Healthcare Process Automation Case Study

Healthcare Process Automation

Customer

Healthcare process automation was critical for this leading U.S. healthcare services provider specializing in network-enabled care delivery and point-of-care mobile applications. The organization employs 6,000+ people and supports a nationwide network of 160,000+ providers serving 100M+ patients.

Business Objective

The customer needed to:

  • Reduce turnaround time (TAT) for client-facing healthcare processes

  • Improve work quality and minimize manual error rates

  • Automate high-volume, repetitive transactions

  • Scale operations efficiently across a large provider network

  • Reduce operational cost dependency on manual work

  • Integrate multiple systems to ensure seamless data and workflow continuity

The goal was to build a scalable, AI-driven automation layer supporting large-scale clinical and administrative operations.

Scope of Services

BXI Technologies partnered with the customer to:

  • Deploy AI agentic agents to automate repetitive healthcare tasks

  • Integrate workflows across six core enterprise systems

  • Build and deploy automation across 16 end-to-end processes

  • Implement 49 production bots to minimize manual intervention

  • Standardize and streamline client-facing workflows

  • Deliver a scalable automation framework supporting 1.32M+ annual transactions

This created a centralized digital operations model that reduced process cycle time and improved SLA performance.

Benefits

The transformation delivered:

  • Significant reduction in turnaround time (TAT)

  • Improved accuracy and consistency across healthcare workflows

  • Enhanced operational efficiency with AI-driven agents

  • Better utilization of workforce through FTE savings

  • Streamlined workflows across six integrated systems

  • Improved SLA adherence for client operations

  • Automation at scale for multiple high-volume processes

Impact

  • 1,320,000+ automated transactions annually
  • 97,000+ FTE hours saved each year
  • 6 systems integrated
  • 49 production bots deployed
  • 16 processes automated end-to-end

This resulted in faster client delivery, reduced operational cost, and improved healthcare process automation at scale.

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