New York Sate Practitioner Database Project Provider Data Validation Presented by: Josh Schoeller, Vice President, Chief Solutions Architect LexisNexis February 24, 2014 Confidential Proprietary information – Not for Distribution Problem to be Addressed: New York State does not have a comprehensive physician or mid-level practitioner database. The current process of gathering such information is arduous and complicated requiring users to examine multiple local, state, and national data sources, often followed by surveys and telephone contacts with offices, hospitals, and other entities. The need for a common, integrated, practitioner database is greater than ever, particularly as the state addresses the implications of federal and state reforms that will significantly increase the demand for primary care and other services. Gartner: "Big data are high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization." Data growth challenges and opportunities are three-dimensional: Volume (amount of data) Velocity (speed of data in and out) Variety (range of data types and sources) The necessity: to create and have access to actionable data Confidential Proprietary information – Not for Distribution Provider data impacts everything Claims Processing Provider Directories Retention Member and Provider Satisfaction Network Management At the center of payer operations Provider EPS Data Financial Accuracy Returned Mail and Mailing Aggregation Data Warehouse and Reporting Credentialing 3 Fraud Detection Compliance and Accreditation Customer Service Confidential Proprietary information – Not for Distribution Provider data is changing all the time The provider universe is always changing 2.5% of provider demographics change each month 30% of doctors change their affiliations each year 5% of doctors change their status each year The pace of business leads to additional inaccuracies Human errors in data entry Multi-channel delivery of incoming transactions with errors or omissions Data integration challenges across data sources / organizational silos Provider demographic data quality degrades rapidly 100% Bad 50% 0% Months 4 Good 3 6 9 12 15 Confidential Proprietary information – Not for Distribution 18 How is provider data being managed today? Provider Reported Changes Claims External Provider Data Files Audit / Re-credentialing Provider File Cred / New Providers Reactive provider data management 5 Confidential Proprietary information – Not for Distribution Taking a different path 6 Best practice to create a single source of truth or Enterprise Provider Data Master Leveraging referential data to continuously validate provider information improves accuracy and results Systematic updates allow resources to be redirected from manual validation and data entry Focusing resources on significant changes in data speeds updates to internal provider databases Confidential Proprietary information – Not for Distribution Next generation provider data model Credentialing Information Claims Data Provider Feedback External Provider Variables Member Feedback Cost & Quality Information Enterprise Provider Data Master (Integration and Meta Layer) Health Benefit Exchange Member Engagement APCD 7 MMIS Network Optimization Reduced Costs Fraud, Waste and Abuse Provider Performance Optimize Quality of Care Enhanced Member Loyalty Confidential Proprietary information – Not for Distribution Clinical Analytics Operational Efficiencies Questions and Answers Confidential Proprietary information – Not for Distribution Better provider information. Right now.® For more information contact: Mark Biddle Senior Director, Sales 978-475-1551 mbiddle@enclarity.com Confidential Proprietary information – Not for Distribution