AI technologies could make a significant impact on the future of spine care, according to a new analysis published in Global Spine Journal. An effective AI platform, the authors explained, could be the “first legitimate clinical decision-making tool” in the specialty’s history.
“With advances in computer processing capability, data storage and networking, these computer-based algorithms can perform the intricate and extremely complex mathematical operations of classification or regression (specifically nonlinear regression) on immense amounts of data to detect intricate and potentially previously unknown patterns in that data,” wrote lead author Michelle S. Lee, BA, from the Cleveland Clinic, and colleagues. “Machine learning algorithms have been able to analyze complex and large volumes of electronic medical record data to produce predictions for a wide range of clinical problems.”
Lee et al. explored the rise of AI and machine learning, noting that researchers have successfully been able to predict mortality, unexpected readmissions and other important data. Spine surgery, they added, “has recently seen an outpouring of publications related to research in this area.”
This increase in AI-related discussion comes at a crucial time for the specialty. Much like the medical imaging field, spine care is often associated with rising costs—and has ended up being caught in the crosshairs of critics as a result.
“As spinal surgery has evolved with an explosion of new techniques and technologies in recent decades, there still remains a lack of quality, high-level evidence to support much of the spine care rendered in the U.S., especially with the cost associated with many of the treatments and devices,” the authors wrote. “As there are numerous surgical treatments in spine surgery that do not easily lend themselves to traditional randomized controlled trials (due to either cost or ethical considerations, among other reasons), an opportunity arises that is ripe for solutions derived from machine learning approaches.”
Researchers are working to seize that opportunity, with numerous clinical registries currently in the works. And the gathering of more clinical data is certain to lead to more effective algorithms in spine care.
Lee and colleagues wrote that AI and machine learning should help providers from throughout the specialty predict patient outcomes—both positive and negative—and improve the evaluation of spine-related imaging findings. These algorithms can also play a huge role in cutting costs, which is sure to make C-suite executives at health systems especially happy.
“An AI platform that successfully predicts patient and surgeon performance from financial, outcome, and electronic medical record databases across an entire book of business stands to provide the leverage to homogenize outcome and cost,” the authors concluded. “This, in turn, positions said organization optimally for contract negotiations and population health initiatives.”