Data & Analytics · Healthcare
Reporting, prediction and document processing for a medical data platform, delivered with a cross-functional business intelligence, data engineering and machine learning team.
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01Challenge
Medical data arrives in formats built for people rather than systems: documents, attachments and email threads alongside structured records. Reporting, forecasting and document handling had grown up separately, so the same information was re-entered and re-reconciled in several places before anyone could act on it.
02Approach
Treat the document pipeline and the reporting layer as one problem rather than two. Extract structure from documents at the point of arrival, validate and reconcile it against existing records, and build the reporting and prediction layers on the governed result rather than on raw feeds.
03Outcome
Medical data arrives in formats built for people rather than systems. Reporting, forecasting and document handling had grown up separately, so the same information was re-entered and re-reconciled several times before anyone could act on it.
Documents are converted into structured records when they land, rather than being re-keyed later by whoever needs them.
Validation and reconciliation run as defined workflow steps, so the reporting layer reads governed data rather than raw feeds.
Reporting and prediction are built on the same governed layer, so a forecast and a report cannot disagree about the underlying facts.
What changed
How it works
01 / 04
Inside the system
Built with
Documents in. Governed, reportable data out.
More work
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If something here is close to what you need, tell us about your situation and we will walk you through how we would approach it.
Intelligence → Innovation → Automation → Growth