Document Detail


Enhancing clinical problem lists through data mining and natural language processing.
MedLine Citation:
PMID:  18999076     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The availability of timely, accurate, comprehensive, and coded clinical problem lists is essential for supporting a range of healthcare activities. Evidence and experience suggest, however, that problem lists are frequently out-of-date, sometimes omit clinically important problems, and contain uncoded entries. Here, we describe a study being performed at Partners HealthCare System to explore automated techniques for enhancing existing problem lists.
Authors:
Elizabeth S Chen; Adam Wright; Francine L Maloney; Cheryl Van Putten; Marilyn D Paterno; Howard S Goldberg
Related Documents :
18172446 - Primer: history and examination in the assessment of musculoskeletal problems.
9112616 - On situating homophobia.
11654986 - Clinical pragmatism: a method of moral problem solving.
1397426 - Prosthetic rehabilitation in temporomandibular disorder and orofacial pain patients. cl...
15385236 - Relationships between hiv/aids, income and expenditure over time in deprived south afri...
16821036 - Self-organisation and communication in groups of simulated and physical robots.
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2008-11-06
Journal Detail:
Title:  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium     Volume:  -     ISSN:  1942-597X     ISO Abbreviation:  -     Publication Date:  2008  
Date Detail:
Created Date:  2008-11-12     Completed Date:  2010-01-08     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101209213     Medline TA:  AMIA Annu Symp Proc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  901     Citation Subset:  IM    
Affiliation:
Clinical Informatics Research & Development, Partners HealthCare System, Wellesley, MA, USA.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Algorithms
Artificial Intelligence
Information Storage and Retrieval / methods
Medical History Taking / methods*
Medical Records Systems, Computerized / organization & administration*
Medical Records, Problem-Oriented*
Natural Language Processing*
Pattern Recognition, Automated / methods*
Quality Assurance, Health Care / methods*
United States

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  A rapid assessment process for clinical informatics interventions.
Next Document:  Connecting Public Health IT Systems with Enacted Work: Report of an Ethnographic Study.