The client is a large healthcare system that brings together teaching, community hospitals, and academic medical centers. The system employs over 4,800 physicians and 38,000 employees who strive together to expand access to care while conducting groundbreaking research and education.
As a newcomer to Snowflake, Amazon Web Services, and Matillion, the healthcare system was looking to retire their on-prem legacy implementation and migrate their data warehouse components to the cloud. Though their migration plan involved data from a variety of sources, the complexity around working with proprietary Epic data, in particular, was a major blocker for the risk-adverse organization.
With four different entities rolled up under the system’s umbrella, the enterprise needed to be able to ingest and analyze data from a wide gamut of EHR and non-EHR sources
Over the course of a three-month initial engagement, Hakkoda planned and implemented a centralized cloud data platform built on Snowflake and AWS that gave the organization the data dynamic ETL tools and enablement it needed at scale.
Hakkoda’s Healthcare & Life Sciences team also leveraged its deep expertise in Epic EHR data to enable dynamic ingestion of Epic data into Snowflake. The client’s small but highly skilled internal data team is now using the pipelines and best practices put in place for Epic to incorporate other data sources across their ecosystem to power system-wide analytics in and outside of the patient record.
Leveraging a Hakkoda accelerator to manage role-based access and automatically apply their governance and security frameworks, the client’s internal team is also working to bring on as many as 500 users this year. They’ve also begun using the Snowflake AI Data Cloud to achieve their long-term goal of establishing a research hub.
