An Integrated Approach using Process Models and Business Analytics for Efficient Delivery of Patient Care

The use of business process modeling (BPM) and analytics has demonstrated exceptional results in improving efficiency and effectiveness in various industries. Health care processes however, are characterized by uncertain, exception and continual evolution. This project aims to apply flexible, adaptive and evolutionary process modeling protocols coupled with operations research and other analytic methods to the health care environment. The overall goal is to develop an application framework that consists of specific BPM methods, a reference architecture for different technologies that might be used in different health care environments to support BPM, and a slate of analytic models that enable better insight into process improvement. The partner organization benefits through the exploration of different ways of applying its technologies, and the interaction that emerges between interns, healthcare professionals, and representatives from the partner organization.

Faculty Supervisor:

Daniel Amyot, Liam Peyton Craig Kuziemsky, Wojtek Michalowski, Bijan Raahemi, Gregory Richards


Kavya Mallur, Rachel Ozer, Javier Fallos, Fadwa Alazab


IBM Canada


Engineering - computer / electrical


Information and communications technologies


University of Ottawa



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