Clinical Document Intelligence for Private Hospital Group
Automating 85% of clinical document processing across a 9-hospital network
The Challenge
A private hospital group was processing over 40,000 clinical documents per month manually -- referral letters, pathology reports, discharge summaries, and consent forms. Staff spent an average of 8 minutes per document on data entry, classification, and routing. Errors in document handling contributed to delayed patient care.
Our Approach
We built a document intelligence pipeline using Azure AI Document Intelligence and custom NLP models trained on Australian clinical terminology. The system extracts structured data, classifies documents by type and urgency, and routes them to the correct clinical team. Integration with the hospital's PAS and EMR systems ensures data flows directly into patient records.
The Outcome
85% of documents are now processed without manual intervention. Average handling time for the remaining 15% dropped from 8 minutes to under 2 minutes. Document misrouting errors decreased by 93%, and the solution freed up the equivalent of 6 FTEs for direct patient care.
Auto-Processed
Error Reduction
FTEs Redeployed
Technology Stack
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