A major challenge in healthcare is to develop “precision” medicine: delivery of personalized interventions tailored precisely to each individual’s specific personal needs. We will use “big data” analyses as a new tool in healthcare for delivering personalized decision support. We illustrate this for Parkinson’s disease (PD), a disabling chronic condition. Specifically, we will explore a worldwide unique big data set (from large, real-life populations) with 3 main aims: (1) to develop a fine-grained decision support system that offers a personalized prognosis and treatment prediction; (2) to examine how this expert system can support clinicians who are not an expert in treating PD, allowing them to approach the decision qualities of experienced clinicians; and (3) to evaluate how this approach can facilitate patients in decision making, so they receive treatments tailored to their specific needs. Collectively, this innovative approach creates a new knowledge-driven basis for reforming healthcare into personalized medicine, and establishes the level of precision and expertise that is needed to optimize health for patients and reduce societal costs.

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