While health analytics can help improve quality outcomes, increase patient satisfaction and reduce costs, allowing healthcare organizations to draw specific actionable conclusions, they must embrace predictive analytics to realize the promise of personalized care.

The problem is that currently most healthcare organizations are extensive users of “descriptive” analytics, using reporting tools and applications to understand what has happened in the past and to classify and categorize historical, usually structured data. According to Rock Health, which funds and supports early stage healthcare companies, the industry must move to a model of “predictive” analytics—the process of learning from historical data in order to make predictions about the future, which in the case of healthcare means “enabling the best decisions to be made, allowing for care to be personalized to each individual.”

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