Improve workflows with NLP and AI-enabled fax for clinical records

Most faxed patient data cannot be used immediately — until someone performs a manual task

In today’s healthcare landscape, the integration of cutting-edge technologies like natural language processing (NLP) and artificial intelligence (AI) is proving to be pivotal for streamlining and automating cumbersome clinical workflows. Intel’s former Chief Data Scientist, Bob Rogers, in collaboration with the University of California, San Francisco (UCSF), unveiled groundbreaking insights that could revolutionize the way healthcare organizations handle patient data.

Overcoming manual challenges in healthcare workflows

The prevalence of faxed patient data poses a significant challenge in healthcare systems. Traditionally, manual intervention was required to process these faxes, causing delays and inefficiencies. The reason is that faxed documents are unstructured data – data that is not ready to be consumed by a clinical system. Rogers’ pioneering research delved into the implementation of NLP and AI techniques to transform these unstructured fax documents into organized, actionable data.

The impact of NLP and AI integration

Bob Rogers is currently an Expert in Residence for Artificial Intelligence at UCSF. As he explained to CMSWire (a leading publication for the customer experience industry), Rogers assembled a team of scientists in 2022 to improve the fax workflows of the university’s healthcare system — because the existing fax processes were tedious and created significant inefficiencies for the staff.

UCSF Health receives more than 1 million faxes each year. And although the health system uses an electronic fax solution — which is more efficient than receiving the documents on a paper-based fax machine — the old process was simply to convert inbound faxes to PDFs and route them to a university server, where they sat until someone reviewed them.

As Rogers put it: “First, the raw data from faxes were dumped into a processing queue. Next, patient appointments were added to an electronic health record. And finally, various diagnostic reports were scanned and uploaded to the patient’s chart.” All of these manual workflows, he added, usually required the manual intervention of several people.

The game-changer: Applying NLP and AI to patient faxes

Rogers’ team successfully implemented NLP and AI algorithms to automatically extract essential data from incoming faxes. This automated process significantly streamlined clinical workflows, reducing the need for extensive manual labor and expediting patient care processes. By leveraging AI for feature extraction, UCSF Health witnessed a paradigm shift in their operations, moving away from manual review and data entry.

The efficiency breakthrough, Rogers explained, was applying NLP and AI to the inbound faxes — to automatically identify the type of fax, pull key data from it, place that key data in the correct fields in the university’s EHR, and take whatever other next actions were required to move the patient’s care forward.

As Rogers explained, by turning the unstructured data in those faxed PDFs into structured and actionable data, his team was able to create a far more efficient and quicker series of clinical workflows — which freed UCSF Health’s staff from the time-consuming manual tasks that those faxes had previously required every day.

In contrast to its previous, high-touch workflows, the health system’s AI-enabled fax processes leveraged automation to move faxes forward with little or no human intervention: “Connect the fax directly to the charts of the existing patients and create a new record for new patients,” Rogers said. “Now, schedule the patient electronically. Use AI feature extraction to index key contents of additional uploaded diagnostic files.” 

Rogers concluded: “This is a game-changer for hospitals and health systems.”

Meet Clarity: NLP and AI-enabled fax for clinical records

Recognizing the persistent challenges faced by healthcare organizations, solutions like Clarity from Consensus Cloud Solutions offer a transformative approach. Clarity employs NLP and AI engines to convert unstructured fax documents into digitized, actionable content. This innovation not only eliminates manual review and data entry but also mitigates the potential for human error, ensuring swift and accurate patient care.

Embracing the future of healthcare automation 

Healthcare providers can leverage AI-powered tools to enhance patient care, minimize delays, and streamline operations. Solutions like Clarity mark a pivotal shift in healthcare’s clinical workflow automation, enabling healthcare organizations to save time, reduce errors, and expedite patient access to care. 

Ready to experience the transformation? 

Schedule your complimentary demonstration of Clarity, the AI-powered solution designed to revolutionize your clinical workflows.

Having worked with thousands of healthcare organizations over several decades, we at Consensus Cloud Solutions have found that the manual review and re-entry of faxed patient data remains one of the most time-draining and costly workflows facing providers — and it creates the ongoing risk of delays in patient care.

That’s why we developed Clarity — an NLP and AI engine that helps healthcare organizations like yours turn your unstructured fax documents into digital, actionable content that can help your company:

• Save enormous amounts of time by eliminating manual fax review and data re-entry.
• Reduce the potential for human error present every time your staff needs to manually re-enter the contents of a patient record into another platform or database.
• Speed your patients’ access to care by leveraging AI to automate key fax workflows — scanning faxes for urgent messages and routing important patient information to the right members of your team.

Ready to see it in action?

Book your free demo of the AI-powered Clarity