Category Archives: Modeling and simulation

A way to understand the pros and cons ofproposed designs before doing full-blown builds.

Process mining vs. data mining

In this post, I will try to highlight key differences between process mining and data mining, and explain why we should be paying greater attention than we currently are to the former.

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“The number” vs. outcomes of varying likelihood: gaining perspective

How many times have we heard a manager or executive say “Just give me the number!”? This request smacks of frustration and conveys an unrealistic expectation.  While this is slowly changing, single-point estimates are still the goal when making managerial projections at many healthcare providers today. In this post, I want to discuss an alternative approach.

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Optimizing distributed processes locally, and why it may not be a good idea

In healthcare, many tend to work in silos, through narrow specialization or a physical area of focus, be it the ED, an OR, the Cath Lab, Labor and Delivery, and so on. As such, staff driven to reduce harm and waste embark on process improvement (PI), frequently thinking that fixing their own workflows and work-spaces will do. This is often not the case, and bears rethinking from a broader perspective.
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