Transform prior authorization process with Red Hat
A complex landscape creates inefficiencies and compromises outcomes
Prior authorization (PA), though vital for healthcare revenue, is a fragmented and inefficient process. Its complex, non-standardized steps frequently cause delays, errors, and impede timely care delivery. These inefficiencies disrupt provider workflows, lower patient/member satisfaction, and negatively impact clinical outcomes.
At the heart of the issue is a complex operational landscape shaped by evolving regulatory requirements and outdated technology infrastructure. Federal mandates, such as the CMS Interoperability and Prior Authorization Final Rule (effective January 1, 2027) require that payers send PA decisions within 72 hours for expedited requests and 7 calendar days for standard requests. This is a significant reduction in comparison to the current national average of 14.5 days for PA turnaround.
In a 2024 AMA survey1 of practicing physicians, 89% reported that prior authorization increases burnout, while 94% stated that it delayed patient access to necessary care.
A modern approach to the PA process
To address the inefficiencies of current PA processes, while also remaining compliant, healthcare organizations are rapidly shifting towards an electronic Prior Authorization (ePA) solution with focus on four key areas:
- Secure and compliant interoperable APIs for real-time data exchange
- Automation and AI for faster decision-making
- Cloud-based platforms for scalability and flexibility
- Advanced analytics and reporting
While developing an ePA solution will address the current needs of the organization, there are additional challenges that must be considered in its implementation such as integrating with legacy electronic health record (EHR) systems, navigating unstructured medical policy data, and ensuring real-time data exchange without disrupting clinical workflows. Adopting a platform engineering approach—building a standardized, reusable internal platform that abstracts complexity and provides self-service tools—can streamline ePA integration, improve scalability, and accelerate deployment while maintaining security and compliance across systems.
Red Hat’s platform engineering approach to ePA
Red Hat supports a platform engineering approach to ePA with a composable, cloud-native platform that unifies infrastructure, development, and operations, allowing cross-functional teams to deliver secure, automated, and intelligent ePA services, enhanced by agentic artificial intelligence (AI). This foundation accelerates scalable innovation across both clinical and administrative functions.
Red Hat’s platform includes:
Hybrid cloud platform for AI: Red Hat® OpenShift® AI provides a unified platform for managing the lifecycle of predictive and generative AI (gen AI) models at scale, across hybrid cloud environments. With the platform, users can work alongside large language models (LLMs) and graph retrieval augmented generation (RAG) to gain insights from specific data sets such as clinical practice guidelines, patient records, or medical policies. This streamlined approach provides answers that are fast, accurate, and prioritized. In addition, the answers use natural language (rather than clinical language), making them contextually relevant for facilitating medical review, policy assurance, audit, and benefits inquiry. In many cases, GraphRAG can eliminate the need to retrain the model for increased efficiency and cost savings.
With OpenShift AI, organizations can also manage the costs of inferencing with distributed serving through an optimized vLLM framework. To further reduce operational cost and complexity, it offers advanced tooling to automate deployments and self-service access to models, tools, and resources.
Integration and API: Red Hat Integration has a full suite of Fast Healthcare Interoperability Resources (FHIR) connectors for existing application programming interfaces (APIs), following HL7 standards such as the Da Vinci Project. This supports the documentation and transparency requirements within the rule.
Automation: Red Hat Ansible® Automation Platform allows for the automation of routine tasks, reduces errors, and streamlines processes. By pulling data into an automated prior authorization workflow, claims and required documentation can be expedited. This also reduces the burden of highly customized claims systems that require manual effort to maintain and upgrade.
Security and Compliance: Red Hat OpenShift AI and Red Hat Ansible Automation Platform can be used together to provide enterprise-grade security and compliance. OpenShift provides core security features like access controls and networking, while Ansible Automation Platform allows for automating security tasks and managing compliance, supporting HIPAA and CMS compliance with robust audit logging, encryption, and access controls.
Why choose Red Hat?
Flexible
Access multiple, disparate data sources; run AI workloads against those data sets—on-premise or in the cloud—to provide contextually relevant decisions.
Security-focused
Limit data exposure in LLMs running on Red Hat’s platform.
Scalable
Scale to support new regulations and initiatives for enhanced patient outcomes and member experiences.
Gain efficiency and scale with an agentic AI framework
In healthcare, data is typically spread across multiple data sources and in different formats, from structured to unstructured. By using an agentic framework, smaller AI models can run against data specific to your organization, with an additional model summarizing the result. This approach creates a more accurate query, producing clinically relevant results and saving on data costs as less compute is required.
With an agentic framework, healthcare organizations can easily scale to cover other AI use cases such as:
- Summarizing clinical notes for payer justification
- Extracting key information from unstructured data
- Document generation and form filling
- Multisource data extraction and normalization
This approach supports a strategic transformation of the PA process using AI. By converting complex medical policies into decision tree representations (DRTs), a foundation is built for automated, rules-based decision-making. When combined with an agentic workflow that dynamically populates each DRT with member, or patient, specific contextual data that supports a substantial reduction in manual processes that can significantly reduce processing times. Together, these capabilities let provider and payer organizations deliver a more efficient, patient-centered experience.
Streamline prior authorization and improve outcomes
Red Hat provides a comprehensive platform approach in support of the current prior authorization rule requirements, with the agility to support additional claims management initiatives as needs evolve.
With Red Hat, healthcare organizations have the flexibility to navigate the evolving healthcare landscape while avoiding vendor lock-in. Visit redhat.com/health to see a demo or contact your Red Hat Account Representative to have an exploratory conversation.
American Medical Association. 2024 AMA prior authorization physician survey, 2025.