Interoperability Workshop: FHIR Up Real-Time Patient Analytics With the Lakehouse
Patient-centric care requires data harmonization and with FHIR becoming the standard for health data exchange, the opportunity to bring together siloed patient data is now a reality. But FHIR alone cannot solve all the analytics challenges facing organizations. For example, FHIR is not designed for downstream analysis. Significant engineering work is required to prepare FHIR bundles for analytics and build pipelines that support real-time updates on streaming data. Not to mention, legacy analytics platforms typically lack the robust ML capabilities needed to build predictive models for use cases like disease risk prediction.
Fortunately, there’s a path forward with a modern, scalable Lakehouse Platform for data and AI. Join this workshop to learn how the Databricks Lakehouse for Healthcare and Life Sciences and our new joint solution from Lovelytics automate the real-time ingest of FHIR bundles, address incremental data updates, flatten the bundles to enable interactive querying, and prepare the data for downstream analytics at scale.
© Databricks 2022. All rights reserved. Apache, Apache Spark, Spark and the Spark logo are trademarks of the Apache Software Foundation.