Unified Clinical Analytics

A regional health system operated three hospitals and 40+ clinics, with clinical and operational data locked in separate EHR, claims, and patient experience systems. Producing quality and regulatory reports required weeks of manual effort across multiple departments. The health system partnered with Vitosha to build a unified analytics platform on Microsoft Fabric, connecting fragmented data sources into a single governed view for clinical quality, operational performance, and financial analysis.

The health system managed data across Epic EHR, a legacy claims system, and a third-party patient experience platform, with no integration between them. Quality reporting for CMS, Joint Commission, and state regulators required manual data extraction, reconciliation, and validation that took 4–6 weeks per report. Clinicians and administrators could not get timely answers about readmission rates, infection trends, or patient satisfaction. Population health analytics were practically impossible, and the system lacked early warning signals for deteriorating patient cohorts or operational bottlenecks.

Phase 1: Data Unification — Connected EHR, claims, and patient experience data into Microsoft Fabric using Azure Health Data Services with FHIR conversion, creating a single governed clinical data foundation with Purview for data cataloging and lineage. Phase 2: Quality Dashboard Suite — Built Power BI dashboards for clinical quality (readmissions, HAI rates, core measures), operational performance (ED throughput, bed utilization, OR turnover), and financial analysis (cost per case, payer mix, denial trends), all with role-based access. Phase 3: Predictive Analytics — Developed Azure ML models for 30-day readmission risk, sepsis early warning, and patient no-show prediction, integrated into clinical workflows through automated alerts in the existing EHR and care coordination platform.

Clinical quality reporting that previously took 4 weeks was reduced to under 1 week — a 60% improvement. The health system identified and reduced avoidable readmissions by 30% through the predictive readmission model, which achieved 82% AUC. Operational dashboards helped reduce ED boarding time by 25% and improved OR utilization by 15%. All three hospitals and 40+ clinics now access a single source of truth for quality, operational, and financial analytics, saving an estimated $1.2M annually in manual reporting labor and avoided penalties.

By connecting fragmented clinical and operational data, the health system transformed its ability to measure and improve care quality. Unified analytics enabled faster reporting, proactive interventions, and a data-driven culture across the enterprise.