Healthcare Group Scales Insights

Challenges

Data was fragmented across dozens of systems, making it impossible to generate 360-degree patient views or hospital-wide metrics. Reporting was slow, often taking 3–5 days to pull patient journey data across systems. There was no single source of truth, and clinicians lacked insights to improve care pathways. The infrastructure couldn’t support predictive modeling (e.g., readmission or no-show risk). Moreover, regulatory compliance and secure access were top concerns when considering cloud adoption.

• EMRs, billing, and lab systems were disconnected and inconsistent

• Reporting cycles took multiple days, delaying decisions

• Clinical teams had no access to actionable insights

• No support for predictive models like readmission risk

• Limited data governance and compliance controls

Solutions

We designed and deployed a secure Snowflake-based data cloud platform with governed analytics and predictive modeling for real-time visibility.

Data Centralization: Unified data from EMR, labs, and billing via Fivetran into Snowflake with dbt for transformations

Security & Compliance: Enforced HIPAA safeguards using Snowflake’s dynamic masking, row-level security, and OAuth

Reporting Layer: Built semantic layers and dashboards in Power BI for clinical, financial, and executive teams

Predictive Analytics: Built ML models (scikit-learn) for readmission risk, embedded via Snowpark UDFs in Snowflake

Monitoring: Used Snowflake’s Resource Monitors and Access History for performance and security audits

Data Ops: Scheduled ELT jobs and health checks via Airflow and GitHub Actions