research-article

Real time patient flow management using business process management, location tags, and complex events processing

Authors:

Omar Badreddin and

Liam PeytonAuthors Info & Claims

CASCON '13: Proceedings of the 2013 Conference of the Center for Advanced Studies on Collaborative Research

November 2013

Pages 357 - 359

Published: 18 November 2013 Publication History

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Abstract

Hospitals in North America are operating at near full or full capacity. Ageing populations are further increasing patients' inflows. These trends manifest themselves in continuously increasing patients wait time that can reach 20 hours at emergency departments [1]. Excessive wait time is both costly to patients and hospitals, increases risks to patients, and in many cases, is in conflict with medical guidelines standards.

References

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Canadian Institute for Health Information (CIHI).: Who Is Using Emergency Departments and How Long are They Waiting?. CIHI Website, ISBN: 1-55392-676-5, 2005.

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Saeed Ahmadi Behnam, Omar Badreddin, "Toward a Care Process Metamodel". ICSE Workshop on Software Engineering in Health Care, 2013.

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D. Barone, T. Topaloglou, and J. Mylopoulos, "Business Intelligence Modeling in Action: A Hospital Case Study," in Advanced Information Systems Engineering, Springer Berlin Heidelberg, 2012, pp. 502--517.

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Martin Keen; Omar Badreddin; Waveney Croson; Andy Garratt; Ben Karchner; Ines Lehmann; Frank Neumann; Lincoln Roach. Human-Centric Business Process Management with WebSphere Process Server V6. IBM Redbooks Pub., ISBN: 0738486787. IBM Forum Number: SG24-7477-00. Publish Date: 15 October 2007.

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Published In

CASCON '13: Proceedings of the 2013 Conference of the Center for Advanced Studies on Collaborative Research

November 2013

449 pages

Conference Chair:
Joanna Ng
CAS Research, IBM Canada Software Lab
,
Program Chairs:
James R. Cordy
Queen's University
,
Krzysztof Czarnecki
University of Waterloo

Publisher

IBM Corp.

United States

Publication History

Published: 18 November 2013

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Overall Acceptance Rate 24 of 90 submissions, 27%

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