OBJECTIVE: To study existing problem list terminologies (PLTs), and to identify a subset of concepts based on standard terminologies that occur frequently in problem list data. DESIGN: Problem list terms and their usage frequencies were collected from large healthcare institutions. MEASUREMENT: The pattern of usage of the terms was analyzed. The local terms were mapped to the Unified Medical Language System (UMLS). Based on the mapped UMLS concepts, the degree of overlap between the PLTs was analyzed. RESULTS: Six institutions submitted 76,237 terms and their usage frequencies in 14 million patients. The distribution of usage was highly skewed. On average, 21% of unique terms already covered 95% of usage. The most frequently used 14,395 terms, representing the union of terms that covered 95% of usage in each institution, were exhaustively mapped to the UMLS. 13,261 terms were successfully mapped to 6776 UMLS concepts. Less frequently used terms were generally less 'mappable' to the UMLS. The mean pairwise overlap of the PLTs was only 21% (median 19%). Concepts that were shared among institutions were used eight times more often than concepts unique to one institution. A SNOMED Problem List Subset of frequently used problem list concepts was identified. CONCLUSIONS: Most of the frequently used problem list terms could be found in standard terminologies. The overlap between existing PLTs was low. The use of the SNOMED Problem List Subset will save developmental effort, reduce variability of PLTs, and enhance interoperability of problem list data.
OBJECTIVE: To study existing problem list terminologies (PLTs), and to identify a subset of concepts based on standard terminologies that occur frequently in problem list data. DESIGN: Problem list terms and their usage frequencies were collected from large healthcare institutions. MEASUREMENT: The pattern of usage of the terms was analyzed. The local terms were mapped to the Unified Medical Language System (UMLS). Based on the mapped UMLS concepts, the degree of overlap between the PLTs was analyzed. RESULTS: Six institutions submitted 76,237 terms and their usage frequencies in 14 million patients. The distribution of usage was highly skewed. On average, 21% of unique terms already covered 95% of usage. The most frequently used 14,395 terms, representing the union of terms that covered 95% of usage in each institution, were exhaustively mapped to the UMLS. 13,261 terms were successfully mapped to 6776 UMLS concepts. Less frequently used terms were generally less 'mappable' to the UMLS. The mean pairwise overlap of the PLTs was only 21% (median 19%). Concepts that were shared among institutions were used eight times more often than concepts unique to one institution. A SNOMED Problem List Subset of frequently used problem list concepts was identified. CONCLUSIONS: Most of the frequently used problem list terms could be found in standard terminologies. The overlap between existing PLTs was low. The use of the SNOMED Problem List Subset will save developmental effort, reduce variability of PLTs, and enhance interoperability of problem list data.
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