Home Health & Hospice Week

Diagnosis Coding:

Consider AI When It Comes To Auditing Coding, Documentation

Find out where the technology can improve your workflows.

When you think of artificial intelligence, coding audits may not be the first thing that follows. But AI can help direct your attention — and resources — where they need to be.

Deploying AI to dig through documentation during the auditing process can be a substantial timesaver. The technology assists you by reviewing records and can automatically flag possible coding errors or gaps in the documentation.

“This is going to allow us to streamline that process and allocate our human resources more effectively,” said coding expert Jacob Swartzwelder, managing director of Compliant Approach Partners, during his session, “Enhancing Compliance with AI-Powered Audit Tools and Techniques,” at AAPC’s AUDITCON 2023.

He explains that the computer can quickly scan a large amount of documentation. “[The technology] can go through multi-targeted focus areas very quickly. We can set it up to check 20 things on all 100,000 records, and it can do that and prioritize which records would be most beneficial to receive a human review,” Swartzwelder added.

Due to the human element of healthcare and medical coding, medical conditions may be under-documented in the patient record or claim. Under-documented conditions contribute to inaccurate coding and even loss of revenue for the organization. In the auditing process, you can use AI to hunt through medical documentation to locate these conditions.

“We can use that AI to analyze clinical documentation to identify if there are keywords or concepts that might be missing, or that should be included to get the most accurate patient profile, and we can identify those under-documented conditions,” Swartzwelder said.

Better Coding Leads To Better Outcomes

Clinicians can then use the AI’s analysis to improve their documentation quality, which will help coders more precisely code. And providers can have an accurate picture of the patient’s health to help improve the patient’s outcome.

“We all know that coding accuracy is essential for reimbursement for one, reimbursement, security, and risk for two,” Swartzwelder said. “We want to make sure that we’re not having money taken back, and that we can build stable financial forecasts. Coding accuracy is very important for accurate patient profiles and reporting to your payer system.”

When you use AI to assist in your auditing process, the technology can automatically flag certain records for potential errors, such as incorrect codes and incomplete documentation. Then, you’ll know to prioritize those records to communicate with your providers, either via a query or an educational session.

Clinicians can receive helpful advice for improving their documentation as they perform the task. AI technology can deliver automatic alerts for areas where refinements may be needed.

But keep practical considerations top of mind. “If you’re in the space of looking at vendors for this or if you’re in the development side of these things, please pay attention to what that provider is going to be interfacing with,” Swartzwelder said. He continued, “Some providers today are working on even small laptop screens, and we do need to pay attention to what that is going to look like in terms of not taking away from patient care, and not taking away from some of the positives that already exist there.”

Streamlining your audit workflow is a huge step toward optimizing your resources and improving the process for coders and clinicians alike. Adding AI to your process can also enhance your auditing by automatically reviewing large volumes of records; flagging sections for additional review; and delivering helpful feedback to clinicians.

Bottom line: Using AI can lead to greater coding accuracy, optimized reimbursement, reduced risk, and improved patient outcomes, proponents maintain.

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