How AI is Becoming a Staple in Medical Coding, Auditing

Tech reduces manual work

“We've got a lot of clinical data in healthcare, but it's difficult to make sense of it,” Sahar says. “It's difficult to make sure that the data is accurately reflecting what's happening with the patient.”

Still, breaking down clinical documentation into codes — the language of medical professionals — is critical. One misstep and there can be serious consequences, whether that’s missing a diagnosis, submitting false information on a claim, or contributing to data quality issues for analytics. These mistakes can be a headache for revenue cycle teams looking to submit clean claims and reduce denials, but also for patients who expect a seamless experience from the clinician’s exam room to the back office.

“It's a critical process that sees all this clinical data flowing through it, but that relies on experts, so medical coders and CDI specialists, to review this data as fast as they can and as accurately as they can,” Sahar explains. “Technology can improve these manual reviews, both in terms of productivity and in terms of identifying error opportunities or audit opportunities.”

Providers are seeing the benefits of applying technology to medical coding even though the process requires expertise.

“There's a healthy interest in looking for efficiencies that technology brings,” Jimenez states. “The goal of coding is to make it more enabled by technology and less manual.”

“For example, looking up a medical record and then populating codes into a different system,” Jimenez continues. “Those types of operational efficiencies where if you have a more streamlined workflow tool that limits the clicks and the redundancy of populating information from one system to another, you can consider that manual.”

That is where technology can really impact medical coding and billing: workflow. Workflow software that leverages machine learning and AI can elevate coding quality by reducing manual tasks, making it easier for professionals to verify accurate coding and tackle more complex cases.

Workflow software should consider all the tools a coder or auditor needs to review clinical charts, coding data, and AI suggestions. This is likely technology’s happy home in medical coding versus complete process automation.

“I don't think we're at automation with coding and auditing within the context of AI, and I don't think it will ever be automated fully,” Sahar adds. “The reason that's the case is a lot of these processes are more half science-half art, so you really need experts in the loop with AI systems to be able to review complicated cases.”

Synergy between tech and coders

AI can eliminate the repetitive tasks that are easier to accomplish, bringing more efficiency to coders and auditors, according to Jimenez. AI-enabled technology can summarize large data sets stemming from hundreds of pages of medical records, which a human would have to parse to code an encounter accurately.

“The tool can help summarize and give you a snapshot of what happened through the entirety of that admission by quickly capturing the diagnosis and identifying where in the documentation it came from,” Jimenez elaborates. “Staff can then quickly go to those areas without reading hundreds of documents. That is a game changer with time and efficiency. That is going to enable your humans to make better decisions quicker.”

That is the key to implementing AI in medical coding and billing; technology must complement the professional’s workload and workflow. Coders and technology need to develop a synergy.

“And that process then teaches the AI what to do and what not to do,” Sahar explains, emphasizing how AI and professionals need to work together in order to maximize benefits and ROI. “So over time, this creates a positive feedback loop that frees up the coder to be able to take on more complex work.”

AI cannot work in a black box in order to successfully aid medical billing and coding, Jimenez stresses. Coders and auditors need to be able to verify that output from the AI solution reflects the patient encounter fully and accurately.

This approach to technology implementation — technology supports human work versus eliminating it — aligns with healthcare, which relies on people. Technology needs to make care delivery and administration more efficient, whereas other industries can automate more of their tasks completely to achieve efficiency.

The future of AI in medical coding, auditing

 There’s a significant desire and need for tech-enabled coding processes, which underlined AAPC’s recent acquisition of Semantic Health.

“By putting this tool in the hands of our members, it's going to make them more efficient,” Jimenez says. “It's also going to help them understand how their roles will evolve, which is also very important to us.”

Healthcare organizations simply cannot keep up with the sheer volume of claims lately as more patients touch the healthcare system after a years-long pandemic and recent coverage changes that reduced the uninsured rate in the US. An aging population also means that providers are going to see more claims since older populations tend to use more healthcare.

“That’s hard to keep up with,” Jimenez explains. “So, if there are tools that can help staff gain efficiency and take the more simplistic encounters to code and automate those, people can focus on the harder cases, which, in most cases, generate the most revenue. AI helps them do more work with the staff they already have versus having to hire more individuals.”

Not only are staff expensive to hire, but also hard to find. A 2023 Medical Group Management Association (MGMA) poll found that 34 percent of medical groups find medical coders the most difficult revenue cycle role to hire. Coders also require specialized education and training compared to other revenue cycle roles — another aspect AI-enabled coding and auditing technology can help.

“Training people on how to use this technology to be more efficient means you'll be able to get more production out of each coder,” Jimenez states. “It might also help with their proficiency because they've got a tool. It's not them making the decisions on their own as one person. They've got a tool to give them confidence that they're making the right code selections.”

Technology is also a tool providers can use to reduce burnout. However, organizations need to ensure they are digitally mature — meaning they aren’t on pen and paper — and have change management in place to leverage AI-enabled coding and auditing technology, Sahar underscores.

“People are going to be using AI, so they need to be comfortable with it, they need to trust, they need to know what it can and cannot do,” Sahar explains. “On the change management side, AAPC can provide the education, thought leadership, and training to the next generation of codes and continuing coders and auditors.”