A mid-sized health system had strong patient demand but was underperforming financially, and leadership assumed the problem was billing inefficiency.
The real issue was revenue leaking between workflows, not inside them. Referrals weren't getting scheduled, patients were dropping between disconnected systems, and services were approved but never delivered, so revenue wasn't being billed because the care never happened. Core systems like the EMR couldn't see referrals that arrived by phone, text, or email, and with no full lineage of a patient from referral to scheduled visit, there was no real-time visibility into where patients fell out. In one oncology practice, each surgical slot was worth $70K–$100K and profitability swung sharply with payer mix, yet the team couldn't see in real time which referrals were converting, the difference between making $10K and $30K on the same slot.
OutcomeCatalyst built a unified 'shared context layer', the 'brain', connecting the health system's disconnected sources without ripping out the EMR. It captures referral signals the EMR can't see (phone, text, email), structures unstructured data with a knowledge graph so an agent can search and reason across it, and tracks the full referral → scheduling → visit lineage in one place, with a plain-English query layer on top.
Significant annual revenue recovery from referrals and visits that previously leaked between workflows.
Improved patient access and throughput without adding headcount.
Teams shifted from reacting after revenue was already lost to catching drop-offs in real time.
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