endpoint ID, formulation, measurable parameter, document list, status).

Mini-check:

• Are all claims/endpoints formulated in the SMART way? ✔
• Does each claim/endpoint have an associated measurable parameter? ✔

3.3 Weak State-of-the-Art (SotA) Analysis

Problem & Impact: If SotA remains merely descriptive, the benchmark for substantiating claims or improvements is lacking.
Countermeasures (specific):

• Derive measurable benchmarks (parameters) from SotA (e.g., mean complication rate, measurement deviation). These benchmarks define your target variables.

Mini-check:

• Benchmarks derived and documented? ✔
• SotA → CER/CEP issues linked? ✔

3.4. Excessive reliance on equivalence

Problem & Effect: Insufficiently documented equivalence leads to requests for further information from notified bodies; clinical data are then unusable.
Countermeasures (specifically):

• Create a complete equivalence dossier with three building blocks: technical equivalence (design, dimensions, functions), biological equivalence (materials, surfaces, contacts), clinical equivalence (intended purpose, indication, population, users).
• Systematically evaluate differences: small/neutral vs. relevant → if relevant, plan your own data (study or PMCF).

Mini-check:

• Is the equivalence dossier (tech/biol/clin) complete? ✔
• Differences assessed & documented? ✔

3.5 Literature search without reproducibility / traceability

Problem & Impact: Missing search protocols and undocumented selection criteria make results unreproducible — auditors demand reproducibility.
Countermeasures (specific):

• Use a written search log (databases, search terms, time period, date of search).
• Use digital tools that make it easier for you to document your literature search.

Mini-check:

• Search log available? ✔

3.6. PMS / PMCF data are not integrated

Problem & Impact: When field data remains isolated, benefit-risk arguments become obsolete.
Countermeasures (specific):

• Define a clear process in SOPs for how PMS and PMCF results are regularly reviewed, evaluated, and fed back into the clinical assessment.
• Include sections for evaluating the PMS and PMCF results in the CER template.
• Establish a fixed sequence: First, evaluate PMS/PMCF → then update the CER so that the new data can be integrated consistently.

Mini-check:

• PSUR/PMS events are documented in the CER. ✔
• PMCF results are used to confirm or adjust clinical statements.✔
• The benefit-risk assessment is regularly updated based on current field data. ✔

3.7. No structured benefit-risk analysis

Problem & Impact: Narrative perspectives are subjective; a lack of data makes decisions difficult.
Countermeasures (specific):

• Define a fixed methodology for benefit-risk assessment, e.g., using structured tables, scoring models, or qualitative categories with clear evaluation criteria.
• Explicitly link benefit and risk parameters to clinical data, including clinical trials, literature, PMS and PMCF results.
• Document assumptions and weightings in a transparent manner so that decisions remain consistent even with updates to the CER.

Mini-check:

• Benefits and risks are clearly defined and presented in a structured comparison. ✔
• Clinical data and PMS/PMCF results are demonstrably included in the assessment. ✔
• The benefit-risk assessment is reproducible and comprehensibly reasoned. ✔

3.8. Inconsistent documents (CER vs. IFU vs. Claims/Endpoints)

Problem & Impact: Discrepancies between IFU/Marketing and CER lead to audit findings.
Countermeasures (specifically):

• Establish a systematic reconciliation process that ensures all clinical claims/endpoints in IFU, marketing materials and technical documentation are supported by the clinical evaluation.
• In the CER, define a “claim reference” that explicitly lists all essential clinical claims and links them to the underlying data.

Mini-check:

• All clinical claims/endpoints in IFU and marketing are documented and substantiated in the CER.✔
• Indication, target population, and purpose are consistent across all documents.✔

3.9. No clear clinical evaluation strategy (route missing)

Problem & Impact: Arbitrary data collection without a goal leads to gaps and unnecessary effort.
Countermeasures (specific):

• Establish the assessment route in the CEP, justify the choice with risk and data situation, and define milestones.

Mini-check:

• Assessment route documented in the CEP? ✔
• Is there a fallback plan? ✔

 4. Conclusion

Under the MDR, clinical evaluation is no longer a static final document, but rather the central, evidence-based management tool for the safety, performance, and clinical benefit of a product throughout its entire lifecycle. Errors in CEP/CER processes—such as unclear claims/endpoints, lack of reproducibility of the literature review, insufficiently substantiated equivalence assumptions, or the failure to integrate PMS/PMCF data—regularly lead to audit findings and requests for further information, weakening the defense of your claims. Many of these deficiencies can be avoided through clear processes, transparent methodology, and consistent documentation.

Key recommendations for action can be summarized thematically:

Planning & Claims/Endpoints: Begin the clinical evaluation with a complete, finalized Clinical Evaluation Plan (CEP). Define claims early and precisely (SMART: specific, measurable, traceable) and link each claim/endpoint to concrete endpoints, data sources, and acceptance criteria. The CEP phase establishes the data route (own studies, equivalence, performance data) and determines if and when a clinical investigation is required. Early involvement of the clinical lead, biostatisticians, regulatory affairs, and quality assurance prevents later plan changes and reduces regulatory risks.

Evidence Building & SoTA: Conduct a systematic, reproducible literature search and document the search protocol, inclusion/exclusion criteria, and screening process (PRISMA style). Structure the state-of-the-art analysis along measurable, clinically relevant parameters and derive benchmarks and gaps from them. Use an extracted dataset as the source of truth (numerator/denominator, follow-up, limitations), not just narrative summaries.

Methodology & Equivalence: Critically assess the quality of each data source (bias, follow-up, endpoint coherence). If you intend to use equivalence data, provide a complete, verifiable equivalence matrix covering technical, biological, and clinical comparison points; document differences and their relevance. If robust equivalence is lacking, plan an alternative evidence route (e.g., prospective cohort, PMCF).

Benefit-Risk & Traceability: Work with a data-driven benefit-risk matrix in which benefits and risks are quantified, weighted, and supported by concrete data sources. Establish a traceability matrix that links claims, endpoints, the associated studies/data, and the relevant CER, IFU, and marketing sections. This is the only way to avoid inconsistencies and quickly answer auditor questions.

PMS/PMCF Integration: PMCF and PMS are not separate "reports" but rather permanent sources of evidence for the CER. Define the workflow "PMS/PMCF → CER Update" in your SOPs. Ensure that PSUR/PMS/PMCF results automatically trigger a CER review task.

5. How we can help you

We provide pragmatic support throughout the entire clinical evaluation lifecycle—from strategic planning to audit-ready documentation. Our goal is to design your CER processes to be MDR-compliant, methodologically sound, and practically applicable. We combine regulatory expertise with practical project and study know-how to transform requirements into genuine, defensible evidence.

Specifically, we can support you with, for example:

• Gap analyses of your existing CEP/CER/PMCF documentation, including prioritized action planning.
• Creation and review of CEPs and CERs.
• Methodology decision & study design: We define endpoints, populations, statistical plans and monitoring concepts for clinical trials or PMCF studies.
• Literature review & evidence appraisal: systematic search, quality assessment and integration into the benefit-risk analysis.
• PMCF conception and implementation.

Want to know more? Contact us for a free initial consultation!

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