Bots in Hospital Revenue Cycle? Yep. Get on Board or Get Left Behind.


It’s getting tough in your revenue cycle that is. More volume. More complexity. More things that can and do go wrong. In no other industry is it as hard to get paid for providing a service. Take for example the explosion in demand for preventing and managing denials. That alone is a symptom of systemic complexity in an endlessly expanding sea of claims data.

And while many hospitals are justifiably experiencing tech fatigue, thanks to the industry onslaught of EMR and Population Health projects, more technology is needed to get out in front of this growing complexity in hospital revenue cycle.  

Why bots? First, let’s quickly define ‘bot’. A bot is an autonomous Robotic Process Automation, RPA for short, software that can run multiple repetitive, rules-based processes that need to occur between disparate systems. While there is some disagreement in the marketplace about whether or not AI (Artificial Intelligence) or Machine Learning are attributes of bots (or if bots are a type of personal view), there is growing clarity in their value. Compared to humans, they are not prone to error and do not work in shifts. They can absorb growing volume at scale and don’t need break time to do it.

How real is bot technology? In North America alone it’s a $209 million segment expected to grow to nearly $17 billion, yes billion with a ‘b’, by 2024 (source). And it makes sense as we see the explosion of disparate technologies across all industries creating greater demand for the ability to talk to each other to get work done.

Why bots in healthcare? No doubt your mind is already spooling up ideas. Let’s take a peek specifically into Revenue Cycle Management. No doubt your hospital system has at least a handful of systems within your revenue cycle (EMR, claims processing, etc.) with humans manually performing many repetitive tasks. You’re working in growing complexity and volume to ensure precision in accuracy and consistency in compliance. How do you reduce the onslaught of variability at scale relative to these simple, repetitive but critical tasks and workflows?

Let’s look at two specific areas of opportunity.

1)    Eligibility.

What’s the glaring issue here after you achieve initial cooperation? It’s completing eligibility processing while they are still receiving care. When they leave the doors of your hospital, cooperation drops by as much as 50%. So efficiency and accuracy are paramount. To accomplish this, there are dozens of repetitive back office tasks that must occur between disparate systems, most of which occur in a couple of general layers. There’s the layer within the hospital itself and the multiple disparate systems outside the hospital. Bots are autonomous and can accelerate moving patient eligibility data between those systems efficiently and accurately...while they are still onsite. Some of our hospital partners are already seeing the value with bot deployment in this area.


2)    Denial Management (or ‘prevention’ if your bot deployment can take you there).

Simply put, old is bad when it comes to claims. The growing complexity and volume in filing claims puts them at increasing risk for being the tune of millions of dollars. Of course you live that so you already know. But deploying bots can accelerate processing at scale through the assignment of rules that you likely already know but cannot execute against (or execute well) because of volume and human error. Some of our more forward-thinking hospital partners are showing commitment to exploring this path of bot deployment with us.

While it’s easy to want to reach for the low hanging fruit of probable labor savings, and that’s a worthy reach, the greater value is in the impact of capturing more top line revenue while avoiding headwinds in compliance mishaps. Bots can also free up a path to productivity gains in areas that do require human intelligence and touch. The impact actually goes beyond revenue cycle. The impact of bots can measurably improve the patient experience as well as the experience of your team. Winning all around.



Satish Cheema joined MedAssist in 2013 and brings to the company new product strategy, prioritization and product management expertise. With more than 12 years of healthcare experience developed in blue-chip organizations including McKinsey & Company Inc., The Advisory Board Company and Abbott Pharmaceuticals, Mr. Cheema most recently served as a knowledge expert at Objective Health, a McKinsey solution for healthcare providers, advising health systems and hospitals on operational and strategic issues. Mr. Cheema earned his MBA from INSEAD, M.S. from the University of Colorado and bachelor’s degree in engineering from Bangalore University.

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