Application of machine learning to identify risk factors for outpatient opioid prescriptions following spine surgery

HIGHLIGHTS

  • What: The aim of this study was to employ six ML algorithms to identify clinical variables predictive of increased opioid utilization across spinal surgeries, including anterior cervical discectomy and fusion (ACDF), posterior thoracolumbar fusion (PTLF), and lumbar laminectomy. While this approach has proven beneficial from both a clinical and financial perspective, this study illustrates that, in some scenarios, it may come at the cost of increasing outpatient opioid requirements.
  • Who: Alexander Bouterse and colleagues from the School of Medicine, Loma Linda University, Loma Linda, CA, USA have published the Article: Application of Machine Learning to . . .

     

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