From 40 Hours of Manual Reporting to 4 Hours

The Challenge

A national pathology laboratory network with 8 locations across 5 states had grown through acquisitions, and each location brought its own systems, processes, and reporting formats. Every month, the operations team spent 40 hours manually pulling data from 8 disconnected systems, normalizing it into consistent formats, and stitching together reports for leadership.

The problem went beyond time. Reports were frequently late, contained errors from manual data handling, and provided an incomplete picture of network-wide operations. Duplicate workflows existed across locations — the same reports being generated independently with no standardization. Leadership had no unified view of the business, making it nearly impossible to compare performance across sites or identify network-wide trends.

Previous attempts to solve this with off-the-shelf BI tools had failed because the underlying data was too fragmented. Each system used different data structures, different naming conventions, and different HL7 message formats. The data needed to be unified before any reporting tool could work.

Our Approach

DxLogic created a unified data layer that ingests data from all 8 systems in real time. Rather than replacing any existing system, the integration layer sits on top — pulling data through APIs, HL7 feeds, and database connections — and normalizes everything into a consistent schema.

A custom HL7 processing pipeline was built to handle the variations in message formats across locations. The pipeline parses, validates, and transforms incoming messages regardless of the sending system's format, ensuring data consistency without requiring any changes to the source systems.

On top of the unified data layer, DxLogic built automated dashboards that generate the monthly reports that previously required 40 hours of manual work. The dashboards update in real time, meaning leadership no longer waits until end-of-month to see how the network is performing. Alerts flag anomalies as they happen, not weeks after the fact.

The Results

Monthly reporting time dropped from 40 hours to 4 hours — a 90% reduction. The remaining 4 hours are spent reviewing and annotating the automated reports, not generating them. All 8 locations are now visible in a single unified dashboard, and 100% of duplicate workflows have been eliminated. The operations team that previously spent a full week on reporting each month now spends that time on analysis and improvement initiatives instead.