Real-Time Patient Data Dashboard
Unified 7 disparate clinical data sources into a single real-time Lakehouse with sub-second analytics.
Where Vantage Health was stuck.
Clinical teams at Vantage Health were working from data that was 24–48 hours stale. Patient information lived in 7 systems that didn't communicate: an EHR, two lab systems, a pharmacy platform, a scheduling tool, a billing system, and a legacy reporting database. Producing a single patient view required manual exports and spreadsheet reconciliation, a process that took a senior analyst 3 hours per report.
How we solved it.
We built a cloud-native Lakehouse on AWS using Apache Iceberg for the table format, dbt for transformation, and Apache Kafka for real-time event streaming from all 7 source systems. A thin API layer serves a React dashboard with sub-second query performance. Role-based access ensures clinical, operational, and executive views are appropriately scoped. HIPAA compliance was addressed at the architecture level, not retrofitted.
Results that matter.
Clinical teams now have a single, live patient view refreshed every 30 seconds. The time to produce a patient summary dropped from 3 hours to 11 seconds. The operational dashboard identified three process bottlenecks in the first month that, once resolved, reduced average length-of-stay by 0.4 days, a meaningful outcome at Vantage's volume.
from 24–48 hrs
down from 3 hrs
in one Lakehouse
team reported
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