Can hospitals and healthcare networks generate more efficiency and savings through medical billing and coding?

In a transformative move for healthcare, Dr. Matthew Hitchcock and over 1,000 physicians at the University of Pittsburgh are harnessing the power of AI to streamline patient documentation, cutting down hours of clerical work to mere minutes. Companies like Abridge are at the forefront, offering solutions that ease doctors’ workloads and enhance patient engagement by providing accessible visit summaries. However, while the potential of AI in medical diagnosis is vast, professionals like Dr. Hitchcock remain cautious, prioritizing patient safety and regulatory compliance.

If AI can assist in streamlining patient documentation, what about medical coding? Can medical billing coders utilize these tools to enhance the process and create efficiencies across the whole operation.

Matthew Isaacson, a 15-year veteran of revenue cycle management, says there are positives to exploring AI in medical billing and coding. To do it right, certified coders should drive the train.

Matthew’s Thoughts

“What is definitely being used is clinicians and revenue cycle staff work together to translate clinical encounters into billable codes for reimbursement. AI is integrated there because it drives efficiency and cost-effectiveness for these organizations. With the great resignation affecting the healthcare industry as much as any other, AI has played a crucial role in filling some of those gaps. However, it’s a double-edged sword. There are definite pros to AI’s involvement, but there are cons as well.”

The Evolution of Technology in Healthcare

“Technology is evolving in healthcare more than ever. AI should play a role because it’s driving efficiency and cost-effectiveness. But AI is being used in partnership with IT technology, and data integrity is key. If you’re going to utilize AI in healthcare, you need to ensure that your coders are incorporating appropriate codes. If that’s not happening, then AI isn’t going to be effective. It’s proven. There are growing pains. If someone is going to implement AI within their coding structure, they need to ensure that from the beginning, their coders are using the appropriate codes. Using any AI engine, a predictive model is created. It’s the garbage in, garbage out mentality. They need to ensure that the infrastructure is in place from the beginning to make sure that the AI modeling is as accurate as possible. AI has many benefits within healthcare, but it’s not the silver bullet. There must be infrastructure and a strategy in place for its deployment.”

The Importance of Certified Healthcare Billing Coders

“Using certified coders is an absolute must. It comes down to ensuring that the medical coder is certified and trained and that quality control is in place to ensure they’re using appropriate codes. If they’re not doing that, there will be garbage in and garbage out. Additionally, by not using proper coding it’s driving denials and barriers to reimbursement. It’s essential that these coders implement the appropriate codes so that the AI model can take flight.”

Article by James Kent