Bolstering referral management with a streamlined approach using digital, AI-powered fax

Industry research suggests that as many as 56% of referrals are sent by fax, often due to interoperability issues and lack of effective information sharing capabilities between providers. For post-acute care and other ambulatory health care providers, which often rely on a network of providers to get patients in the door, these referrals are paramount to ongoing sustainability, continuity of care, and increased revenue.

Yet stats suggest that in many cases (between 40-65%), referrals are simply never completed, whether for a diagnostic test or an in-person specialist visit. Delays associated with manual referral management processing often lead to no-shows and abandoned referral pathways (otherwise known as referral leakage), equating to trouble for patients and providers in the form of poorer outcomes and lost revenue.

There is a better way. Advancements in cloud-based digital fax—alongside new AI capabilities—can take old-school process bottlenecks associated with fax and turn them into referral management superpowers, speeding up the referral process so patients' care is not interrupted.

Streamlining fax referral with AI

Organizations today face a slew of challenges just getting a patient in the door, including days’ worth of referral backlogs that staff must review, possibly missing urgent requests. Additionally, benefits checking and prior authorizations take even more time, further slowing the process of scheduling an appointment.

Fax has long been the preferred referral delivery method and remains so to this day. Unfortunately, many organizations still rely on manual processes to input patient information from paper and digital faxes into their systems. Consequently, they can’t handle the increased volume of patients (and their information) that practices see today.

When the right AI capabilities are applied to digital cloud fax and other unstructured data, health care organizations can automate these processes and push intake through faster. Intelligent data extraction automates the process of populating an existing EHR with relevant information, sending data directly to the most relevant workflow. Not only can these AI solutions extract relevant information from scanned documents that come in via fax or are handwritten, but clinically-trainedAI can also flag the document type, including referrals, then route it to the right department.

Sophisticated document classification eliminates the need for staff to manually review every fax. This enables them to find and respond to referrals faster, focusing solely on the required action, and directly supporting the "race to yes." Furthermore, this AI is specifically trained to identify critical indicators, such as the word "urgent" often handwritten on a document, and instantly flag those cases for priority triage. This quick identification and routing shortens the referral response time, ultimately leading to better patient experiences and driving critical growth by maximizing revenue and capacity planning.

Considering that some estimates note it takes up to 70 minutes for a staff member to process a referral, this automation can save staggering amounts of time over the course of a week, month, or year, while simultaneously getting patients in the door faster.

Patient data entry is the task that eats up the majority of staff time and can naturally lend itself to typos, errors and mistakes that are, at best, inaccurate and, at worst, pose a risk to the patient’s care and outcomes. Using AI and large language models, unstructured faxes will no longer be a part of the blocker. They will be able to translate these paper, handwritten, and scanned documents into correctly sorted and actionable information within a patient’s record.

AI-powered digital fax in action

It might seem backwards to consider the long-used fax as a method of communication that should be modernized, not ignored. With the right tools, health care organizations can address numerous workflow challenges in mission-critical processes such as referrals.

As an example, one imaging provider receives an average of 30,000 orders per month. This high volume means staff will consistently work against referral backlogs, delaying care, frustrating patients and providers, and burning out staff and administrators who constantly process referrals with no end in sight.

AI-powered fax referrals streamline the processing of imaging orders. By applying AI to unstructured data, the information is converted into structured, mapped content, leading to faster reception of orders into the system of record. Not only can the implementation of AI in the referral process cut days off the referral turnaround time, but it can also stem the flow of referral leakage, capturing requests faster, before patients turn to a competing imaging practice or just abandon the referral. This automation also significantly reduces the administrative workload on staff, freeing them from tedious manual data entry and allowing them to focus on higher-value tasks, which directly boosts job satisfaction and overall efficiency.

Removing the bottleneck

Referrals are historically one of the most challenging—and priciest—areas of inefficiency in health care, but organizations can implement new AI-powered digital fax workflows to change this dynamic. By using health care-specific models and solutions across multiple aspects of the referral process, organizations can dramatically speed referrals, eliminate information gaps, and optimize staff resources—ultimately streamlining formerly clunky processes to improve experiences and outcomes across the board.

Bevey Miner, is executive vice president, Healthcare Strategy and Policy, Consensus Cloud Solutions