Promoting interoperability between SNOMED CT and ICD-11: lessons learned from the pilot project mapping between SNOMED CT and the ICD-11 Foundation
Bibliographic record
Abstract
OBJECTIVE: To explore the feasibility and challenges of mapping between SNOMED CT and the ICD-11 Foundation in both directions, SNOMED International and the World Health Organization conducted a pilot mapping project between September 2021 and August 2022. MATERIALS AND METHODS: Phase 1 mapped ICD-11 Foundation entities from the endocrine diseases chapter, excluding malignant neoplasms, to SNOMED CT. In phase 2, SNOMED CT concepts equivalent to those covered by the ICD-11 entities in phase 1 were mapped to the ICD-11 Foundation. The goal was to identify equivalence between an ICD-11 Foundation entity and a SNOMED CT concept. Postcoordination was used for mapping to ICD-11. Each map was done twice independently, the results were compared, and discrepancies were reconciled. RESULTS: In phase 1, 59% of 637 ICD-11 Foundation entities had an exact match in SNOMED CT. In phase 2, 32% of 1893 SNOMED CT concepts had an exact match in the ICD-11 Foundation, and postcoordination added 15% of exact match. Challenges encountered included non-synonymous synonyms, mismatch in granularity, composite conditions, and residual categories. CONCLUSION: This pilot project shed light on the tremendous amount of effort required to create a map between the 2 coding systems and uncovered some common challenges. Future collaborative work between SNOMED International and WHO will likely benefit from its findings. It is recommended that the 2 organizations should clarify goals and use cases of mapping, provide adequate resources, set up a road map, and reconsider their original proposal of incorporating SNOMED CT into the ICD-11 Foundation ontology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".