Now coming to the topic, the headline of the article, data science can answer a lot of these questions. Every player in the healthcare industry needs to build on innovative statistical insight generating engine that will essentially nudge them in keeping a tab on the proceedings and also in making smarter decisions. A doctor, for example, should be able to view the entire history of a patient while providing better care. He should be able to view the risk associated with the patient beforehand. An ACO should be able to track the government defined measures to keep a view on the measures for which incentives are linked. They should be able to identify the providers who are performing at par and bring in the best practices in play for the other providers and help them catch up. Innovative solutions to predict the length of stay of incoming patients will help them manage operations effectively. Knowing the likelihood of a readmission of a patient at the time of discharge would help them keep readmission levels down. 

Now let us take a view on what is happening in big data space. The word has been around for not so long but has created a lot of noise. To better answer what is happening in big data space let us head back to what was happening in data space a couple of decades back. As far as I can recall, the 1990s was when companies were aggressively trying to shift the manner in which they stored data. From a paper-based collection to a more digital format. The companies hired engineers to develop custom applications to structurally store the data and build reporting engines on top of them. Then came a time in the late 1990s and early 2000 when IT companies like oracle, IBM, SAP started to understand the common structure of data and the reporting needed in different verticals. I call it the productization phase of IT applications. This was also the time when we experienced the exponential growth in increasing processing power and decreasing data storage space that gave a massive rise to the bulk of data ready to be processed.

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