Determining non-urgent emergency room use factors from primary care data and natural language processing: a proof of concept

dc.contributor.authorSt-Maurice, Justin
dc.contributor.supervisorKuo, Hsing
dc.date.accessioned2012-03-28T20:32:37Z
dc.date.available2012-03-28T20:32:37Z
dc.date.copyright2012en_US
dc.date.issued2012-03-28
dc.degree.departmentSchool of Health Information Scienceen_US
dc.degree.levelMaster of Science M.Sc.en_US
dc.description.abstractThe objective of this study was to discover biopsychosocial concepts from primary care that were statistically related to inappropriate emergency room use by using natural language processing tools. De-identified free text was extracted from a clinic in Guelph, Ontario and analyzed with MetaMap and GATE. Over 10 million concepts were extracted from 13,836 patient records. There were 77 codes that fell within the realm of biopsychosocial, were very statistically significant (p < 0.001) and had an OR > 2.0. Thematically, these codes involved mental health and pain related biopsychosocial concepts. Similar to other literature, pain and mental health problems are seen to be important factors of inappropriate emergency room use. Despite sources error in the NLP procedure, the study demonstrates the feasibly of combining natural language processing and primary care data to analyze the issue of inappropriate emergency room use. This technique could be used to analyze other, more complex problems.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/3860
dc.languageEnglisheng
dc.language.isoenen_US
dc.rights.tempAvailable to the World Wide Weben_US
dc.subjectnatural language processingen_US
dc.subjectnlpen_US
dc.subjectprimary careen_US
dc.subjectprimary care dataen_US
dc.subjectemergency room useen_US
dc.subjectinappropriate useen_US
dc.subjectproof of concepten_US
dc.titleDetermining non-urgent emergency room use factors from primary care data and natural language processing: a proof of concepten_US
dc.typeThesisen_US

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