Dan Heinmiller is the VP of Operations for the Application Suite Business Unit for Health Catalyst. He oversees teams working to efficiently deploy DOS Mart data products, monitor and optimize DOS Mart performance, develop best practices around release engineering and develop a world class data quality solution. Dan earned his BA in Economics from the Ohio State University and his professional experience includes time as an Analytics Director at Health Catalyst and considerable time at Nationwide Children’s Hospital in central Ohio, where he concentrated on process improvement and optimizing revenue cycle workflows. Dan has worked with a variety of healthcare organizations throughout his career on a variety of projects throughout the United States but still calls Columbus Ohio home with his wife and two young children.
(Analytics Best Practices, Innovative Data and Analytics Transformation — Course Level: Intermediate)
COVID-19 response and recovery efforts provided urgent analytic use-cases, each one highlighting data quality as a prerequisite. Discover five essential data quality lessons that COVID-19 helped shine a light on, and how heath organizations can apply these lessons to be prepared for the future.
In this session, you will learn:
- Why assessing data quality at the end of the data pipeline is not good enough.
- How firefighting data quality issues falls on the backs of analysts in the absence of a systematic approach to data quality assessments.
- Why going beyond simple verification of data quality may require looking outside the four walls of a single organization, and more.