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Case Study

Orders/Referral Management

Turning a manual, paper-driven referral process into an automated, accountable workflow

The Challenge: Managing Orders Was Slow, Manual, and Risk-Prone

Before automation, the health system’s teams were buried under faxed, scanned, and emailed physician orders that required manual indexing and tracking. This created daily pain points across departments:

  • Lost or incomplete orders delaying patient care
  • Hours spent sorting and matching documents by hand
  • Manual faxes clogging workflows and costing thousands of dollars in paper
  • Missed scheduling opportunities and referral leakage
  • Provider frustration and weak visibility into referral activity

Each missing order represented lost revenue and strained provider relationships. We needed visibility, automation, and accountability.

Operations Director, Regional Hospital

The Solution: Naviquis Unified the Entire Order Lifecycle

Naviquis deployed an Intelligent Document Processing gateway to capture incoming orders, referrals, and supporting documentation, using AI agents to replace the manual review, indexing, and routing that previously consumed staff time.

The platform automates every step of the order lifecycle, from capture to communication, and was integrated directly with the health system’s existing EHR and departmental systems. This removed manual handling end-to-end while keeping referring providers in the workflows and formats they already knew, taking adoption friction off the provider side.

The Impact: From Paper Chaos to Digital Control

KPIResult
Paper eliminated1.3 million pages annually
Lost ordersReduced to zero
Scheduling speedImproved significantly
ROIOperational cost savings and faster revenue capture
Provider satisfactionImproved through frictionless communication

Naviquis delivered measurable ROI by removing manual touchpoints, speeding up scheduling, and giving leadership real-time referral insight.

Better order management means better provider relationships

Naviquis turns a once-manual, error-prone process into an automated, transparent workflow that benefits patients, providers, and revenue teams alike.

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