Medical problem list automation using natural language processing

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Title Medical problem list automation using natural language processing
Publication Type dissertation
School or College School of Medicine
Department Biomedical Informatics
Author Meystre, St©phane M.
Date 2005-08
Description The electronic problem-oriented medical record was conceived to alleviate limitations of the paper-based medical record, and to improve its organization. The list of medical problems is at the heart of this problem-oriented record, and requires completeness, accuracy and timeliness to fulfill this central role. At Intermountain Health Care (IHC), a problem-oriented electronic medical record is being developed, and features a medical problem list at its core. This list is already in use in the outpatient setting, but is often incomplete, inaccurate and out-of-date. This issue is even more prominent for hospitalized patients. To help maintain a complete, accurate and timely problem list, I developed an Automated Problem List system using Natural Language Processing (NLP) to extract potential medical problems from the patient's electronic clinical documents. These problems are proposed to the user for inclusion in the "official" problem list, along with a link to allow viewing the documents the problem was extracted from. Two main applications compose this system. A background application does all documents processing and analysis using NLP, and the problem list management application allows viewing and editing these proposed problems. In the development of this system, the NLP module of the background application was evaluated first. This laboratory function study showed good recall and satisfying precision; accuracy was further improved by enhancing disambiguation and negation detection. A second study prospectively evaluated the whole Automated Problem List system in a clinical setting at the LDS Hospital. Patients benefiting from this system had more complete and timely problem lists. The sensitivity was higher, and the time between a medical problem's first mention in a clinical document and its addition to the list of problems was significantly reduced. In summary, this dissertation describes the planning, development, implementation and evaluation of a system using NLP to automatically extract medical problems from electronic clinical documents. This Automated Problem List system allowed better quality content of the problem list, opening doors to larger scale use of this system and contributing to possible answers to the challenge of making the problem list a cornerstone of our evolving clinical information system.
Type Text
Publisher University of Utah
Subject Utah, LDS Hospital
Subject MESH Medical Records Systems, Computerized
Dissertation Institution University of Utah
Dissertation Name PhD
Language eng
Relation is Version of Digital reproduction of "Medical problem list automation using natural language processing." Spencer S. Eccles Health Sciences Library. Print version of "Medical problem list automation using natural language processing." available at J. Willard Marriott Library Special Collection. RA4.5 2005 .M49.
Rights Management © Stéphane M. Meystre.
Format application/pdf
Format Medium application/pdf
Format Extent 2,682,863 bytes
Identifier undthes,4674
Source Original: University of Utah Spencer S. Eccles Health Sciences Library (no longer available).
Master File Extent 2,682,902 bytes
ARK ark:/87278/s60c4xhq
Setname ir_etd
ID 190963
Reference URL https://collections.lib.utah.edu/ark:/87278/s60c4xhq
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