Catching up with the “What medicine can learn from Wall St. ” Series

The “What medicine can learn from Wall Street” series is getting a bit voluminous, so here’s a quick recap of where we are up to so far:

Part 1 – History of analytics – a broad overview which reviews the lagged growth of analytics driven by increasing computational power.

Part 2 – Evolution of data analysis – correlates specific computing developments with analytic methods and discusses pitfalls.

Part 3 – The dynamics of time – compares and contrasts the opposite roles and effects of time in medicine and trading.

Part 4 – Portfolio management and complex systems – lessons learned from complex systems management that apply to healthcare.

Part 5 – RCM, predictive analytics, and competing algorithms – develops the concept of competing algorithms.

Part 6 – Systems are algorithms – discusses ensembling in analytics and relates operations to software.


 

What are the main themes of the series?

1.  That healthcare lags behind wall street in computation, efficiency, and productivity; and that we can learn where healthcare is going by studying Wall Street.

2.  That increasing computational power allows for more accurate analytics, with a lag.  This shows up first in descriptive analytics, then allows for predictive analytics.

3.  That overfitting data and faulty analysis can be dangerous and lead to unwanted effects.

4.  That time is a friend in medicine, and an enemy on Wall Street.

5.  That complex systems behave complexly, and modifying a sub-process without considering its effect upon other processes may have “unintended consequences.”

6.  That we compete through systems and processes – and ignore that at our peril as the better algorithm wins.

7.  That systems are algorithms – whether soft or hard coded – and we can ensemble our algorithms to make them better.


 

Where are we going from here?

– A look at employment trends on Wall Street over the last 40 years and what it means for healthcare.

– More emphasis on the evolution from descriptive analytics to predictive analytics to proscriptive analytics.

– A discussion for management on how analytics and operations can interface with finance and care delivery to increase competitiveness of a hospital system.

– Finally, tying it all together and looking towards the future.

 

All the best to you and yours and great wishes for 2016!