Data is accumulating faster than health-care decision-makers can make use of it. A new generation of machine-learning powered predictive models, contextual decision support, and process automation can help deliver concise, actionable insights to strategic, clinical, and operational decision-makers. Advanced analytical techniques depend on a mature foundational business intelligence program, including flexible data architecture, consistent data governance, and a culture of data-driven decision making.

In this on-demand webcast, presented by The Advisory Board, we explore how health care organizations can utilize new data sources to help cut costs and solve common industry issues.

Andrew Rebhan, Consultant, The Advisory Board

Andrew Rebhan is a consultant with Advisory Board's Health Care IT Advisor. Andrew’s research interests include artificial intelligence, consumer medical IT, biopsychosocial IT, and other emerging technologies. Previously, Andrew worked for IHS Markit, where he was the primary analyst in charge of building out its health IT portfolio across custom and syndicated reports. Prior to that role, he was an analyst for IBISWorld, where he covered indirect procurement research on a number of titles related to health care and social services.