Model performance for professional billing code levels of 4 and 5 were AUC-ROC 0.94 and 0.95, accuracy 0.80 and 0.92, and F1-score 0.79 and 0.91, respectively. At a 95 percent decision boundary threshold, Level 5 predicted charts had a positive predictive value of 0.99 and sensitivity of 0.57.

The research team says those numbers tell a story every physician can get behind; AI can save time and money. According to research published in the Journal of the American Medical Association in 2021, administrative expenses are a major proportion and growing source of health care costs in the United States, estimating that they contribute 15-20 percent of total national health care expenditures. In the emergency department, it is estimated that the total cost of these activities (e.g. registration and reregistration, physician time, billing, and overhead) is $61.54 per encounter, including professional billing costs of $38.88 (25.2% of professional revenue) for discharged patients, and 32 minutes of total processing time.

“From the finance perspective, it’s no different than anything else—we want to prove the concept,” Dr. Winters said. “And as we’re thinking about, how do we implement it? There are a lot of other things to consider. We want to make sure that we’re compliant with the regulations that we’re able to adapt. We can’t be assigning improper codes because that would have a big effect on the patients and their finances and organizational finances. Like any other organization thinking about AI, we have identified a space where AI can be helpful. Now, what needs to be built around that to make sure that it is valid and that it’s something we can rely upon.”

Recent advances in AI for medical billing are only possible now because of what Edward R. Gaines III, JD, CCP, calls a generational change in coding standards in 2023. It opened the gates to machine learning, said Mr. Gaines, the Vice President of Regulatory Affairs and Industry Liaison at Zotec Partners, LLC. He has been a member of ACEP’s Reimbursement Committee since 2015 and is a longtime faculty member at ACEP’s Reimbursement and Coding Conference as well as an honorary ACEP member.

Mr. Gaines said the new standards took away a lot of the subjectivity, the old way of coding. Zotec responded by hiring engineers from Google to develop its machine learning system, which they currently use for hospital clients and physician groups of all sizes.