- Healthcare
- United States
- Updated
How CenteredCare Onboards a New Community in Under 24 Hours
CenteredCare embeds healthcare into senior-living communities, but ran on a fragmented, largely manual data ecosystem where onboarding a new community took 3 weeks. We built a FHIR-native analytics platform on Microsoft Azure and Azure Databricks that cut onboarding to under 24 hours, removed 70% of manual data-engineering effort and cut ingestion errors 60%.
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The situation
Onboarding a new community took three weeks.
CenteredCare embeds healthcare into senior-living communities, and it ran on a fragmented, largely manual data ecosystem where onboarding a new facility took 3 weeks. It connected multiple EMRs (PCC and ALIS), CRMs and third-party APIs, with limited interoperability and no FHIR-native analytics. Ingesting semi-structured data from partner EMRs was slow and error-prone, and manual ETL consumed up to 80 engineering hours a month. Analytics were retrospective and siloed, staff worked without predictive insight, and HIPAA and FHIR compliance depended on audit-heavy manual processes, which slowed care coordination for the residents who most needed proactive attention.
What we built
One FHIR-native resident record on Azure Databricks.
We deployed a FHIR-native platform on Microsoft Azure. A custom Airbyte connector running on AKS ingests FHIR bundles and is designed to take them from any EMR; a multi-zone Azure Databricks Delta lakehouse with Bronze, Silver and Gold layers curates the data, validated in real time with Great Expectations; and Azure Health Data Services standardizes everything to FHIR R4. On top, Databricks ML drives risk stratification and automated care recommendations, and Power BI gives care navigators and clinicians a live, shared view. Azure Key Vault, RBAC, Azure AD and Purview govern PHI end to end.
How it works
The architecture, stage by stage.
Ingest
- FHIR bundles from EMRs (PCC, ALIS) → custom Airbyte connector on AKS
Standardize
- Azure Health Data Services → FHIR R4
Curate
- Multi-zone Azure Databricks Delta lakehouse, Bronze · Silver · Gold, validated in real time with Great Expectations
Analyze
- Databricks ML → risk stratification and automated care recommendations
Act
- Power BI → live, shared dashboards for care navigators and clinicians
What changed
The outcomes, as the client measures them.
- Onboarding a new community fell from 3 weeks to under 24 hours, on the generic FHIR connector.
- Manual data-engineering effort dropped 70 percent.
- Ingestion errors fell 60 percent.
- Insights generate in under 5 minutes after ingestion.
- Caregiver adoption passed 90 percent within two weeks.
- Staff efficiency rose 31 percent and family satisfaction rose 26 percent.
By the numbers.
<24h
To onboard a new community, down from 3 weeks
60%
Fewer ingestion errors
70%
Less manual data-engineering effort
31%
Higher staff efficiency
26%
Higher family satisfaction
>90%
Caregiver adoption within two weeks
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