When the translation cycle has ended, there are several ways to enhance the quality. First and foremost, feedback mechanisms should be facilitated. Also, the NRC could take initiatives based on text analysis to ensure that the descriptions are in alignment with the actual usage among specialists.

Results of this process may be:

• target language synonyms are proposed and added
• a change to the preferred term is proposed
• a new concept is proposed
• a concept is not used in clinical practice or should be inactivated

6.1 Feedback mechanisms 

The NRC should establish an infrastructure where end users can give feedback on issues like misspellings, missing synonyms, acceptability changes or even translation errors. This infrastructure could be a portal based on tickets which allows for queuing, prioritising and communication between the user and the NRC. Several countries are using a submission portal, e.g. Norway and the Netherlands. A decision on who should be granted the rights to submit issues, has to be decided: Open feedback or restricted to licence holders, for example. Also, the users should be able to access the translation guidelines and - where applicable - the principle decisions (see chapter 5).

The feedback infrastructure could also be made available through the national SNOMED CT Browser. In the Swedish edition the functionality of a Concept Feedback button is activated in the interface of each concept entry in the browser. The button gives access to a feedback form, which will be sent to the Swedish NRC when completed.

Feedback can also be a part of a strategy to reach out to users in the clinical and social care setting. The German translation is based on community based feedback from users from countries such as Germany, Austria and Switzerland. Such crowdsourcing could also be performed at a more local level, like a hospital, which was the case of the Spanish translation during a period. 

6.2 Text analysis

If there are medical text corpora available in the target language, it is possible to perform text analysis to improve the quality of the translation. Analysing genres such as casuistics or medical journal articles could provide a list of terms being used frequently by medical experts. The Norwegian NRC is exploring how automatic extraction of terms in such texts can be performed to check whether terms are missing in the translations. This can be done in collaboration with academic institutions as it requires specific tools. 

This approach is an inversion of using text corpora and text analysis during the translation and validation process. The point of departure are terms being used in texts, not identifying translated terms representing the concept during the translation process.