General Quality Assurance Principles for Maps

Ensuring the quality of a map is a critical step in the map process, often requiring validation of initial processes and adherence to best practices such as dual mappers and reviewers, conducting consensus reviews, and establishing clear map principles.

Project Scope and Planning

The foundation for any mapping QA framework rests on a clear definition and documentation:

• Clearly defining the map's purpose and use case from the outset, since a map that is fit for analytics may not be appropriate for clinical decision support or regulatory reporting.

• Defining clear source and target terminology and version baselines, because mappings can change significantly between releases.

• Carefully consider the scope of your map and set inclusion criteria, specifying whether you are targeting procedures, diagnoses, medications, or other types of clinical concepts. In some cases, specifying a sub-hierarchy may be helpful (e.g., cardiology-related disorders).

• Document the scope and criteria clearly in your project plan to maintain focus and consistency.

Source Terminology Clarity (Pre-Mapping Review)

One way to support automatic map suggestions (e.g., using Snap2Snomed and lexical-based mapping) is by ensuring the source terms are descriptive, clear, and unambiguous:

• Avoid using acronyms, abbreviations, or jargon that may be unclear or have multiple interpretations.

• If a source term could be interpreted in multiple ways, provide additional context, such as usage examples, definitions, or notes, which can be imported as an additional column.

• Conduct a pre-map review of your source terms to identify and address any terms that may cause confusion or ambiguity.

Handling Map Relationships and Decisions

It is essential to discuss and agree on how to deal with maps that have a relationship type other than 'exact' and maps stated as 'no map':

• Aim for exact matches wherever possible.

• Distinguish between exact, broader, and narrower matches, and be explicit about how ambiguity, unmapped concepts, and one-to-many or many-to-one relationships are handled.

• Inexact Matches: Evaluate the clinical impact, relevance, and necessity of revision. Options may include adding the meaning as a SNOMED CT extension concept, selecting the most specific supertype, or refining the source code.

• No Map Decisions: Clearly define the criteria for when a term will be marked as ‘no map’.

• Maintain detailed records of all map decisions, including the rationale for inexact, broader, narrower, or ‘no map’ choices. Regularly review these entries to see if new concepts or terminology updates can resolve the map over time.

• Also consider map directionality; a map should not be simply reversed without separate validation, as map directionality can differ due to code system design (e.g., MedDRA/SNOMED).

Validation and Auditing

• Use peer review and dual review, supported by clinical and domain expert validation.

• Establishing acceptance criteria or quality metrics, for example, accuracy thresholds, inter-reviewer agreement, or sampling approaches, is necessary. A representative sample should cover: the breadth of the target terminology; the range of clinical settings (e.g., inpatient, outpatient, and primary care); high-volume data fields; and validation against ground-truth source data, not against other coded outputs.

• Ensure provenance and auditability: who created and reviewed each map, when, and using which methodology or tools.

• Check that the Edition and version match your intentions, and that all target SNOMED CT concepts are active.

• Ensure there are no duplicate EQUIVALENT rows mapping to the same SNOMED CT code, unless explicitly approved in limited and clearly defined circumstances.

Exception example: In the LOINC Part to SNOMED CT Concept Map, where COMPONENT LPs and DIVISOR LPs (e.g., COMPONENT LP14419-3 Leukocytes and DIVISOR LP157588-7 Leukocytes) are mapped to the same SNOMED concept (e.g., 52501007 |Leukocyte (cell)|).

• Where possible, testing maps against real-world workflows or datasets is recommended to confirm fitness for purpose. Initial testing can inform updates and assist in developing custom QA checks.

• Governance and ongoing maintenance, including stakeholder feedback, are required, including monitoring for terminology updates and downstream impacts as source vocabularies evolve.

SNOMED CT-Specific Map Considerations

• Map projects that target structured laboratory or analyte content (such as LOINC and NPU) lend themselves more readily to automated mapping and checks than narrative classifications such as ICD-10. Assigning ICD-10 codes, in particular, is highly idiosyncratic and depends on expert judgement.

• For SNOMED CT as the target, documenting allowed attribute values based on editorial guidance and any project-specific restrictions supports consistency between reviewers and across time.