Map free-text laboratory tests to validated LOINC codes with UCUM units.
npx skills add https://github.com/maziyarpanahi/openmed --skill mapping-loinc
Please help me install this Agent Skill. Skill: mapping-loinc Source: https://github.com/maziyarpanahi/openmed/tree/main/skills/mapping-loinc Command: npx skills add https://github.com/maziyarpanahi/openmed --skill mapping-loinc
This Skill resolves free-text laboratory tests and clinical observations into precise LOINC codes, helping prevent ambiguity across analytes, specimens, methods, and measurement scales.
Use the mapping-loinc skill to map each laboratory observation in the provided clinical text to a validated LOINC code with its display name and UCUM unit.
High-intent search queries and answers about installing and using this skill.
Map free-text laboratory tests to LOINC codes by applying a mapping workflow to analytes, specimens, methods, and UCUM units extracted from clinical notes. This process uses FHIR terminology search and validation to resolve precise observation codes.
Distinguish laboratory panels from individual analytes during observation mapping by evaluating the extracted specimen, method, value, and unit context. This ensures the selected LOINC code accurately reflects whether the observation is a grouped panel or a single test.
You can generate US Core Laboratory Result Observation resources with traceable source offsets by mapping clinical observations to validated LOINC codes. The output includes structured result data, canonical displays, and UCUM units compliant with FHIR standards.
You need to supply UMLS and SNOMED data separately for clinical terminology mapping. The process keeps UMLS and SNOMED data user-supplied and out-of-process, while handling LOINC data license-compliantly to ensure traceable and validated observation mapping.
FHIR terminology validation for laboratory coding works by searching and validating candidate LOINC codes through terminology services. It retrieves canonical displays and UCUM units, ensuring the mapped clinical observations are precise and disambiguated by specimen and method.
Mapping clinical observations requires specimen and method disambiguation to prevent ambiguity across analytes, specimens, methods, and measurement scales. Resolving these contextual elements ensures the final LOINC code accurately represents the specific laboratory test or vital sign.
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