Abstract
In the past, medicine has been primarily a reactive field. When we are faced with a disease, we treat it; if the pain gets worse, we alleviate it; when someone stops breathing, we resuscitate them. One of the aims in predictive analytics in healthcare is to diagnose problems in an early stage of development (or even before they occur at all), before they have had a chance to take a toll on the human body. But the role of predictive analytics does not stop once the individual develops the disease. Another aim of predictive analytics is to guide in selecting and tailoring treatments for individuals by predicting the course of events that is likely to occur with every treatment option that is available. Of course these concepts apply not only to individuals but to populations, and by using predictive analytics we can foresee public health threats and take the necessary steps to lessen their burden or prevent them from happening at all. These ideas are the overriding philosophy of this chapter, as we cover the main topics of medical informatics and how they relate to accomplishing this move to proactive healthcare.
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