The Challenge
Executives and frontline teams lacked timely, trustworthy data. Operational KPIs—such as patient throughput, staffing efficiency, and referral performance—were reported too late to influence decisions. Data was spread across multiple EHR, marketing, and financial systems, each with its own logic and delays. Reporting relied on batch processes and spreadsheets, leading to inconsistencies, duplicated efforts, and limited accountability. Leaders wanted a real-time view of the system, but lacked the architecture to support it.
The Solution
Productive Edge developed and presented a Lakehouse architecture strategy using Databricks and Delta Live Tables. The design leveraged a medallion approach (Bronze/Silver/Gold) to support real-time and batch data ingestion from clinical, operational, and engagement systems. Key focus areas included HL7 and FHIR readiness, patient journey mapping, and machine learning enablement for segmentation, outreach, and scheduling optimization. Governance models, data contracts, and access layers were outlined to ensure security, compliance, and scalability. The proposed platform was built to deliver fast insights without compromising trust or control.
The Results
While still in the pre-implementation phase, the proposed architecture received strong buy-in from executive and technical stakeholders. It offers a clear path to eliminating silos, increasing the speed of decision-making, and enabling AI-driven operations. Teams can expect to gain real-time access to key metrics with refresh rates under five minutes, along with new capabilities for predicting demand, identifying care gaps, and optimizing resource allocation. This platform will serve as the foundation for the health system’s next generation of analytics and automation.
