They had the domain expertise — former hospital CFOs, revenue cycle directors, charge capture specialists — but their technology was a patchwork of Excel models, manual data pulls from client EMRs, and quarterly reports that told hospitals what they already knew: they were losing money.
But execution depended entirely on consultants being on-site to implement changes. And every time a consultant left, their methodology knowledge walked out the door. The inherited environment combined application behavior, data movement, user workflows, and operational dependencies. Engineering began by locating authoritative data, integration contracts, control owners, failure behavior, and a reversible acceptance boundary.
The Algorithm leadership confirms this engagement as part of the company’s delivery history. Public wording is limited to the technical narrative while client-sensitive and precision claims complete leadership review.
Cloud-based RCM intelligence and execution platform. Automated assessment engine connecting to client EMR and billing systems — identifying revenue leakage patterns automatically using rule engines built from the company's proprietary methodology. Real-time monitoring dashboards for client hospital leadership. Charge capture optimization — alerts for missed charges before the billing window closes.
The engagement produced a working change to the client’s system or operating workflow. Exact measurements, delivery duration, audit outcomes, and client sentiment are withheld until the corresponding leadership-confirmation items are resolved.
The first call is with a senior engineer.
Tell us the system boundary, operating constraint, and evidence required for acceptance. We'll identify the assumptions and technical questions that should shape the engagement.