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eFax Automation

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01 Revenue Cycle Automation → 02 eFax Automation →

eFax Automation

eFax & Intelligent Document Processing Solutions automate the intake, extraction, and routing of faxed healthcare documents into EHR systems using AI-driven document understanding. This enables faster referral processing by converting unstructured fax referrals into structured data and automatically directing them into the appropriate clinical or scheduling workflows.

Healthcare professional using digital document automation
99.6 %

accuracy in routing inbound faxes

to the appropriate specialty workflow.

Challenges eFax Automation Solves

  • schedule

    Slow referral intake and patient access delays

    Faxed referrals can sit in queues before they are reviewed, entered, and routed, slowing down scheduling and time-to-care.

  • assignment_late

    Administrative burden from manual referral processing

    Teams spend valuable time reading documents, entering data, checking details, and moving referrals between systems.

  • leak_remove

    Referral leakage and lost revenue opportunities

    When referrals are delayed, misrouted, or difficult to track, organisations risk losing patients and downstream revenue.

  • rule

    Incomplete, inconsistent, and error-prone referral data

    Unstructured documents and manual transcription can create missing fields, duplicate records, and avoidable rework.

  • visibility_off

    Limited visibility into referral performance and bottlenecks

    Without real-time insight, teams struggle to see referral status, workload volumes, turnaround times, and where delays occur.

  • groups

    Growing referral volumes without the capacity to scale

    As referral demand increases, manual processes make it difficult to keep pace without adding more administrative resources.

Benefits

  • forward_to_inbox_24dp_0000FF_FILL0_wght200_GRAD0_opsz24

    Accelerate referral intake

    Process referrals faster and reduce delays in patient scheduling and access to care.

  • task_alt_24dp_0000FF_FILL0_wght200_GRAD0_opsz24 (1)

    Increase productivity

    Eliminate manual data entry and administrative work, allowing teams to focus on higher-value activities.

  • fact_check_24dp_0000FF_FILL0_wght200_GRAD0_opsz24 (1)

    Improve data quality

    Reduce transcription errors, duplicate records, and incomplete referral information.

  • visibility_24dp_0000FF_FILL0_wght200_GRAD0_opsz24 (1)

    Enhance visibility

    Gain real-time insight into referral status, volumes, bottlenecks, and turnaround times.

  • groups_24dp_0000FF_FILL0_wght200_GRAD0_opsz24 (2)

    Scale without adding headcount

    Handle growing referral volumes efficiently while maintaining service quality.

  • health_and_safety_24dp_0000FF_FILL0_wght200_GRAD0_opsz24

    Improve patient access

    Ensure referrals are processed quickly and accurately, helping patients access care sooner.

Case Examples

fact_check

eFax automation — Referral Management

An eFax referral management solution automates the intake, processing, and routing of faxed referrals into the EHR using AI-powered document understanding. It extracts structured data, converts referrals into orders, and routes them to the correct workqueues, with human review for exceptions.

This reduces manual data entry, speeds up patient access, improves visibility into referral status, and helps minimize referral leakage.

Case

A large academic health system implemented eFax automation to convert inbound referrals into structured data, eliminating manual transcription. This reduced intake delays and ensured referrals moved directly into scheduling and referral workflows, improving time-to-care and reducing leakage.

An exception-based model automated the majority of referrals, while incomplete faxes were routed for review — allowing teams to focus on exceptions and significantly improving throughput and efficiency.

  • Achieved 99.6% accuracy in routing inbound faxes to the correct specialty workflows
  • Delivered 97% data extraction accuracy
  • Reduced manual intervention to less than 15% of total fax volume, enabling higher-value work and patient-facing activities

Get in Touch

Tom Herrmann

Tom Herrmann

North America – Vice President, Revenue Cycle Transformation

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Tom is a healthcare revenue cycle leader with over 20 years of experience across Patient Access and Revenue Cycle operations within large academic healthcare systems. He has led organizations in improving operational performance, increasing revenue, and enhancing patient financial experience. Tom is passionate about leveraging emerging technologies and intelligent automation to drive efficiency, improve revenue capture, and reduce denials across the Revenue Cycle.

+1 617 962 1409
thomas.herrmann@digitalworkforce.com
Jennifer Carmichael

Jennifer Carmichael

North America – Director, Revenue Cycle Automation

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Jennifer is a healthcare technology and revenue cycle professional with extensive experience supporting patient access and revenue cycle transformation within large academic healthcare systems. At Digital Workforce, she partners with health systems to implement intelligent automation strategies that improve financial performance, reduce administrative burden, and enhance patient and staff experiences. Jennifer brings deep expertise across Epic applications including ADT, Prelude, Cadence, Grand Central, and Benefit Engine.

+1 978 987 8664
jennifer.carmichael@digitalworkforce.com

Lindsey Hylwa

North America – Sales Director, Intelligent Automation

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Lindsey is Sales Director for Intelligent Automation at Digital Workforce, where she leads enterprise engagements across the US, helping organizations transform operations through automation, AI agents, and end-to-end process orchestration. She focuses on delivering measurable value in large-scale digital transformation programs with particular expertise in healthcare and regulated industries.

+1 919 880 4969
lindsey.hylwa@digitalworkforce.com