Clinical Evaluation Plan
The Clinical Evaluation Plan defines methods for creating and updating the Clinical Evaluation Report. This plan is updated regularly, e.g. to include new search criteria for the literature search.
While the content of the Clinical Evaluation is simple, writing it, coming up with the right structure and forming a sensible line of reasoning (equivalence) can be a bit tricky.
These are the guidance documents on Clinical Evaluation. If you’re the person writing it, you should read them:
- MDCG 2020-1, 2020-5, 2020-6
- MDCG 2020-13: Quite helpful as it gives you an idea of the structure.
- MEDDEV 2.7.1 rev. 4. (mostly for MDD, but still a good starting point; especially the list of proposed headings for a report at the end of the document).
1. Relevant Documents
- SOP Clinical Evaluation
- Clinical Evaluation Report
- Name: <product name>
- Version: <product version>
- Basic UDI-DI: <insert UDI-DI, if/when available>
Describe the roles of people who will be doing the Clinical Evaluation.
- Literature search
- Evaluation of complaints, customer feedback
2. Scope of the Clinical Evaluation
Note: This section will be copy-pasted into the Clinical Evaluation Report
2.1 Device Description
Copy-paste your Device Description (which includes the Intended Use) here. If it’s not done yet, remember to do it later :)
2.2 Clinical Benefits, Outcome Parameters
Describe the clinical benefits you expect from your product. Define how you’ll measure those (outcome parameters). You’ll probably be planning to do a literature search to prove them - as you know the literature, it makes sense to select outcome parameters which were already established in prior studies.
Also describe the product claims as stated by MEDDEV 2/7.1 Rev. 4, as stated there: Medical device claims results from general requirements on safety and performance. These claims are part of materials (e. g. IFU, marketing material and other accompanying documents). These product claims will be checked within the clinical evaluation and evidence are made. e.g.
- diagnosis for better treatment decision (performance)
- xy % accuracy, xy % sensitivity, xy % specificity
2.3 Clinical Safety, Methods for Analysis
Describe your safety parameters, i.e. which things should you product fulfil so that you consider it safe? And your methods, i.e. how will you prove that your product fulfils those safety parameters? A method could be literature search for past studies, but you could additionally do a Post-Market Clinical Follow-Up to double-check whether that’s actually true for your device.
2.4 Acceptability of Benefit-Risk-Ratio
After you’ve defined your benefits and safety parameters, which combination of those is acceptable to you? In the case of most software devices (and apps), you’ll probably have subtle benefits (e.g. better disease management, early detection of relapses) while low safety concerns (e.g. disease progression unlikely, not killing anyone).
3. Type of Evaluation
Describe the type of Clinical Evaluation you’ll be doing. In 99% of cases as a startup, you’ll be claiming equivalence to an already-certified (CE marked) device. You’ll have some methodology for searching for such a device. If you need some inspiration, check out the FDA 510k database for FDA-approved devices which claim equivalence to an already-certified device. Those are usually good to compare clinical and technical features and demonstrate equivalence :)
And based on that, you’ll be doing a literature search to come up with adequate clinical data.
4. Literature Search
4.1 Literature Search Methods
Describe your literature search methods: The databases you’ll be using (PubMed, Google Scholar, Cochrane, Embase), the keywords you’ll be entering and how you plan to document it (you’ll be creating a table, I suppose).
I blindly copy-pasted some semi-helpful bullet points from guidance documents here:
- The adequacy of search terms: for example, it should be sufficiently broad to establish benchmarks, determine the general state of the art, determine potential risk, adverse events, undesirable side-effects, etc.
- Note that a search which is restricted to the manufacturer’s own product or the name of their chosen equivalent could miss important information and therefore is not acceptable.
- Databases used (to minimize bias multiple databases should be used).
- Acceptability of inclusion and exclusion criteria.
- Both favourable and unfavourable data included.
- Strategies for avoiding duplication of data (for example, across different publications or between manufacturer and published data).
- Literature search and review protocol (i.e. how did the manufacturer test this protocol to ensure comprehensive identification of relevant data / demonstrate that all relevant data has been retrieved?).
- Any deviations from the manufacturer’s literature search protocol.
- Overall conclusions regarding the adequacy of search methods, likelihood of having retrieved all relevant data, and methods used to avoid bias.
It makes sense to differentiate between “context” and “pivotal” data:
- context data describes the state of the art (commonly the introduction / literature part of papers)
- pivotal data is used for the appraisal, i.e. that’s the data describing the actual study and outcome(s). In the best case, the pivotal data is about the actual device you’re claiming equivalence to.
4.2 Literature Appraisal Criteria
Describe your criteria for clinical data which you deem acceptable for you clinical evaluation. Firstly, the information should be relevant, secondly, you’ll probably have some additional hard criteria, like requirements for the study design etc.
Also: How will you weigh the information from multiple studies?
You can evaluate the appraisal of pivotal data by considering the equivalence of the described device literature (e.g. material & methods part, algorithm, models); the level of evidence can be taken from different sources (LoE of American heart association or quality of clinical data according to MDCG Guideline 2020-6).
4.3 Additional Databases
You can also check out additional databases for relevant data and mention how you search them:
- Clinical trials: clinicaltrail.gov, DRKS, WHO, ANZCTR
- Adverse events: EUDAMED (if it works), FDA MAUDE, FDA Medical Device Recalls
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