Do I need an external interface terminology to implement SNOMED CT?

Collection: Implementation dilemmas

Summary: No, as a general approach, SNOMED CT does not require an external interface terminology to be implemented in clinical settings. SNOMED CT descriptions function as interface terminology, and clinical projects in member countries submit requirements and updates to improve this resource's quality continuously.

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Implementation dilemma

Some SNOMED CT implementers consider whether it is necessary to use an external interface terminology, i.e., a list of clinical terms specially designed to facilitate data entry. Each term would be mapped to SNOMED CT. The goal of using custom interface terminology is to have more control over the terms presented to the user, intending to provide a better fit for the local context.

What's an external interface terminology?

Custom interface terminologies offer a separate set of terms that can match user search strings and are directly mapped to SNOMED concepts. These custom terminologies can include terms that do not adhere strictly to SNOMED naming conventions, such as local terms, jargon, typos, etc. Maintaining a custom interface terminology requires great effort and dedication to keep current and ensure the best quality.

To what extent is a custom interface terminology required when integrating SNOMED CT into clinical systems?

Advice

The recommended approach in modern SNOMED CT implementations is to use SNOMED descriptions as the interface terminology.

The separation of "interface" and "reference" terminology roles has been reviewed in many articles¹, where the interface terminology is used to collect information, and the Reference Terminology is used to represent the information with the greatest possible level of detail and its relationships to other concepts. An antecedent version of SNOMED from 1997 was denominated SNOMED RT (Reference Terminology), describing the intended role of that version of the terminology. However, the next generation of SNOMED terminologies, the one we use today, was released in 2001 and includes specially designed interface terminology functions.

Today, SNOMED CT is implemented worldwide using its native interface terminology features for data entry without requiring an external interface terminology. The June 2024 International Edition contains 1.6 million active descriptions for 368,000 active concepts, averaging 4.4 descriptions per concept². SNOMED terms have a clinical level of detail, including wording as submitted by clinicians in member countries. Members and affiliates can add additional terms as required in national or local extensions. Using best practice text matching algorithms supports partial matching and meaningful sorting, which facilitates clinicians' search by parts of clinical terms. The best matches are properly shown first in the results, facilitating identification and selection.

Clinicians can search for SNOMED CT concepts using text searches that match the descriptions provided in the International Edition or any SNOMED Extension.

Table 1: Example of native SNOMED CT interface terminology features

Concept Id	Term	Description ID
22298006	Myocardial infarction (disorder)	751689013
	Myocardial infarction	37436014
	Cardiac infarction	37442013
	Heart attack	37443015
	Infarction of heart	37441018
	MI - myocardial infarction	3726632018
	Myocardial infarct	1784873012
406506008	Attention deficit hyperactivity disorder (disorder)	2150336014
	Attention deficit hyperactivity disorder	2158158016
	ADHD - Attention deficit disorder with hyperactivity	2163260014
	Attention deficit hyperkinetic disorder	2163265016
	Hyperkinetic disorder	2163261013
	Hyperkinetic syndrome	2163262018
	MBD - Minimal brain dysfunction	2163266015
	Minimal brain dysfunction	2163263011
	Overactive child syndrome	2163264017

Custom interface terminologies are usually incomplete and map only to a part of SNOMED CT. They are challenging to maintain and keep up to date with new SNOMED versions, with risks of quality issues like duplication and ambiguity. Users who access SNOMED content through interface terminology will experience the continuous improvements and enhancements published monthly in SNOMED releases only when those are reflected in the custom terminology. The SNOMED release is prepared to be imported into standard terminology servers supporting effective search engines. Maintaining additional synonyms as part of an extension of SNOMED CT provides many benefits for seamless integration with SNOMED updates and integrations in clinical systems.

Local or custom interface terminologies can play a role in migrating systems to SNOMED CT. Some systems may need more flexibility to incorporate full use of standard terminology services, or the clinical user base could be inclined to continue coding with a local set of terms. However, it is recommended that this be an interim solution until the system is upgraded to support full access to SNOMED CT content directly, unlocking the complete breadth of content in SNOMED CT for data entry.

Modern SNOMED CT is a global collaborative terminology system with over 50 member countries actively contributing to its development. These countries prioritize development areas, submit new content, and shape a unified health language. Accessing SNOMED CT content solely through an external interface terminology will restrict access to continually updated content and ongoing improvements.

Tips for best results implementing direct data entry with SNOMED CT

• Focus on creating the best possible terminology bindings: use value sets or ECL (the Expressions Constraint Language) to ensure that only the right concepts are available for data entry

• Use a terminology server for out-of-the-box best-practice text-matching algorithms or implement these algorithms locally³

• Train clinical users on how the multiple prefixes, no order, string matching technique works.

• Include local synonyms as new descriptions on a local extension, or submit synonyms requests to national or international editions.

• Consider the use of a local synonyms table for pre-normalization of search terms.

• Implement advanced NLP or AI matching to compensate for spelling errors ("Did you mean...?)

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References

1. Rosenbloom ST, Miller RA, Johnson KB, Elkin PL, Brown SH. Interface terminologies: facilitating direct entry of clinical data into electronic health record systems. J Am Med Inform Assoc. 2006 May-Jun;13(3):277-88. doi: 10.1197/jamia.M1957. Epub 2006 Feb 24. PMID: 16501181; PMCID: PMC1513664.

2. SNOMED Release Statistics: https://browser.ihtsdotools.org/qa/#/SNOMEDCT/general-release-statistics

3. https://www.implementation.snomed.org/terminology-services

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