Repository logo

Supporting Pathology Process Management with Real-time Business Intelligence

dc.contributor.authorLi, Wei Chen
dc.contributor.supervisorLessard, Lysanne
dc.contributor.supervisorMichalowski, Wojtek
dc.contributor.supervisorAmyot, Daniel
dc.date.accessioned2016-11-03T17:06:10Z
dc.date.available2016-11-03T17:06:10Z
dc.date.issued2016
dc.description.abstract[Context] Clinical pathology is a medical specialty that uses laboratory analysis of tissues and fluids to diagnose diseases. As emerging methodologies and technologies extend their realm to anatomical pathology, pathology facilities are faced with new challenges related to the increasing volume and complexity of patient cases in their work processes. [Problem] Existing tools that monitor process data show limitations in supporting pathology process management. They lack the capability of identifying emerging process bottlenecks in a real-time manner, and this prevents facility managers from conducting corrective actions proactively. [Methodology] Applying the Design Science Research Methodology, this thesis proposes and builds a Business Intelligence solution that provides visual analysis and real-time monitoring functions to support pathology process management. A usability study with expert participants from the Eastern Ontario Regional Laboratory Association was conducted to validate this solution. [Results] The proposed solution meets the requirements of the experts and can provide efficient, flexible, and multi-tenancy support to users in the context of their daily professional activities.en
dc.identifier.urihttp://hdl.handle.net/10393/35329
dc.identifier.urihttp://dx.doi.org/10.20381/ruor-287
dc.language.isoenen
dc.publisherUniversité d'Ottawa / University of Ottawaen
dc.subjectdashboarden
dc.subjectBusiness Intelligenceen
dc.subjectpathology process managementen
dc.subjectpathology informaticsen
dc.titleSupporting Pathology Process Management with Real-time Business Intelligenceen
dc.typeThesisen
thesis.degree.disciplineGénie / Engineeringen
thesis.degree.levelMastersen
thesis.degree.nameMCSen
uottawa.departmentScience informatique et génie électrique / Electrical Engineering and Computer Scienceen

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail ImageThumbnail Image
Name:
Li_Wei_Chen_2016_thesis.pdf
Size:
3.39 MB
Format:
Adobe Portable Document Format
Description:

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail ImageThumbnail Image
Name:
license.txt
Size:
6.65 KB
Format:
Item-specific license agreed upon to submission
Description: