Solution Showcase: All Things Data with Clearsense and the Six Pillars of Data Governance

<p><strong style="background-color: transparent">May 10, 2023: </strong><span style="background-color: transparent">Live from the HIMSS Conference, </span><a href="https://www.linkedin.com/in/terrimikol/" target="_blank" style="background-color: transparent">Terri Mikol</a><span style="background-color: transparent">, Data Governance Principal Advisor at </span><a href="https://clearsense.com/" target="_blank" style="background-color: transparent">Clearsense</a><span style="background-color: transparent"> and </span><a href="https://www.linkedin.com/in/govind-thirumalai-mba/" target="_blank" style="background-color: transparent">Govind Thirumalai</a><span style="background-color: transparent">, Vice President of Business Intelligence at </span><a href="https://www.parkview.com/" target="_blank" style="background-color: transparent">Parkview Health</a><span style="background-color: transparent"> talk all things data. What are the six work streams when implementing data governance in healthcare organizations? How does Clearsense combine data with institutional knowledge to provide a learning platform for users? How can healthcare organizations ensure that the answers to common data governance questions are accessible to departments and hospitals? How does the complexity of healthcare data across multiple states impact data governance initiatives? What are the benefits of having a community of analytics users within an organization? Why is it necessary to have clear definitions for data elements, even if multiple definitions are acceptable in different use cases?</span></p><p><strong style="background-color: transparent">Key Points:</strong></p><ul><li><span style="background-color: transparent">Metadata</span></li><li><span style="background-color: transparent">Data governance</span></li><li><span style="background-color: transparent">Data definitions</span></li><li><span style="background-color: transparent">Data literacy</span></li><li><span style="background-color: transparent">Complexity of healthcare data.</sp