Data Analytics and Population Health – Keys to the Transition to Payment for Quality and Cost Effectiveness

By: Paul R. DeMuro

In 1854, John Snow helped solve a public health problem by concluding that the cause of cholera in London was primarily from people drinking water from the pump on Broad Street which had the bacterium that caused cholera. He interviewed people, drew a map with black marks for each death and concluded that the center of the affected area was the Broad Street pump. The brewery workers across the street from the pump were by and large fine as they drank the liquor provided by their employer and generally did not drink water from the pump.

What does John Snow have to do with Population Health, particularly today? Well, his finding of epidemiology as a field of modern sciences used data analytics. Dr. Snow did not know about Big Data, Data Analytics, Precision or Personalized Medicine, and Predictive Analytics. He did not have a personal computer, a laptop, or even a smart phone. He painstakingly interviewed people, drew a map, and tested his theories.

Much of Dr. Snow’s work is relevant to the Population Health of today, Data Analytics, and Predictive Analytics. Dr. Snow was concerned with the health of the population. He used a form of data analytics to determine the cause of cholera for the individuals who contracted it. He was able to predict who would get cholera.

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