As more hospitals experience this growing phenomenon first-hand, look for their policies and procedures to evolve in response.

Providers bringing AI into healthcare
Artificial intelligence and machine learning tools have gained acceptance in many healthcare settings, but their full range of practical benefits and applications have yet to be realized. Based on industry sentiment so far, the positives seem to outweigh the negatives, based on some early examples of AI adoption.
Take coding. Without much heavy lifting, a medical coder can use an AI script to review 1,000 patient charts and flag any that meet certain criteria that pose high risk for coding errors. In hospitals where such coding errors have been costly, generative AI can be an especially useful time- and money-saving tool that reduces the burden on human coders. These tools are relatively inexpensive, making them available to hospitals of all sizes and operating budgets.

The potential for biased datasets to exacerbate disparities in medical outcomes through the use of AI is beginning to get the attention it deserves. AI tools also have the potential to reduce disparities. Anyone with an internet connection can access ChatGPT and input a question focused on their personal healthcare needs. Providers whose services are constrained by staffing shortages, or long driving distances for patients within a broad area, can educate patients on how to use an AI-based app to pre-screen their own symptoms at home.


About the author: Hilton M Hudson, MD, FACS, is a board-certified cardiothoracic surgeon and the Chief of Cardiothoracic Surgery at Franciscan’s Michigan City and Olympia Fields health systems. He is also the CEO of HPC International (HPC), the leading educational purchased services supplier for healthcare, corporations and academic institutions.

Back to HCB News

Business Affairs Homepage