An Automated Solution to Healthcare’s $125 Billion Fax Problem

By Thomas Thatapudi, CIO, AGS Health

In 2018, the head of the Centers for Medicare and Medicaid Services issued a challenge to health IT developers and providers alike to “help make every doctor’s office in America a fax-free zone by 2020.”

The challenge was issued out of frustration with a vital workflow that remains reliant on outdated fax technology. Each year, healthcare providers exchange over 9 billion fax pages, driving an estimated $125 billion in costs across the healthcare system.

The continued reliance on fax technology is a persistent challenge for healthcare, undermining data integrity and operational efficiency. Studies by DirectTrust reveal alarming statistics: 30% of tests must be re-ordered due to lost faxes, and 25% fail to arrive on time for patient visits. Additionally, integrating faxes into health systems often demands manual indexing—an expensive and time-intensive task many organizations can ill afford.

Fortunately, automation offers a solution. Machine Learning and Generative AI are particularly adept at handling repetitive tasks such as fax indexing. While achieving perfect accuracy from the outset is unlikely, pairing AI-driven Digital Workers with human oversight ensures exceptions are managed effectively. Over time, as AI systems learn and adapt, they can assume more complex responsibilities.

To succeed, this model requires a carefully designed workflow that balances human expertise with AI capabilities to meet quality, timeliness, and accuracy standards.

Building the Digital Workforce

A successful hybrid fax indexing strategy relies on a carefully designed digital workflow model that effectively coordinates efforts between human staff and Digital Workers. The process begins with identifying the necessary technologies, which is best accomplished by observing human indexers to gain a comprehensive understanding of their workflows and unique requirements. This insight informs both implementation planning and feasibility testing.

Digital Workers are equipped with advanced intelligence and automation tools to streamline fax processing. Utilizing optical character recognition (OCR), they convert faxed documents into machine-readable text, while natural language processing (NLP) models interpret and manage the embedded data. Generative AI is then applied to classify faxes based on the sender’s documentation format, assess confidence thresholds, and either integrate the data into a documentation management system or EHR or direct it to manual validation workflows.

Through Machine Learning, Digital Workers continuously adapt to new document formats, refine categorization methods, and align with providers’ templates and styles. Every processed fax contributes to greater accuracy, enhanced efficiency, and reduced exceptions over time.

To ensure long-term success, monitoring key performance indicators (KPIs) is essential. Metrics such as daily indexing volume, accuracy rates, turnaround times, and overall productivity provide valuable insight into performance and progress.

Reality-based Deployment

While automated fax indexing has been around for some time, Digital Worker-driven automation is a relatively new entrant in the burgeoning field of healthcare AI, one that has already had an impact. For one health system, implementing automated fax indexing has put it on track to save approximately $2 million in annual expenses.

Automation reduced the number of manual indexers required to process the health system’s fax volume, enabling key team members to focus on higher-value tasks while achieving a near-perfect accuracy rate and 24-hour turnaround time. Over time, Digital Workers’ capabilities will expand, raising the automation rate and decreasing the need for human intervention, increasing anticipated cost savings.

While a completely fax-free healthcare system may remain out of reach in the near term, automation and AI technologies offer practical solutions to digitize the process. By leveraging these tools, healthcare organizations can significantly reduce costs, boost productivity, and enhance patient safety. This, in turn, helps mitigate the long-standing challenges tied to fax communications.

Automated fax indexing exemplifies how AI can effectively address persistent, age-old issues. It brings innovation to a process that has long resisted modernization, paving the way for greater efficiency and progress across the healthcare sector.