Paper Info
Title
Detecting earlier indicators of homelessness in the free text of medical records.
Abstract
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 nonhomeless Veterans. NLP detected mentions of either direct or indirect evidence of homelessness in a significant portion of Veterans earlier than structured data.
Year
DOI
Venue
2014
10.3233/978-1-61499-423-7-153
Studies in Health Technology and Informatics
Keywords
Field
DocType
Pattern recognition,natural language processing,homelessness
Knowledge management,Speech recognition,Natural language processing,Medical record,Artificial intelligence,Medicine
Conference
Volume
ISSN
Citations 
202
0926-9630
2
PageRank 
References 
Authors
0.64
0
7
Name
Order
Citations
PageRank
Andrew Redd1116.59
Marjorie Carter285.52
Guy Divita365.48
Shuying Shen446323.81
Miland N. Palmer551.70
Matthew H. Samore614326.07
Adi Gundlapalli74714.74