The Slow Death of The Fax Machine: How AI Transforms Healthcare Fax Workflows

Did you know that most of the faxes sent each year—around 75% — are in healthcare? That’s a whopping 9 billion faxes globally, all within healthcare.

For decades, fax machines have been the backbone of communication in healthcare. Physicians and providers use fax machines, or now more commonly, electronic fax (efax), to exchange crucial medical information among healthcare professionals, pharmacies, laboratories, insurers, nursing staff, and patients.

However, the dependency on fax comes with various challenges, including:

  • Time consuming triaging and processing of incoming faxes, repetitive tasks, and manual data entry, contributing to admin burden.
  • There have been delays in patient care due to lost or misplaced faxes, whether related to referrals, results, prior auth, or other critical workflows.
  • Disjointed communication, with limited confirmation and acknowledgment, often contributes to patient errors as patients navigate health systems.
  • The lack of digitization and interoperability with Electronic Medical Record (EMR) systems and downstream workflows makes it difficult to track and manage faxed documents efficiently.
  • Unencrypted transmissions pose significant risks of losing intercepted documents and data security.

That is why the transformation from analog to digital fax workflows is crucial for modernizing healthcare communication. Here is where Phelix comes into play.

What is Phelix?

Artificial Intelligence (AI) and intelligent automation have been integrated into many industries, and healthcare is no exception. Phelix is an AI-powered automation platform specifically designed to save over 75% of staff time spent on repetitive healthcare workflow tasks linked with EMR and other health record systems.

Phelix automates a range of tasks across clinic workflows, including:

  • Triaging faxes
  • Answering phone calls
  • Scheduling appointments
  • Managing referrals
  • Streamlining prior authorization workflows
  • Task automation
  • Facilitating intake processes
  • Charting and summarizing records
  • Follow-ups and navigating care gaps

Phelix Fax AI:

Phelix’s Inbox Assistant offers an industry-leading AI solution for triaging and processing incoming faxes, HL7 messages, e-mails, e-referrals, and other documents. This module automates the handling of incoming faxes, improving searchability, saving time on fax processing, improving turnaround times, and minimizing data errors.

Phelix’s proprietary Fax AI model is built from the ground up and tuned specifically for various tasks and workflows associated with triaging healthcare faxes, including:

  • Searching for patient faxes within seconds
  • Classifying and naming documents
  • Looking up and tagging patients in the EMR
  • Creating new referrals and all associated details
  • Checkbox requisition detection
  • Assigning to provider inboxes
  • Creating tasks or ticklers
  • Identifying urgent faxes
  • Splitting faxes with multiple patients

How Does Phelix’s Fax AI Work?

Phelix leverages state-of-the-art AI to revolutionize fax processing & downstream workflows in the healthcare industry. Here’s how it works:

Faxes Synced from eFax or Shared Drive: Phelix’s Fax AI seamlessly integrates with your existing eFax services or shared drives, automatically syncing incoming faxes for processing. This eliminates the need for manual uploads and ensures all documents are captured in real-time.

Multi-Page document crawling: Once synced, the system features sophisticated multi-page crawling, including native cover page detection and processing of documents across multiple pages. This ensures accurate classification and comprehensive processing of all information, even if multiple patients are referenced within a single document. The system scans and can also split the document into single or multi page segments as necessary.

Document Classification: Phelix’s AI classifies documents into predefined categories such as consult notes, insurance authorizations, prescriptions, referral letters, and more. Additionally, we support custom documentation classification and naming conventions tailored to the specific needs and workflows of the clinic. This flexibility allows clinics to manage upto hundreds of unique document classes effectively.

Field Level Data Extraction: Phelix extracts detailed information at the field level, including:

  • Patient Details: Name, date of birth, gender, contact details, and health card/social insurance information.
  • Provider Information (From) Physician name, contact details, address, provider ID, NPI, facility, and specialty.
  • Recipient Details (To): Information about the intended recipient of the fax.
  • Insurance Information: Details of primary and secondary insurance, plans, and subscriber information.
  • Priority Detection: Urgency indicators such as ASAP, STAT, or urgent notes.
  • Diagnosis and Referral Details: Relevant clinical information, reasons for referral, and summaries of medical history.
  • Date Extraction: Referral dates, visit dates, procedure dates, consultation dates, and encounter dates.

User Review + Auto-Filing: After extraction, the information is presented for user review. The user interface is optimized to reduce the number of clicks and save time associated with triaging faxes. This step allows for any necessary adjustments before the data is automatically saved, ensuring the highest level of accuracy and security in document handling. Over time, Phelix captures input to achieve accuracy levels over 95%. Once confident in the system’s accuracy, users can enable auto-filing of document types to bypass the review step entirely.

Responses for Faxes: Phelix provides templated responses for responding to faxes, such as missing items in referrals or auto replies to pharmacies and insurance companies. This feature streamlines communication and ensures quick follow-up.

EMR Integration and Workflows: Phelix seamlessly integrates with Electronic Medical Record (EMR) systems including assigning documents for provider review, creating patient charts, entering referrals, and creating and assigning tasks. The integration settings can be configured to a granular level, providing a wide range of options to fit the specific needs of your clinic’s workflows and EMR.

By following these steps, Phelix’s FaxAI delivers a comprehensive, efficient, and user-friendly solution for automating and optimizing fax workflows.

Benefits of Using Phelix For Healthcare Industry

  • Save time: By automating document processing tasks, Phelix helps save more than 60% of clinician time related to fax handling. As a result, it helps healthcare professionals to focus on delivering quality patient care. 
  • Quick turnaround: Phelix improves turnaround times by 2-4X, significantly speeding up patient care processes.
  • Out of the box Accuracy: Phelix reduces manual data entry errors, ensuring 90%+ accuracy in patient-related extraction and 70-80% in other tasks. This accuracy improves over time, leading to more reliable patient information and smoother workflows.
  • Productivity Tracking: Phelix allows for productivity tracking at the user or fax level. This kind of data granularity is not possible with EMR (Electronic Medical Records) or other systems, providing unique insights into operational efficiency.
  • Enhanced audit trails: Phelix ensures compliance with data security and privacy regulations by encrypting sensitive information and detailed audit trails for document access and handling.

The Bottom Line

In essence, the integration of AI with OCR technology in Phelix represents a significant leap forward in digitizing healthcare fax workflows. By harnessing the power of AI to understand, interpret, and act upon faxed documents, Phelix enables healthcare organizations to achieve unprecedented levels of efficiency, accuracy, and patient care quality. In short, Phelix plays a crucial role in shaping the future of healthcare communication and patient care delivery.

If you also want to leverage the benefits of Phelix, contact us and book a demo.

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