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Improving health and healthcare institutions requires understanding of data and creation of interventions at the many levels at which health IT interact and affect the institution. These levels range from the external 鈥渨orld鈥� in which the institution operates down to the specific technologies. Data scientists find that, when they aim at implementing their models in practice, it is the 鈥渟ocio鈥� components that are both novel to them and mission critical to success. At the end of this course, students will be able to make a quick assessment of a health informatics problem鈥攐r a proposed solution鈥攁nd to determine what is missing and what more needs to be learned. Who Is This Class For? Physicians, nurses, pharmacists, social workers, and other allied health professionals interested in expanding their understanding of digital health, big data, health information systems, and the unintended consequences of disruptive innovation in the healthcare system. The course is also aimed at those with technical, engineering, or analytics backgrounds who want to understand the nuances of those topics when it comes to healthcare.