Key result
Artificial intelligence platforms have the potential to serve as clinical decision-making tools in spine care to improve physician performance and promote appropriate, efficient care.
Why the study?
Exponential expansion of computing capacity has converged with unsustainable healthcare spending, creating an opportunity to explore artificial intelligence to enhance healthcare quality and safety.
Artificial intelligence has the potential to serve as a clinical decision-making tool to improve healthcare quality, safety, and physician performance, particularly in spine care.
AI tools require prospective validation before spine care integration; leaves open targeted trials on decision quality and safety.
As exponential expansion of computing capacity converges with unsustainable health care spending, a hopeful opportunity has emerged: the use of artificial intelligence to enhance health care quality and safety. These computer-based algorithms can perform the intricate and extremely complex mathematical operations of classification or regression on immense amounts of data to detect intricate and potentially previously unknown patterns in that data, with the end result of creating predictive models that can be utilized in clinical practice. Such models are designed to distinguish relevant from irrelevant data regarding a particular patient; choose appropriate perioperative care, intervention or surgery; predict cost of care and reimbursement; and predict future outcomes on a variety of anchored measures. If and when one is brought to fruition, an artificial intelligence platform could serve as the first legitimate clinical decision-making tool in spine care, delivering on the value equation while serving as a source for improving physician performance and promoting appropriate, efficient care in this era of financial uncertainty in health care.
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Lee et al. (2020) conducted a review in Health care quality and safety in spine care. Artificial intelligence was evaluated. Artificial intelligence platforms have the potential to serve as clinical decision-making tools in spine care to improve physician performance and promote appropriate, efficient care.
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