Solve the Top Five Challenges of Revenue Cycle Management with Agentic Automation

How can healthcare providers improve patient satisfaction, drive down costs, and accelerate reimbursement? The answer is to supercharge revenue cycle management (RCM) with AI.

Earlier waves of automation removed up to 40% of manual tasks. Yet, administrative complexity in the US healthcare system still wastes an estimated $265.6 billion per year.

Now, you can combine automation with the latest AI tools, such as generative AI, in an approach called agentic process automation (APA). APA leverages semi-autonomous decision-making to automate more complex processes, spanning multiple IT systems and data silos.

Here’s how APA solves five of your top RCM challenges: accuracy, speed, workforce shortages, the cost of appeals, and the complexity of payer policies.

Improve the accuracy of claims, appeals, and prior authorization

Because of the vast number of claims that need processing and the way information is spread across multiple systems, staff work under immense pressure. Mistakes are inevitable.

By automating data collection, you can ensure that claims are supported with complete and accurate information. This improves your clean claims rate (the percentage of claims that are accepted on first submission without any requests for more information).

Of course, once you’ve established the ability to use APA, you can streamline a whole host of other RCM processes with it. Prior authorization, for example, can be carried out by intelligent agents dedicated to payer communications and medical necessity verification. Using automation for prior authorization cuts errors significantly.

By automating and processing those claims that require prior authorization (PA) proactively, APA improves your clean claim rate. By flagging those claims that require not only PA but also medical necessity verification, APA helps to streamline the entire RCM process.

Accelerate claims and appeals

The quicker providers can file a claim, appeal, or prior authorization request, the sooner they can get paid. Money tied up in accounts receivable can’t be spent on looking after patients.

RCM processes routinely require extensive manual work across disparate data sources and computer systems. The strength of APA is that it orchestrates multiple intelligent agents to implement an entire workflow faster, often with concurrent processing. People are still involved where required, but they focus on higher-level activities such as decision-making.

Confront workforce shortages

Alongside the well-known shortage of medical skills, there is a shortage of RCM professionals. Coders are the most difficult role to hire, followed by billers (compliance and audit professionals), according to a membership survey by The Medical Group Management Association.

APA helps in two ways. First, it makes your team much more efficient so that they can process more claims and appeals. A human expert can write approximately six appeal letters a day, for example, whereas a worker using AI can create them in minutes.

Second, you can encapsulate some of your team’s expertise in an AI agent, which can help inexperienced new team members perform at higher levels.

That means your experienced staff can focus on exceptions and queries that warrant human attention rather than routine work that can be automated or delegated with AI support.

Appeal everything

With manual processes, there’s an amount below which it’s not worth making an appeal. The work processing it costs you more than you’d get back. The threshold might only be about $125, but all those relatively small sums add up fast.

Using APA, you can appeal every denial because the workflow is almost entirely automatic. You can keep a human in the loop for oversight, review, and approval. However, they can work extremely efficiently because they’re presented with all the information, including appeal letters, ready to go.

Understand the payer’s policies

Claims that do not comply with the payer’s policies are denied. That either means the reimbursement is jeopardized, or the provider has to spend more admin time on filing an appeal.

Unfortunately, it’s hard to keep pace with all the policies from all the providers because they change periodically. Luckily, AI can digest massive amounts of information and surface what’s important. Integrate it with your existing healthcare software and you can automatically intervene if a treatment is about to be booked or claimed that won’t be reimbursed. Your system might recognize, for example, that a claim code needs to be more specific for the payer to honor it. As a result, you can get it right the first time and drive up your clean claims rate.

Make RCM Soar with APA

As a result of using siloed IT systems and distributed data sources, RCM suffers from challenges in accuracy, speed, and cost. At the same time, it’s hard for providers to find expert staff and keep pace with changes in payer policies.

By using APA to orchestrate across bots and intelligent agents, you can automate up to 80% of manual tasks in RCM.

Learn more about automation use cases in healthcare.