AI-Powered Pre-Bill Claims Analysis Software: Optimize Revenue Integrity Prior to Billing with eValuator!
As healthcare’s only automated pre-bill coding analysis solution with real-time results, Streamline Health eValuator™ enables you to easily identify, quantify and expedite correction of the issues with the greatest impact on your revenue integrity and financial performance from your Inpatient, Outpatient, and Pro-Fee care.
Analyze Every Case.
Streamline Health eValuator is a cloud-based platform that provides 100% automated analysis of coding and charge accuracy prior to billing by analyzing potential under-coding and over-coding cases on both the Need for Further Review and Financial Impact.
Address Issues Before Billing.
Backed by automated workflows, robust reporting and market-leading expertise, eValuator enables you to identify coding issues before billing for optimal revenue integrity for Inpatient, Outpatient and Pro-Fee encounters.
Requires minimal IT support and integrates with any Electronic Medical Record system and is typically implemented within 45-60 days with less than 45 hours required from your IT team.
Robust rule sets thoroughly analyze each case prior to billing to gauge for coding/charge accuracy and compliant revenue capture.
Using custom thresholds, it routes cases to the designated resource(s) to ensure your team is always focused on the cases with the greatest potential impact.
Flagged charts are returned in real time with detailed corrections on suspected issues, helping assure accuracy while improving coder and auditor performance.
ARTIFICIAL INTELLIGENCE AT THE CORE OF
EVALUATOR™
Leveraging machine learning methods, we analyze millions of encounters processed by eValuator, uncovering trends and patterns to generate…
NEW RULES
ENHANCED RULES
TAILORED CLIENT INSIGHTS
HOW IT WORKS:
Using data points from claims processed by eValuator™, Streamline’s Artificial Intelligence extensively analyzes millions of medical encounters, seeking out similarities and patterns. This information forms data clusters, which are then reviewed by our experienced rules team to develop new rules, improve existing ones, and offer tailored insights to individual clients.