Analysis of physician questions in an ambulatory care setting.
We collected 38 questions generated by physicians based on their active patient medical records. Each question was associated with a single term in a specific record (Key Term). These questions were analyzed with respect to word content and concept content. Concepts were matched to the National Library of Medicine's Metathesaurus (Meta-1). Thirty-seven Key Terms matched completely to Meta-1 terms. Each question matched to an average of 4.1 Meta-1 terms for a total of 156 concepts. Based on word count, these 156 concepts accounted for 40 percent, stop words accounted for 39 percent, and numbers and drug trade names accounted for less than 1 percent of the words. The remaining 20 percent of the words could be matched to 69 concepts not in Meta-1. Review of all concepts showed that they could be divided into medical terms (Noun Concepts), modifiers (Modifier Concepts), and concepts that provided context for the questions (Relation Concepts). The majority of Relation Concepts did not match to Meta-1. A vocabulary of Relation Concepts would provide a useful starting point for a computer system designed to aid physicians in answering clinical questions.
Cimino
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Laboratory of Computer Science, Massachusetts General Hospital, Boston 02114.
Barnett
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D000553:Ambulatory Care; D016247:Information Storage and Retrieval; D010820:Physicians; D013358:Subject Headings; D009626:Terminology as Topic; D017432:Unified Medical Language System