Availity Intelligent UM
*Availity Intelligent UM utilizes artificial intelligence, including machine learning and natural language processing (NLP), to automate and optimize various aspects of utilization management, primarily focusing on prior authorizations.
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Its core features include:
- AI-Powered Decisioning
- Touchless Processing
- Bi-directional Data Exchange
- Integrated Workflows
- Comprehensive Prior Authorization Module
- Auth Connectivity
- AuthAI
- Reduced Administrative Waste
- Transparency and Auditability
- Support for CMS Interoperability Mandates
AI-Powered Decisioning:
The system's proprietary AI clinical engine analyzes case-specific clinical data against codified medical policies to make transparent and traceable recommendations for prior authorizations. This allows for automated approvals in a significant percentage of cases (up to 80% for some common authorizations), often within seconds or minutes.
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Touchless Processing:
A major goal is to enable "touchless" prior authorizations, meaning responses are returned without the need for manual review by staff at either the provider or payer end. This drastically reduces processing times.
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Bi-directional Data Exchange:
Availity acts as a central hub, facilitating direct, real-time data exchange between payers and providers. This eliminates intermediaries and reduces latency in communication.
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Integrated Workflows:
The solution integrates into existing provider workflows, including Electronic Health Records (EHR) systems, allowing providers to submit requests and receive determinations directly within their native environments.
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Comprehensive Prior Authorization Module:
This module typically includes:Auth Foundation: Establishes the framework for how health plans receive authorization requests and routes them appropriately.
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Auth Connectivity:
Leverages Fast Healthcare Interoperability Resources (FHIR) APIs and other connections to enable end-to-end authorization communication.
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AuthAI:
The AI engine that automates the review and decision-making process.
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Reduced Administrative Waste:
By automating repetitive tasks and ensuring accurate documentation upfront, Intelligent UM helps to minimize administrative errors, denials, and appeals, leading to cost savings for health plans and improved revenue cycle for providers.
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Transparency and Auditability:
While AI drives decisions, Availity emphasizes "responsible AI" with human oversight. AI recommendations are transparent and auditable, and human clinicians review complex cases.
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Support for CMS Interoperability Mandates:
The solution is built with FHIR®-based APIs to help health plans comply with current and upcoming Centers for Medicare & Medicaid Services (CMS) interoperability regulations.
How it Works ⚙️
Availity Intelligent UM works by serving as a central "digital front door" for prior authorization requests. Here's a simplified breakdown:
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Submission:
Providers submit prior authorization requests through the Availity platform, often directly from their EHR system. This submission includes necessary clinical documentation.
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Data Extraction and Analysis:
The system's AI engine (AuthAI) extracts pertinent clinical information from the submitted medical records.
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Policy Matching:
The AI then analyzes this clinical data against the specific medical policies and criteria of the relevant health plan. Unlike simpler models, it considers each payer's unique policies and the precise conditions for each patient.
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Automated Decision/Recommendation:
For a large percentage of common and straightforward authorizations, the AI can make an immediate approval or denial decision. This process can take less than 90 seconds, often under 20 seconds. For more complex cases, the AI provides a recommendation that is then reviewed by a human clinician.
Notification and Transparency:
The provider receives a rapid response, often while the patient is still at the clinician's office. The system also provides real-time visibility into the status of all authorization requests.
This approach aims to move away from traditional, often manual prior authorization processes that are time-consuming and prone to errors, fostering a more efficient and patient-centered healthcare experience.
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