“Risk Management: Artificial Intelligence in Clinical Practice,” Innovations in Clinical Neuroscience Journal Article by PRMS

“Risk Management: Artificial Intelligence in Clinical Practice,” Innovations in Clinical Neuroscience Journal Article by PRMS

Our PRMS Risk Managers frequently share their expertise by contributing articles to clinical journals, including the Innovations in Clinical Neuroscience (ICNS) digital journal, throughout the year. Read an excerpt by PRMS Director of Risk Management, Donna Vanderpool, MBA, JD, from ICNS’ article, “Risk Management: Artificial Intelligence in Clinical Practice.”

Question

I’ve read a lot about artificial intelligence (AI) in healthcare, and I’m ready to incorporate it into my practice. What is the current risk management thinking on this topic?

Answer

AI basically means the use of computers to perform tasks that usually require human intelligence, and it is exploding into all aspects of our lives at a rapid pace. However, most AI uses are not yet ready to incorporate into a clinical practice. Those few that are ready have significant risks, and they must be used in conjunction with, not instead of, a clinician’s decision-making.

General problems with AI in healthcare include but are not limited to the following:

  • Gathering information: AI needs an incredibly large amount of patient information to train, but there are federal and state confidentiality protections on patient data.
  • Security issues in training data: There are security concerns with training data, such as training data poisoning (the intentional contamination of data to sabotage the AI).
  • Hallucinations: AI is well known to hallucinate (i.e., present false or misleading information as fact) about medications, which could be a significant patient safety issue. AI also cannot distinguish between accurate and false information.
  • Bias: Bias in training data, such as sexism and racism, will cause biased AI results. This is a significant issue since training data includes everything on the internet, and we know there are inequities in healthcare found in medical data.

Subscribe to the ICNS publication for free here to read the rest of Donna’s article with professional guidelines and takeaways to consider.


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