Automatic message triage: a decision support system for patient-provider messages

Tavasoli, Amir; Archer, Norman P.; McMaster eBusiness Research Centre (MeRC)

Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/5312

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DC Field	Value	Language
dc.contributor.author	Tavasoli, Amir	en_US
dc.contributor.author	Archer, Norman P.	en_US
dc.contributor.author	McMaster eBusiness Research Centre (MeRC)	en_US
dc.date.accessioned	2014-06-17T20:44:22Z	-
dc.date.available	2014-06-17T20:44:22Z	-
dc.date.created	2013-12-23	en_US
dc.date.issued	2012-08	en_US
dc.identifier.other	merc/1	en_US
dc.identifier.other	1000	en_US
dc.identifier.other	4943335	en_US
dc.identifier.uri	http://hdl.handle.net/11375/5312	-
dc.description	<p>1 v. (unpaged) ; Includes bibliographical references. ; "August 2012."</p> <p>This work was developed based on a thesis titled "Automatic Message Triage" submitted to School of Graduate Studies at McMaster University by the primary author in partial fulfillment of the requirements for the M.Sc. Degree in Computer Science. The second author of this work supervised the development of the thesis and this article.</p> <p>This research was supported through a grant from the Natural Sciences and Engineering Council of Canada. The authors would like to acknowledge the cooperation of the MyOSCAR research team in the Department of Family Medicine at McMaster University, including Dr. David Chan, Christine Rodrigues, and Dr. Lisa Dolovich, for providing the patient messages, triage levels, help in triaging the messages. Their help is greatly appreciated.</p>	en_US
dc.description.abstract	<p><em>Background:</em> Email communication between patients and healthcare providers is gammg popularity. However, healthcare providers are concerned about being inundated with patient messages and their inability to respond to messages in a timely manner. This work provides a text mining decision support system to overcome some of the challenges presented by email communication between patients and healthcare providers.</p> <p><em>Method:</em> A decision support system based on text mining algorithms was developed and tested to triage real world email messages into medium and highly urgent messages that are routed to health provider staff, or low urgency messages that could be routed to an automated response system, responding to the messages in a timely and appropriate way.</p> <p><em>Results</em>: Due to the length of email messages, feature reduction algorithms are inadequate in this context. Therefore, in this work, several different classifiers were combined and tailored to build a high performance classifier that supports this type of classification. The system was tested and proved to perform well with real-world patient messages that were exchanged with healthcare providers during a hypertension management study.</p>	en_US
dc.relation.ispartofseries	MeRC working paper	en_US
dc.relation.ispartofseries	no. 42	en_US
dc.subject	Text mining	en_US
dc.subject	Classification	en_US
dc.subject	Triage	en_US
dc.subject	Personal health records	en_US
dc.subject	Information systems	en_US
dc.subject	Decision support systems	en_US
dc.subject	Business	en_US
dc.subject	E-Commerce	en_US
dc.subject	Health and medical administration	en_US
dc.subject	Health information technology	en_US
dc.subject	Medicine and health sciences	en_US
dc.subject	Business	en_US
dc.subject.lcc	Electronic mail messages	en_US
dc.subject.lcc	User interfaces (Computer systems)	-
dc.subject.lcc	Physician and patient	-
dc.title	Automatic message triage: a decision support system for patient-provider messages	en_US
dc.type	article	en_US
Appears in Collections:	MeRC (McMaster eBusiness Research Centre) Working Paper Series

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