Practice Analytics Profile: Associate Professor Rodrigo Cavalcanti

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Practice Analytics Profile: Associate Professor Rodrigo Cavalcanti

By Anna Janssen

This month the Practice Analytics Node profiles Associate Professor Rodrigo Cavalcanti. Rodrigo is Associate Professor in General Internal Medicine at the University of Toronto. His research interests include trainee competence assessment, clinical reasoning and applications of cognitive load theory in medical education.

Rodrigo was asked five quick questions about Practice Analytics:

What does practice analytics mean to you?

This is a relatively new term that refers to educational activities derived from analyzing health professional’s practice data. That means combing through a health professional’s clinical activity (much of which is captured electronically nowadays) to provide useful feedback to the clinician.  This analyzed data allows for self-reflection, benchmarking and learning.  There should be an emphasis on the last point, Practice Analytics needs to be focused on helping health professionals improve their practice through learning.

How did you get interested in practice analytics?

I have a longstanding involvement in postgraduate medical education and have a strong belief that development of expertise requires effective feedback.  Much of this is done through supervisors feedback after observation of activities, however there is a great wealth of information to be derived from the clinical activities themselves. This has been done for a while in the form of practice audits, but they were costly and time consuming. Our modern electronic data management and analysis systems have opened the door for us to do this in a much more timely and efficient way.

What excites you about the area?

The great potential to provide effective feedback to heath-care professionals and leverage their ability to improve the quality of care we deliver.

What are some of big challenges in the practice analytics areas?

There are many, some to do with institutional buy-in, some related with respecting privacy of personal health information and some to do with acceptability to practicing professionals. One last one I always emphasize is that our data will be imperfect, due to multiple contextual variables, such as patient characteristics and practice location.  However, if we focus our efforts on using practice analytics to help with individual learning that imprecision becomes less important.

What is your “blue sky” vision for the area in the next five years?

That we will be able to share real-time practice data with health professionals in a platform that meets their needs, and even more, that we can offer education that is targeted on the identified areas for improvement.  This should happen in an iterative, evolving model, so that different aspects of care can be analyzed over time and an impact on quality can be linked to these tools.

If you want to be profiled for the Practice Analytics Node of the DHIN email: jacqueline.wells@sydney.edu.au

By | 2018-06-28T11:25:53+00:00 June 28th, 2018|Categories: Blog|Tags: , , |0 Comments

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