J Am Med Inform Assoc - A multi-part matching strategy for mapping LOINC with laboratory terminologies.

Tópicos

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Resumo

JECTIVE: To address the problem of mapping local laboratory terminologies to Logical Observation Identifiers Names and Codes (LOINC). To study different ontology matching algorithms and investigate how the probability of term combinations in LOINC helps to increase match quality and reduce manual effort.MATERIALS AND METHODS: We proposed two matching strategies: full name and multi-part. The multi-part approach also considers the occurrence probability of combined concept parts. It can further recommend possible combinations of concept parts to allow more local terms to be mapped. Three real-world laboratory databases from Taiwanese hospitals were used to validate the proposed strategies with respect to different quality measures and execution run time. A comparison with the commonly used tool, Regenstrief LOINC Mapping Assistant (RELMA) Lab Auto Mapper (LAM), was also carried out.RESULTS: The new multi-part strategy yields the best match quality, with F-measure values between 89% and 96%. It can automatically match 70-85% of the laboratory terminologies to LOINC. The recommendation step can further propose mapping to (proposed) LOINC concepts for 9-20% of the local terminology concepts. On average, 91% of the local terminology concepts can be correctly mapped to existing or newly proposed LOINC concepts.CONCLUSIONS: The mapping quality of the multi-part strategy is significantly better than that of LAM. It enables domain experts to perform LOINC matching with little manual work. The probability of term combinations proved to be a valuable strategy for increasing the quality of match results, providing recommendations for proposed LOINC conepts, and decreasing the run time for match processing.

Resumo Limpo

jectiv address problem map local laboratori terminolog logic observ identifi name code loinc studi differ ontolog match algorithm investig probabl term combin loinc help increas match qualiti reduc manual effortmateri method propos two match strategi full name multipart multipart approach also consid occurr probabl combin concept part can recommend possibl combin concept part allow local term map three realworld laboratori databas taiwanes hospit use valid propos strategi respect differ qualiti measur execut run time comparison common use tool regenstrief loinc map assist relma lab auto mapper lam also carri outresult new multipart strategi yield best match qualiti fmeasur valu can automat match laboratori terminolog loinc recommend step can propos map propos loinc concept local terminolog concept averag local terminolog concept can correct map exist newli propos loinc conceptsconclus map qualiti multipart strategi signific better lam enabl domain expert perform loinc match littl manual work probabl term combin prove valuabl strategi increas qualiti match result provid recommend propos loinc conept decreas run time match process

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