Reveleer Launches Prospective Risk Adjustment Enhancements, Leveraging AI to Close Care Gaps Proactively

Reveleer, a healthcare technology company using artificial intelligence (AI) to empower data-driven healthcare for payers and providers in all lines of business, announced significant enhancements to its AI-enabled prospective risk adjustment solution. Through EHR-agnostic connections, the Reveleer platform packages pertinent patient information as a pre-encounter summary and shares it directly with the provider to proactively close care gaps, leading to better revenue performance, more accurate reimbursements, and better health outcomes. The new GetNext capability enables highly efficient, proactive risk adjustment, optimizing workflows for risk and quality teams by consistently prioritizing the next-most-valuable data for coding and abstraction per customizable rule sets. To receive a live demonstration of the Reveleer platform for Risk, Quality, and Member Management, visit Reveleer booth #313 @RISE National, March 6-8, 2023, in Colorado Springs, Colo.

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The key to Reveleer’s prospective risk adjustment capabilities is its unique data acquisition model that eliminates data silos by leveraging multiple structured and unstructured sources across the care continuum: multiple HIEs, all hospital and specialist EHRs, medications, and labs to create a comprehensive, longitudinal clinical record for members/patients, regardless of the source of the care encounter. Using proprietary AI technology, including Natural Language Processing (NLP) and Machine Learning (ML), the Reveleer solution automates, accelerates, and improves clinical data coding and abstraction while reducing errors, inefficiencies, and program costs. With GetNext, teams work efficiently, focusing on the highest-value cases based on essential parameters indicating where care gaps, coding, or documentation issues may be present.

Leveraging this comprehensive member/patient record, relevant data is summarized and delivered to the provider, giving insight about care gaps – or potential care gaps – before the patient encounter. Bi-directional integration with the EHR delivers information to the provider and then returns data from the provider to the longitudinal record for concurrent and retrospective analysis. Making valuable information available at the point of care enables prospective risk adjustment, eliminates reimbursement delays, increases the accuracy of Risk Adjustment Factor (RAF) scores, and improves revenue performance.

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“AI’s role today should be to assist risk and quality teams with improved accuracy and productivity – not replace human intelligence. That’s how Reveleer continues to shift the paradigm for AI,” said Jay Ackerman, CEO and President of Reveleer. “Our approach quickly and accurately optimizes risk adjustment program performance, making it possible to proactively close care gaps, rather than acting after the fact. Using AI to put the right information in the hands of providers at the point of care is a game changer for better patient outcomes and more accurate and timely reimbursement.”

Considering the Centers for Medicare & Medicaid Services’ (CMS) recent Medicare Advantage Risk Adjustment Data Validation Final Rule, it’s more important than ever for payers and providers to work together to close care gaps and ensure accurate documentation to overcome the challenges of delayed reimbursement and poor patient/member outcomes. As providers take on more risk, efficient, friction-reducing work processes supported by sophisticated technology must seamlessly share data needed among stakeholders. Reveleer’s proprietary AI-driven capabilities help providers close the care gap loop – now prospectively rather than retrospectively – allowing health plans to confidently execute prospective risk adjustment programs by automating the collection, analysis, review, and submission of risk adjustment data through to the point of care. Join Reveleer’s educational session at RISE National to learn the Keys to Successful Health Plan and Provider Collaboration .

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