AI may lead to better outcomes after joint surgery — 4 findings


New York City-based Hospital for Special Surgery researchers found that artificial intelligence may help orthopedic surgeons predict how patients will react after joint replacement surgery.

In the June 2019 issue of Clinical Orthopaedics and Related Research, they reported: "Machine learning has the potential to improve clinical decision-making and patient care by helping prioritize resources for postsurgical monitoring and informing presurgical discussions of likely outcomes" after total joint replacement.

Four insights:

1. The study indicates that machine-learning algorithms can predict with reasonable accuracy which patients will report a minimal clinically important difference in symptoms two years after total knee or total hip replacement surgery.

2. Senior Director of Data Science at HSS and lead author of the study Mark Fontana, PhD, said that understanding patient-reported outcomes is vital as "pain and function are subjective," so asking patients "how they're doing is necessary."

3. The researchers examined the physical and mental status of patients from data collected at HSS —7,239 hip and 6,480 knee replacement cases — from 2007 through 2012.

4. The researchers were able to determine whether a patient achieved an MCID across four patient reported outcome measure scores: one for each of general physical health, general mental health, hip health and knee health. They are now creating print and digital decision aids for surgeons to predict the likelihood of a patient achieving MCID depending on their individual characteristics.

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