Think of AI agents as the building blocks of a customizable workflow engine—each one optimized for a specific task, much like assembling a bespoke tool kit tailored to your organization’s needs.

Consider these real-world applications:
● Prior Authorization: AI co-pilots rapidly analyze medical records and payer guidelines, pre-validating claims to cut approval wait times from weeks to hours.

● Care Gap Closure: AI scans unstructured patient records to pinpoint missed screenings or treatments, allowing care teams to intervene before conditions escalate.
● Risk and Quality Assessments: AI-driven models classify patient risk and evaluate care quality, driving proactive interventions and improving outcomes.
● Case Management: AI compiles case summaries from scattered data sources, equipping case managers with a complete, real-time picture of patient needs.

Making AI work for healthcare — not against it
The key to making AI effective in healthcare is context. AI agents must be deeply embedded with domain-specific knowledge, leveraging pre-trained models and industry knowledge graphs to operate within real-world clinical and administrative settings. This means:

● Extracting meaning from unstructured data—turning free-text clinical narratives, handwritten notes, and medical images into actionable insights.
● Integrating disparate data sources—pulling together EHRs, imaging systems, and payer databases into a unified, intelligent workflow.
● Ensuring traceability and compliance—offering explainability and auditability, which are critical for regulatory approval and operational trust.

The 13-year-old waiting for an MR: A case study
Imagine a 13-year-old suffering from debilitating migraines. Their doctor orders an MR, but before the scan can happen, prior authorization is required. Without AI, this process can take weeks—medical records must be manually reviewed, payer policies cross-checked, and back-and-forth communication ensues. Sometimes the first round can result in the patient not receiving the authorization which can provide undo stress, not just for the patient but for the healthcare professionals that are trying to care for their patients.

Now, introduce AI-powered agentic workflows. The AI agent instantly retrieves the necessary clinical notes, verifies compliance with insurer policies, and submits a pre-approved request—all within minutes. The result? The patient gets timely care, administrative overhead shrinks, and doctors spend more time treating patients instead of chasing approvals.

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