Standardized Problem List Generation, Utilizing the Mayo Canonical Vocabulary Embedded within the Unified Medical Language System

Peter L. Elkin, David N. Mohr, Mark S. Tuttle, William G. Cole, Geoffrey E. Atkin, Kevin Keck, Thomas B. Fisk, Brian H. Kaihoi, Karen E. Lee, Michael C. Higgins, H. Jaap Suermondt, Nels Olson, Paul L. Claus, Paul C. Carpenter, Christopher G. Chute

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


Vocabulary: The Mayo problem list vocabulary is a clinically derived lexicon created from the entries made to the Mayo Clinic's Master Sheet Index and the problem list entries made to the Impression/ Report/ Plan section of the Clinical Notes System over the last three years. The vocabulary was reduced by eliminating repetition including lexical variants, spelling errors, and qualifiers (Administrative or Operational terms) [1]. Qualifiers are re-coordinated with other terms, at run-time, which greatly increased the number of input strings which our system is capable of recognizing. Implementation: The Problem Manager is implemented using standard windows tools in a Windows NT environment. The interface is designed using Object Pascal. HTTP calls are passed over the World Wide Web to a UNIX based vocabulary server. The server returns a document, which is read into Object Pascal structures, parsed, filtered and displayed. Study: This paper reports the results of a recent Usability Trial focused on assessing the viability of this mechanism for standardized problem entry. Eight clinicians engaged in eleven scenarios and responded as to their satisfaction with the systems performance. These responses were observed, videotaped and tabulated. Clinicians in this study were able to find acceptable diagnoses in 91.1% of the scenarios. The response time was acceptable in 92.5% of the scenarios. The presentation of related terms was stated to be useful in at least one scenario by seven of the eight participants. All clinicians wanted to make use of shortcuts which would minimize the amount of typing necessary to encode the concept they were searching for (e.g. Abbreviations, Word Completion). Conclusions: Clinicians are willing to choose a canonical term from a suggested list (as opposed to their own wording). Clinicians want an "intelligent" system, which would suggest terms within a category (e.g. Types of "Migraine"). They are able to make functional use of our system, in its current state of development. Finally, all clinicians appreciate the value of encoding their problems in a standardized vocabulary, toward improved research, education and practice.

Original languageEnglish (US)
Pages (from-to)500-504
Number of pages5
JournalJournal of the American Medical Informatics Association
Issue numberSUPPL.
StatePublished - 1997
Externally publishedYes

ASJC Scopus subject areas

  • Health Informatics


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