Applying AI, Automation to the Healthcare Revenue Cycle

Applying AI, automation to the healthcare revenue cycle

Inefficiencies in the healthcare revenue cycle represent opportunities to apply Artificial intelligence and automation.

Artificial Intelligence (AI) and intelligent automation, in general, are changing the face of modern business, and this is as true in the world of healthcare as anywhere else. You may have at least a general understanding of how intelligent automation can benefit your healthcare business, but identifying the best use cases and defining a pragmatic action plan can be difficult.

Here are steps to assist healthcare professionals in identifying and implementing the best use cases for artificial intelligence within the revenue cycle processes of their organization.


The first step in getting started with automation is understanding the technologies available to you at a high level. There are two core types of intelligent automation available: AI and Robotic Process Automation (RPA).

AI learns and iterates as it goes by completing repetitive, high-volume, error-prone tasks while collecting intelligence on this work along the way. This approach allows the technology to ultimately identify and address larger, more complex, opportunities for automation. The goal of AI is to mimic human intelligence using computers, enabling them to solve complex problems quickly and to scale.

On the other hand, RPA simply takes a set of inputs and produces an output based on a predefined set of rules. RPA doesn’t “learn”— it reacts the same way every time. RPA can complete the same types of repetitive, high-volume, error-prone tasks while collecting simple metrics for reporting.

Regardless of the technology, the objective of intelligent automation in healthcare, or any other industry, is the same. Take repetitive, high-volume tasks that are done in a similar way every time and offload them to software, freeing up human capital to focus on more important tasks.

Human capital is often reduced to the number of hours human employees spend completing their work, but that view has to be expanded to truly see the impact intelligent automation can have on your organization. At the surface, using automation to replace repetitive tasks humans complete can save money — bots don’t require benefits or vacation time — and reduce errors because typos don’t exist in their world. But at a deeper level, automation can free up human employees to focus on more complex skills, like customer service, patient advocacy, and empathy.

There are several forms of intelligent automation that offer a multitude of capabilities, but humans possess infinite intelligent skills. When you’re able to apply your staff’s skills to the most important parts of your business rather than to the processes that automation can conduct, that is when you truly see the value intelligent automation can bring to your healthcare organization.


With an understanding of AI and RPA, you can start to see where their applications lie. Rule-based business processes (e.g., insurance verification, data recording) are prime candidates for RPA. More complex judgment-based processes (e.g., eligibility checks that require a review of electronic health records) can benefit from the application of AI.

Categorizing your revenue cycle processes can help set the tone as you continue to brainstorm precise processes to automate and what that implementation should look like. Keeping that constant throughout your brainstorming helps solidify your choices.


The next step is brainstorming, identifying specific processes in your business that can benefit. As you begin to approach specific use cases for intelligent automation within your healthcare organization, it is important to consider the impact automation can have and the speed with which these tasks can be completed with automation versus how they are done now.

There are several common places impact and speed can be targeted within the revenue cycle, and account updates are usually a great place to start. These kinds of updates are usually a massive undertaking and can touch many or all of your organization’s patient accounts, and are tedious tasks that have to be done correctly.

Impact is immediately recognizable as automation is much faster than humans, reduces errors to negligible numbers, and can prevent costly errors down the line, saving your organization money. In this kind of automation, speed and impact are intertwined.


To identify specific processes to offload to intelligent automation, you can use either a problem or solution-oriented approach.

The problem-oriented approach looks to identify bottlenecks and areas where employees spend the bulk of their time performing repetitive tasks. The solution-oriented approach looks to optimize workflows and makes sense when there are no clear bottlenecks. This approach identifies where key performance indicators (KPIs) can be positively impacted by implementing intelligent automation. Whichever approach you take at this stage, remember that every moving piece in a healthcare business has multiple high-volume administrative processes. Intelligent automation does not have to be limited to one department or team — everyone can reap the benefits directly by improving their daily work, or indirectly by experiencing the positive impacts of these improvements in other tangent workflows and cycles.


Once you have identified where AI should be applied, you have to consider how you’ll get it implemented. Building an automation solution requires a team of highly skilled developers, project managers, and automation engineers. The DIY approach can make sense, but for many, the upfront costs and lack of technical knowledge create barriers. Partnering with an AIaaS provider makes the benefits of intelligent automation more easily accessible to businesses of all sizes and allows you to focus on core business competencies, instead of development.

Want to get started?

To take the first steps toward automation at your organization, download this free guide. You’ll learn how to identify the right processes for automation, and start to build the case for AI and automation.

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