Objective To identify challenges in mapping internal International Classification of Disease, 9th edition, Clinical Modification (ICD-9-CM) encoded legacy data to Systematic Nomenclature of Medicine (SNOMED), using SNOMED-prescribed compositional approaches where appropriate, and to explore the mapping coverage provided by the US National Library of Medicine (NLM)'s SNOMED clinical core subset. Design This study selected ICD-CM codes that occurred at least 100 times in the organization's problem list or diagnosis data in 2008. After eliminating codes whose exact mappings were already available in UMLS, the remainder were mapped manually with software assistance. Results Of the 2194 codes, 784 (35.7%) required manual mapping. 435 of these represented concept types documented in SNOMED as deprecated: these included the qualifying phrases such as 'not elsewhere classified'. A third of the codes were composite, requiring multiple SNOMED code to map. Representing 45 composite concepts required introducing disjunction ('or') or set-difference ('without') operators, which are not currently defined in SNOMED. Only 47% of the concepts required for composition were present in the clinical core subset. Search of SNOMED for the correct concepts often required extensive application of knowledge of both English and medical synonymy. Conclusion Strategies to deal with legacy ICD data must address the issue of codes created by nontaxonomist users. The NLM core subset possibly needs augmentation with concepts from certain SNOMED hierarchies, notably qualifiers, body structures, substances/products and organisms. Concept-matching software needs to utilize query expansion strategies, but these may be effective in production settings only if a large but non-redundant SNOMED subset that minimizes the proportion of extensively pre-coordinated concepts is also available.
Nadkarni and Darer REF mapped legacy ICD-9-CM codes used at their institution to SNOMED CT.
Migrating existing clinical content from ICD-9 to SNOMED
Journal of the American Medical Informatics Association : JAMIA
Journal of the American Medical Informatics Association : JAMIA
Computer Science Medicine