Document Detail


Detecting earlier indicators of homelessness in the free text of medical records.
MedLine Citation:
PMID:  25000039     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
Early warning indicators to identify US Veterans at risk of homelessness are currently only inferred from administrative data. References to indicators of risk or instances of homelessness in the free text of medical notes written by Department of Veterans Affairs (VA) providers may precede formal identification of Veterans as being homeless. This represents a potentially untapped resource for early identification. Using natural language processing (NLP), we investigated the idea that concepts related to homelessness written in the free text of the medical record precede the identification of homelessness by administrative data. We found that homeless Veterans were much higher utilizers of VA resources producing approximately 12 times as many documents as non-homeless Veterans. NLP detected mentions of either direct or indirect evidence of homelessness in a significant portion of Veterans earlier than structured data.
Authors:
Andrew Redd; Marjorie Carter; Guy Divita; Shuying Shen; Miland Palmer; Matthew Samore; Adi V Gundlapalli
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Studies in health technology and informatics     Volume:  202     ISSN:  0926-9630     ISO Abbreviation:  Stud Health Technol Inform     Publication Date:  2014  
Date Detail:
Created Date:  2014-07-08     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9214582     Medline TA:  Stud Health Technol Inform     Country:  Netherlands    
Other Details:
Languages:  eng     Pagination:  153-6     Citation Subset:  T    
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