Using Artificial Intelligence to Improve the Hospital Revenue Cycle

The financial drivers CFOs care about most

Throughout my years in healthcare, I have come to understand the challenges hospitals and their CFOs face in budgeting.

A hospital CFO's number one objective is keeping the organization's doors open. CFOs zero in on their hospital's overall operating margin and the operating margins of each individual service line.

So, what has the biggest impact on operating margins? Labor costs typically eat up more than half of a hospital's operating revenue, and that allotment is poised to increase as organizations face continued pressure to raise salaries and wages. Hospitals are now rethinking the roles of some employees.

The revenue cycle is one area of the hospital that is labor-intensive. Hospitals have to ensure their organizations are paid for services rendered or, in other words, that they collect payments from patients and payers. Financial leaders need to consider revamping their organization's approach to revenue cycle management.

Common holes in the revenue cycle

Hospitals are constantly battling denials as payers require authorization for more types of procedures or adjust policies without any notification to providers. A denied claim triggers effects that spill over to disrupt other aspects of the hospital's finances. For example, after a payer denies a claim, administrators are forced to chase the denial, which often requires multiple calls to the ordering physician and working closely with the payer. This is a time-consuming, and not always rewarding, process. The claim then sits in accounts receivable until it is adjudicated, which takes days to months.

Reprocessing claims drives up labor costs as billing staff is forced to devote more time to unpaid claims. According to research from the American Medical Association, the industry could save $15.5 billion each year if companies processed claims correctly the first time.

The hospitals and health systems I have worked with have pointed toward lower dollar accounts as another key area where revenue is lost or delayed. That is because hospitals often lack sufficient resources — such as staff or budget — needed to touch each and every patient account. What ends up happening is organizations focus primarily on the high-dollar accounts, which means many low-dollar accounts slip through the cracks. Unfortunately, all those missed payments from low-dollar accounts add up.

Hospitals often turn to an outsourced vendor to tackle these low-value, high-volume accounts. But similar to in-house teams, these outside partners aren't always able to physically act on all accounts.

On the bright side, there's a potential solution for this persisting challenge: inserting AI into revenue cycle processes.

Improving the revenue cycle, starting with artificial intelligence and automation

As leaders devise revenue cycle improvement plans, they should consider how proposed solutions could affect bottom lines and operating margins. Leaders should also determine the resources needed to fulfill plans, such as an outsourced partner or a tool built in-house or purchased elsewhere. AI-enabled automation is one such tool that may help.

This intelligence-based category of automation tools frees staff from necessary but redundant and time-consuming tasks, and it enables the organization to reposition skilled workers toward meaningful quality assurance programs within the revenue cycle. Automating some processes within the revenue cycle is an affordable way for organizations to reduce labor costs and recover leaked revenue since it enables organizations to touch both high- and low-dollar accounts.

When hospitals automate portions of the revenue cycle, they can execute a higher volume of claims at a cost-effective rate and regain their edge. And as the machine learning components of this automation learns, it unleashes meaningful insights to the organization and allows for ever-more opportunities for efficiencies.

Automate the mundane using AI to move employees into modern roles

AI in the revenue cycle is really about revenue integrity, a hospital's ability to achieve operational efficiency, compliance, and optimal reimbursement. The technology allows hospitals to repurpose employees and mitigate revenue leakage in ways that require more critical thinking.

Automation takes high-volume, repetitive, and mundane tasks off employees' workloads, allowing hospitals to expand production at a much lower cost. Hospitals can then re-invest these freed up resources into those tasks that require a more human touch such as empathy, creativity, and complex thought.

AI allows organizations to do a few things differently with their revenue cycle staffing and strategy.

First, with redundant tasks accounted for via automation, hospitals can strategically reassign skilled workers to duties they've historically struggled to fill or to non-urgent but essential projects that have sat too long on the backburner.

Second, AI enables organizations to address workforce shortages. For example, rural markets often have trouble attracting top talent and may struggle to fill important positions. On the other side of the coin, hospitals in competitive markets may struggle to retain employees they have invested in. By automating portions of the revenue cycle, rural hospitals can move loyal and committed staff members into positions that have been difficult to fill due to talent shortages.

Third, AI can help talent retention in more competitive markets, as hospitals can reward loyal employees with more consequential roles as they are no longer needed for tasks that can be completed with automation.

Moreover, AI enables healthcare organizations to be more strategic with the work they outsource. Hospitals can work the accounts likely to be paid in-house while outsourcing the others to a third party.

Overall, AI is really a movement toward an exception-based work environment in which employees only take on tasks automation cannot. In such a workflow, people will only be notified to monitor automated tasks on an exception basis. Automation can help reduce or eliminate the risk for error made by a person charged with typing day in and day out or copying information verbatim from an insurance card or EHR system.

In the same way, AI helps control where sensitive patient information is sent. It eliminates the need for at least one set of eyes on the data and enables information to be securely sent and accessed, meaning hospitals have greater control over who accesses patient data and where it goes.

Getting started

One question I hear often is, "Where should I start?" My advice? Start simple.

The best tasks to automate are tedious, high-volume, and repetitive. In the revenue cycle, some of these processes include checking the status of claims, working denials, or reviewing eligibility. These tasks are typically time-consuming and copy-and-paste intensive. By automating them, a hospital can address every patient account, regardless of the dollar amount attached to it.

After tackling the easy stuff, organizations can progressively deploy AI for more advanced capabilities.

Still, justifying spending thousands of dollars on new technology can be difficult. Organizations are inundated with high expenses. Consider the EHR — a single hospital stands to spend millions of dollars on a new system. But this is the wrong way to think about automation. Hospital leaders shouldn't think about AI and automation as another price tag, but as a path to savings. What automation comes back to is being able to accomplish more with less.

Since automation enables staff to accomplish more work with fewer resources, hospitals can put additional quality controls and checks in place to help speed the time required for processing claims, reduce days in accounts receivable and reduce denials.

That's because automation via an AI system helps staff in a couple of important ways. First off, it completes nearly 100 percent of eligibility checks on the front-end of the revenue cycle. Additionally, it helps highlight changes in payers' reimbursement policies, which helps employees act sooner to reduce AR days or notice variations in accounts much earlier.

Here's an example: Before automation, one hospital I worked with was spending nearly 100 hours per day checking claims statuses. With automation, the hospital was able to get through that same amount of volume in 90 minutes per day, freeing up staff to further the revenue cycle claims management process rather than waiting for payers to respond before proceeding. Automation helps get more answers with less manpower, an AI helps them turn those answers into new solutions.

Planning for the future

Nearly every hospital CFO needs options to do more with less. AI helps hospitals operate smarter, not harder. Through automation, hospitals level up to achieve exceptions-based environments in which employees are empowered to focus solely on work that requires the human touch. Whether a hospital is operating efficiently now or struggling and in need of improvement, every organization is at its best when people are serving the best purpose.

About the author: Braden Lambros
As an artificial intelligence transformation leader at Olive, an AI as a service (AIaaS) company, I observe the promise and potential of automation in cost control firsthand. I have devoted my entire career to healthcare, working as a consultant focused on revenue cycle and other labor or non-labor areas. I have worked with more than 25 healthcare organizations, from small hospitals to some of the largest health systems and academic centers in the U.S.

About Olive:
At Olive, we strive to build revolutionary artificial intelligence and robotic process automation solutions for the healthcare industry to help improve business productivity. Our efficient, cost reducing options deliver positive results with Olive overseeing repetitious high traffic processes and workflows. These specialized tools empower our customers by delivering the freedom to do the hardwork of building the future of healthcare. To learn more, visit our website.