Considering RPA in Healthcare? Read this first. 

RPA, or robotic process automation, is the solution to some of healthcare’s biggest problems and is used across industries to streamline business processes and reduce time spent on repetitive, routine tasks. RPA completes these tasks faster and without errors, freeing up human time better spent on higher-level work. And because healthcare is filled with these repetitive, low-value administrative tasks – and has a pressing need for change – it’s a perfect candidate for widespread RPA. 

In healthcare today, waste and inefficiency permeate every level of the system, trickling down into patient care priorities and initiatives. Healthcare workers are reporting unparalleled burnout and health system cost pressures are mounting. As the amount of paperwork and number of programs used becomes more unmanageable, leaders are looking for a way to transform operations, and many are turning to RPA. 

How does RPA work? 

First, it’s helpful to understand how robotic process automation works. RPA is a basic form of automation, in which repetitive rule-based tasks can be programmed and completed by a bot. They mimic human interaction with programs and platforms, but can work 24/7 to increase capacity and do so without making unprogrammed errors. They can copy-paste information, extract data from programs, make calculations and more. 

These are just a few of the reasons RPA solutions have exploded in recent years. And as the amount of work completed digitally has increased, so has the number of routine digital tasks, and therefore opportunities for automation have grown exponentially. RPA can help companies save significant money by reducing errors and time spent on tedious, repetitive work. And in healthcare, RPA has promised to revolutionize everything from implementing healthcare plans to hospital claims management. Sounds great, right?

Unfortunately, RPA alone isn’t enough to transform how healthcare functions. 

Healthcare has been buzzing about RPA for years now, but when it comes to delivering value and scalability, the truth is that RPA has failed to deliver on all of its promises. Why? Healthcare is a massive industry with complex, varied needs, which RPA is simply too technically limited to adequately address. 

The first problem is the limited capabilities of RPA when used alone. RPA can only automate completely rule-based processes – and there are fewer of these than you think. Every exception and every possible workflow needs to be explicitly programmed, otherwise the bot cannot work. Humans can often understand and navigate these nuances without even thinking about it, but a bot doesn’t work like that. Here’s what happens: Organizations spend a lot of time building and implementing RPA for a process, only to realize there are too many minor variations to account for. The number of exceptions is so great that it doesn’t save much time, and the entire process feels like a waste.

The second problem is with the RPA platform infrastructure (hint: There often isn’t one). An RPA bot is easy to set up, which at first seems like a great benefit. But that means they are often implemented as siloed, stand-alone solutions. Each one is built from the ground up, perhaps even by different teams, without a strong internal governance policy in place. Then, these bots “break” whenever a program they interact with changes, even something as minor as a small UI update, requiring coding fixes. As the number of bots grows, so does the work required simply to maintain performance. It can quickly become a drain to manage and monitor all the random bots operating throughout an organization. 

It’s clear that RPA alone – especially solutions not designed for healthcare’s dynamic environment – may not be the answer that healthcare needs, but automation and all the benefits it brings are still possible. 

The answer is artificial intelligence, and intelligent automation. 

To drive the waste and inefficiencies out of healthcare, we need to think bigger than standalone bots. We need to think about automation supported by artificial intelligence. 

RPA needs to be combined with other AI technologies, like machine learning (ML), computer vision (CV), natural language processing (NLP), and deep learning. When partnered with these more advanced AI capabilities, the RPA use cases and associated value explode, turning into intelligent automation that can tackle much more complex workflows. When you combine RPA and AI, healthcare can transform operations, streamlining entire processes to reduce manual human work. For example, providers can automate their invoice processing and revenue cycle management. For payers, formulary management and billing can be handled by intelligent RPA. And AI has even been able to automate the entire prior authorization process, from payer to provider. 

Besides expanding the use cases for automation, another benefit of partnering AI with RPA is the potential for a connected AI network, or Internet of Healthcare. Instead of siloed bots, AI can connect all the healthcare bots on a network. All the data can be ingested and analyzed together, accelerating the timeline to insights and opportunities to improve. The network can learn as one, so organizations can reap the benefits or shared knowledge and best practices, and won’t have to reinvent the wheel for every new process. 

Finally, healthcare needs to look beyond single use cases and consider a total AI and automation strategy that encompasses RPA as well as these other technologies. A comprehensive strategy will align internal priorities, unify implementations and create the internal governance structure needed to successfully maintain and grow the impact of automation in the organization. 

What is the future for RPA in healthcare?

RPA holds great promise for healthcare – and it can deliver on those promises when powered by artificial intelligence. It’ll enable a better future in which humans are back to doing human work and bots are doing robotic work. Only then can we unlock the untapped potential in our workers and our healthcare system as a whole. Learn more about AI and automation for healthcare.  



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