Connect person records with confidence

Autopilot AI is the machine learning engine built into Rhapsody Identity that automates identity resolution at scale. Rather than relying on manual review or generative AI, Autopilot uses proven ML algorithms to match and link records accurately, consistently, and at a speed no manual process can match. Geisinger achieved a 98% data match rate using Rhapsody Identity, and KeyHIE saved 743 hours of manual labor per month. 

Fragmented identity data is one of healthcare’s most persistent and costly problems. When a patient has records spread across multiple systems that don’t recognize each other as the same person, care teams get an incomplete picture, claims get denied, and analytics are unreliable. An EMPI resolves that fragmentation by creating a single, trusted, longitudinal view of every person. Records link automatically and every match decision is traced and documented, so your team always knows why a connection was made. 

EHR-native matching is designed to work within a single system. Rhapsody Identity is designed to work across systems, linking records from multiple EHRs, labs, payers, HIEs, and other data sources into a unified, trusted person record. It provides full data lineage and versioning, audit-ready compliance tracking, and AI-driven automation that no single-system tool can replicate.

AI models are only as reliable as the data they’re trained and run on. Fragmented identity data produces unreliable outputs. To an AI model, a patient with three unlinked records looks like three different people. Rhapsody Identity creates the trusted, unified person data foundation that AI initiatives require to produce safe, accurate, and actionable results. 

Pricing is based on your organization’s size, record volume, deployment model, and needs. Connect with an interoperability specialist to scope what Rhapsody Identity would look like for your environment.