Artificial Intelligence Used In Billing

Description

The conversation will focus on the growing interest, development, and adoption of Artificial Intelligence in the business setting of medicine, specifically RCM.

Diagnostic data is transformative yet often underutilized. The volume of diagnostic claims and their related financial data is ripe for harvesting insights that can be a catalyst for health system decision making. Identifying leading indicators such as payor behavior and reimbursement trends can assist outreach programs and laboratories in optimizing their processes, and better managing their bottom lines. However, gaining those insights without inadvertently applying another person’s interpretation or subconscious bias is critical.

There are opportunities in the laboratory and RCM to link the many different stakeholders and exchanges to the right data at the right place at the right time, dramatically improving business management and patient care simultaneously.

Learning Objectives

• AI-enabled analytics from health systems ancillary services can create competitive advantage by uncovering insights related to payor behavior as leading indicators, reimbursement trends, potential financial impacts, and profitability opportunities
  
• Leveraging diagnostic and financial data from outreach programs and other ancillary services can support health systems with revenue improvements as well as cost reduction initiatives
  
• Types of analytical insights from diagnostic claims and financial data that may add the most value to health system decision-making

Speakers

Karim Sirgi, MD, MBA
Jeff Carmichael, XIFIN VP of Engineering
Joe Nollar, AVP LIS Product Development
Diana Richard, XIFIN Director of Anatomic Pathology Program Development

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