- Who We Serve
- About Us
The missing piece in your revenue cycle process, Revenue Integrity Insights goes beyond denial monitoring dashboards by combining the power of machine learning and objectivity of XSOLIS’ proprietary Care Level Score™ (CLS) with revenue cycle outcomes.
Our reporting and dashboards provides visibility into missed, appropriate conversion opportunities along with pre-claim and post-claim denial trending and analytics that are aligned with the CLS and Length of Stay. This alignment enables easy identification of trends, missed IP reimbursement, and opportunities for process improvement.
Revenue Integrity Insights offers continuous monitoring of denial performance end-to-end to help organizations identify gaps and opportunities quickly and adjust where needed.
Improves revenue assurance by providing deeper insights into factors that impact appropriate inpatient reimbursement such as underpayments from payer determinations or self-denials, potential payment risk, and status confidence.
Captures opportunities for payer collaboration and automation as well as outlier trends by comparing performance across all payers utilizing reliable machine learning, the CLS, and 2 MN benchmarks to easily identify higher degrees of alignment and/or misalignment.
HFMA White Paper: Leveraging AI in UM Can Enhance Your Revenue Cycle
Learn how providers are able to reduce revenue leakage and rework from underpayments and denials, increase revenue cycle-related efficiencies, and ensure appropriate reimbursement using AI.
HFMA Webinar: Optimize Revenue Integrity & Improve Payer Alignment with AI
Mayo Clinic and XSOLIS leaders discuss how objective, AI-driven insights can strategically align revenue cycle and utilization review teams to streamline hand-offs, ensure appropriate reimbursement and reduce the back-end delays associated with avoidable denials, and more