Rebuilding a fragmented data infrastructure for a leading Canadian long-term care provider

The Challenge

Patient records, staffing schedules, medication logs, and operational data lived in 12 separate systems — most of them manual spreadsheets or legacy databases with nothing connecting them. Reporting was slow and hard to trust. Every week, staff spent hours pulling data from different places and reconciling numbers that never quite matched, just to produce summaries that were already out of date before they reached anyone.

Our Approach

The starting point was a full audit across all 12 source systems — mapping what existed, who owned it, how often it updated, and where the gaps were. Patient records, medication administration, and staffing data were the priority, being both the most critical and the most fragmented.

A cloud data warehouse was built to bring everything into one place, with automated pipelines handling extraction and loading from each source. Quality checks were wired into the ingestion process so bad data got flagged before it had a chance to flow through to reporting.

The harder part was normalisation. "Occupied bed" and "care hours" meant different things in different systems. Getting clinical, scheduling, and billing teams aligned on shared definitions took work, but it's what made the data actually usable rather than just available.

Key Deliverables

• Cloud data warehouse unifying all 12 source systems
• Automated pipelines replacing manual data consolidation across departments
• Data quality framework with automated anomaly detection and alerting
• Normalisation layer with consistent definitions across clinical, scheduling, and billing
• Decommissioning plan for legacy manual reporting processes

“We went from spending half our week chasing data to actually using it.”

— Director of Operations, Canadian Long-Term Care Provider

Results

Engagement

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