Deploying Agentic AI in Healthcare
CLIENT
A healthcare group operating over 40 clinics and four hospitals across several U.S. states. The company serves more than 10,000 patients and works with a mix of public and private insurers.
Its digital environment includes several electronic health record (EHR) platforms, partner systems, and billing tools that have accumulated over years of expansion.
CHALLENGE
The client’s teams were spending a large share of their time moving information between systems. A single patient case could touch multiple applications — scheduling, insurance validation, lab results, billing, and reporting — each managed by different teams.
Routine coordination took effort. Doctors needed to check data in multiple EHRs before each visit. Billing staff often had to revalidate claims because key details were missing. Missed follow-ups were common, simply because reminders or lab results didn’t sync between systems.
Automation existed in pieces, but it stopped at task level. What the client wanted was something that could coordinate those tasks across departments — a system that could understand dependencies and act accordingly.
SOLUTION
REW Technology had already worked with this client before, leading a network modernization program that migrated core infrastructure to Azure. That project gave the company a secure, high-performance base for connecting EHR, billing, and scheduling systems through APIs.
In 2025, the client asked us to build on that foundation with agentic AI — a set of autonomous agents that could take on cross-department workflows.
We worked with clinical, operations, and IT teams to identify where automation could safely take over — processes that were structured but required too much human coordination. Together, we designed three types of agents:
Patient Coordination Agent
Pulled and verified patient data from multiple EHR systems.
Checked insurance coverage and authorization before each visit.
Prepared short pre-visit summaries for clinicians.
Claims and Compliance Agent
Scanned billing data for missing documentation or mismatched codes.
Compared each claim with payer rules and state regulations.
Flagged issues early to reduce claim rejections.
Care-Follow-Up Agent
Monitored lab results and post-visit data.
Identified patients who needed reminders or additional appointments.
Coordinated with scheduling teams automatically.
All three agents worked through a shared orchestration layer.
When a new lab result was uploaded, for instance:
The Care Agent notified the doctor.
The Claims Agent verified that billing coverage still applied.
The Coordination Agent reached out to the patient if a follow-up was needed.
Everything happened within minutes, without anyone copying data between systems. AI handled the predictable work, but people stayed responsible for decisions.
RESULT
After 5 months in production:
• Appointment coordination time dropped by around 70%.
• Administrative workload per clinician went down by roughly one-third.
• Missed follow-ups decreased by 45%.
• AI orchestration layer now handles 12,000+ automated interactions per month
Previously upgraded network and the AI system complemented each other. The modern infrastructure allowed smooth, secure data flow, and the AI agents gave that infrastructure awareness.
TECHNOLOGY STACK
• Agentic AI Layer (Claude + GPT-5) – reasoning and text-to-action engine. Claude processed long records and compliance; GPT-5 generated structured outputs and summaries.
• FHIR-Based APIs – unified data from Epic, Cerner, and Allscripts into a common format.
• Azure Cognitive Search – indexed treatment guidelines and payer rules.
• Power Automate & Azure Logic Apps – executed actions like scheduling, data sync, and alerts.
• Azure OpenAI Service – hosted securely within the client’s cloud tenant for HIPAA compliance.
• Azure Active Directory (RBAC) & ServiceNow – governed data access and provided a unified audit trail for every automated action and agent-to-agent exchange.
Agentic AI isn’t just for healthcare. The same orchestration principles apply to banking, manufacturing, supply chains, and public infrastructure. If you’re exploring what an “AgenticEye” could mean for your industry, let’s discuss how to get there safely and effectively.
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