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Research Focus

In accordance with the three goals discussed earlier, this research will develop new methods to model, analyze, and evolve business goals (why) and business processes (what/who/when/where) based on the use of goals, scenarios, and aspects, and adapted to DW-oriented e-Health services. This will in particular lead to suitable ways of exploiting the DW for trends and goal-driven decision support, and allow us to determine how the right data can be made available by the right individuals in the chain of care at the right level of detail, and how this data can best be accessed.

This combination of complementary approaches is novel and builds on recent developments in requirements engineering, decision support, business process modeling, and business intelligence. How to combine, tailor, exploit and extend the existing tools and techniques represents an important research challenge. This research is much needed in a provincial healthcare sector where business processes are continuously renewed and changing. It is also timely as the healthcare sector recently benefited from large investments in IT infrastructures and must now seize the opportunity to evolve its processes around them.

As an example, Canadian research has demonstrated that 1 in 10 patients treated in teaching hospitals will experience a complication caused by their treatment. One-third of these so-called adverse events are due to preventable errors that staggeringly raise the cost of caring for patients while worsening their well-being. One obstacle to preventing complications is systematically measuring them, and this is not well supported by processes in place. Goals and priorities are difficult to identify. However, some routinely collected hospital data can be used to infer several complications (e.g., prescriptions of naloxone ==> morphine overdose). A DW can help discovering, validating, and tracking complication triggers, leading to better processes for their identification and measurement, and to the design of effective interventions [2].

This research project will offer a rich and stimulating learning environment for nine graduate students, in a collaborative multidisciplinary context. In addition, we expect the expertise and the experience developed to be transferable to our industrial research partners.

-- Daniel Amyot - 03 Feb 2006

Topic revision: r1 - 03 Feb 2006 - 12:42:49 - Daniel Amyot
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