Webinar: How Axia Women’s Health Solved Patient Matching
About This Webinar:
Hear how Axia Women’s Health, the largest integrated OB/GYN healthcare provider in the U.S., solved its patient matching challenges and dramatically reduced its duplicate records by deploying a cloud-based master patient index (MPI) solution in six weeks that uses the new gold-standard in patient matching technology: Referential Matching. And learn how Referential Matching technology harnesses a nationwide database of reference demographic data as an “answer key” to automatically match up to 98% of records with no extensive tuning required—even records that contain out-of-date addresses, maiden names, missing SSNs or birthdates, and errors or typos.
Dave Bonewicz Senior Manager Data Governance Axia Women’s Health
Dave Bonewicz is the Systems Integration Specialist at Axia Women’s Health, the largest integrated OB/GYN healthcare provider in the U.S., where his responsibilities span master data management, data architecture, data integration, data migration, data warehousing, and data analytics, as well as developing and operating Axia’s enterprise master patient index (EMPI) and building HL7 interfaces. Prior to working at Axia, Dave held senior positions at IT and software consulting companies, including as Senior Consultant at Turnberry Solutions, Lead Architect at Ontrac Consulting, and Systems Architect at CYMPAK, Inc.
Mark LaRow Chief Executive Officer Verato
Mark is the Chief Executive Officer of Verato, a leading provider of cloud-based patient matching and master patient index services powered by Referential Matching technology. He was formerly at MicroStrategy, a business intelligence software provider, for 14 years where he was the Executive Vice President of Products, responsible for product strategy, product marketing, and competitive intelligence. Prior to MicroStrategy, Mark was with Ernst & Young for 17 years and left as Partner responsible for all technical consulting in the east region of the US. Mark holds MS and BS degrees from MIT in electrical engineering and computer science.
Pew Report: Enhanced Patient Matching is Critical to Achieving Full Promise of Digital Health Records