Dr Bellin is an authority on how to do predictive analytics on historical patient data. He has been doing it for over 20 years. This video is one in a series of video he produced. He also wrote the book Riddles in Accountable Healthcare: A Primer to Develop Analytic Intuition for Medical Homes and Population Health. This book is a critical read for anyone trying to understand how to do predictive analytics on historical patient data.
I blog about world of Data Science with Visualization, Big Data, Analytics, Sabermetrics, Predictive HealthCare, Quant Finance, and Marketing Analytics using the R language.
Wednesday, May 20, 2015
The Importance of Time when Building Cohort for Healthcare Data
In Temporal Relativity in Cohort Builds video Dr Eran Bellin explains this important feature in correctly build a cohort. The simple fact is that doing this correctly can produce very different results than doing this incorrectly. As Dr Bellin says himself,"It is important to understand the temporal relationships between condition lines used to build a cohort. Further, the index event line is especially important to identify the condition line whose event is going to define the index date of the cohort. By recapitulating a study from the medical literature we will demonstrate how a temporally aware cohort object is built."
Dr Bellin is an authority on how to do predictive analytics on historical patient data. He has been doing it for over 20 years. This video is one in a series of video he produced. He also wrote the book Riddles in Accountable Healthcare: A Primer to Develop Analytic Intuition for Medical Homes and Population Health. This book is a critical read for anyone trying to understand how to do predictive analytics on historical patient data.
Dr Bellin is an authority on how to do predictive analytics on historical patient data. He has been doing it for over 20 years. This video is one in a series of video he produced. He also wrote the book Riddles in Accountable Healthcare: A Primer to Develop Analytic Intuition for Medical Homes and Population Health. This book is a critical read for anyone trying to understand how to do predictive analytics on historical patient data.
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