Literature DB >> 10384527

An evaluation of UMLS as a controlled terminology for the Problem List Toolkit.

H Goldberg1, D Goldsmith, V Law, K Keck, M Tuttle, C Safran.   

Abstract

We are developing a set of software components--the Problem List Toolkit (PL-Tk)--to support operations on clinical problem labels. An adaptation of the National Library of Medicine's Unified Medical Language System (UMLS) provides general vocabulary services to domain-specific software components. Our initial investigation centers on the inclusion in UMLS of problem labels used in the Beth Israel Deaconess Medical Center's Online Medical Record (OMR). We also explore the semantic typing of problem labels matched in UMLS. We have operationally defined a clinical problem to derive its semantic type from classes of terms representing findings or processes typically requiring diagnostic evaluation or therapeutic management in clinical practice. Of 1262 unique OMR problem labels, 999 terms (79%) have matches in UMLS. 986 of 999 terms (99%) map to the UMLS concept of the corresponding lexical match. 952 of 999 terms (95%) have semantic types that comply with our operational definition of clinical problems. These 952 terms (75%) constitute Version 1.0 of the problem list vocabulary B196. Matching terms with inappropriate semantic types raise issues regarding requirements for PL-Tk, typing of existing UMLS terms, and the adequacy of our operational definition for clinical problems. UMLS provides a large repertoire of pre-coordinated terms that are used as problem labels in a heavily used computer-based patient record system. The semantic type hierarchy provides a framework for the consistent use of clinical concepts in problem lists such that clinical problem labels represent "good" clinical problems.

Entities:  

Mesh:

Year:  1998        PMID: 10384527

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  5 in total

1.  Information retrieval performance of probabilistically generated, problem-specific computerized provider order entry pick-lists: a pilot study.

Authors:  Adam S Rothschild; Harold P Lehmann
Journal:  J Am Med Inform Assoc       Date:  2005-01-31       Impact factor: 4.497

2.  Automation of a problem list using natural language processing.

Authors:  Stephane Meystre; Peter J Haug
Journal:  BMC Med Inform Decis Mak       Date:  2005-08-31       Impact factor: 2.796

3.  Inter-rater agreement in physician-coded problem lists.

Authors:  Adam S Rothschild; Harold P Lehmann; George Hripcsak
Journal:  AMIA Annu Symp Proc       Date:  2005

4.  Improving the sensitivity of the problem list in an intensive care unit by using natural language processing.

Authors:  Stéphane Meystre; Peter Haug
Journal:  AMIA Annu Symp Proc       Date:  2006

5.  Extraction and mapping of drug names from free text to a standardized nomenclature.

Authors:  Matthew A Levin; Marina Krol; Ankur M Doshi; David L Reich
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11
  5 in total

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