Healthcare has higher barriers to adopting data science than other industries. State-of-the-art analytics solutions are already available, but few of them are actually in use by clinicians. In this talk, we will introduce a journey of data science to support and guide clinicians in a 30-day readmission reduction at the University of Virginia Health System. We have established a culture of data-driven decision-making among clinicians, and have transformed the quality improvement process. Data science guides clinicians in finding opportunities for improvement, designing and implementing interventions, and evaluating impacts. We will also discuss how we are transitioning from descriptive, to predictive, to prescriptive analytics, with enthusiastic support from clinicians.
Identify opportunities and challenges in clinician’s adoption of data science
Describe approaches to successfully promote advanced analytics in health systems
Discuss prescriptive analytics in quality improvement