Can a national outpatient provider reduce manual referral processing without adding operational overhead?
About the Client
Background
The client is a national outpatient provider delivering diagnostic services across multiple regions. Their operations depend on efficiently processing high volumes of inbound referrals and converting them into scheduled care within complex regulatory and operational constraints.
Overview
As the organization scaled nationally, manual referral intake became a growing operational bottleneck. Large volumes of inbound documents required staff to manually interpret, re-enter, and validate information before orders could move forward. The client partnered with Invene to reduce manual effort in referral processing while preserving accuracy, safety, and human oversight.
Challenge
As a national outpatient provider, the client relied on manual processes because its EMR did not expose APIs for referral intake. Staff spent significant time reviewing paper and faxed documents, re-entering information, and resolving inconsistencies before orders could move forward. This constraint limited efficiency, introduced operational risk, and made it difficult to scale referral processing reliably across regions.
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Solution
Invene built a production system that automated referral intake without relying on EMR APIs. The system uses GenAI to convert unstructured documents into structured data and RPA to enter validated information directly into the EMR. Deterministic rules validate completeness, while ambiguous or high-risk scenarios are routed to staff for review. This approach reduced manual effort without introducing operational or clinical risk.
Results
Manual referral processing was reduced while preserving accuracy and control. By automating standard cases and routing only exceptions to staff, the system allows the team to process a higher volume of orders without increasing manual headcount. Duplicate or unsafe entries are avoided by design through built-in safeguards.

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