The landscape of healthcare payment is shifting from volume to value-based models. New reimbursement policies reward quality improvements, better outcomes and cost control. This all began with the Medicare Access and CHIP Reauthorization Act, and other payers are following Medicare’s lead.

This tectonic shift in payment models means that healthcare organizations need to gather and use data differently. Value-based care (VBC) requires organizations to build outcomes-based financial models and data infrastructure. Failing to do so jeopardizes an organization’s reimbursements which can negatively affect growth and ability to achieve and maintain competitive advantage.

If data is to be used to both support day-to-day operations and also drive the transformation to value, it must be more than just data - it must be actionable information. That requires that data be captured, managed, analyzed and presented in a manner that reveals insights, streamlines processes, and creates efficiencies for team members across the enterprise. 

View this webinar to:

• Understand how VBC is forcing health care organizations to implement population health management and other third-party analytic solutions to support outcomes-based reimbursement models
• Learn how organizations often fail to understand the challenges of provisioning clean data to these solutions in a timely manner – yes, a vendor might offer a 3-to-6-month solution implementation schedule, but if there isn’t already a mature data governance foundation, that timeline means nothing
• See examples of how data profiling helps determine an organization’s readiness to implement an analytic solution by proactively identifying data quality issues in source systems, ensuring reasonable expectations are established regarding the implementation timeline
• Learn common mistakes healthcare organizations make, ranging from not performing data profiling at all to utilizing complex, error-prone and time-consuming SQL queries performed by IT staff
• Receive insight on how data profiling tools allow business and clinical subject matter experts to identify data quality issues with little to no IT support
• Understand the critical importance of establishing data governance roles, responsibilities and workflows