Associate Professor University of Pittsburgh Pittsburgh, Pennsylvania, United States
Description: In this breakout session we will explore practical avenues for data access, and leveraging data driven tools to enhance quality management within clinical laboratories. We will delve into real-world applications of data analytics within the clinical laboratories of an academic medical center’s health network. We will also explore a use case of machine learning to create custom workflows to meet the diverse needs of patient populations.
Learning Objectives: 1. List three methods of accessing clinical laboratory data 2. Outline essential components of an interactive clinical laboratory dashboard for pre-analytical quality management 3. Evaluate the key elements defining a problem suitable for machine learning solutions within clinical laboratory contexts
