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Abstract Opioids are frequently overprescribed after surgery. We applied a tabular foundation model to predict the risk of post-discharge opioid consumption.
Introduction The opioid epidemic is a major public health crisis. The age-standardised prevalence of opioid dependence has been estimated to be 510 per 100,000, with the highest prevalence in the USA, Middle East and East Asia [1]. This translated to approximately 109,500 opioid overdose deaths worldwide in 2017 [1].
Postoperative pain is common, complex, and often severe, affecting up to 80% of patients1. It is frequently managed using opioid analgesia, which, although potent, incurs the risk of significant adverse events. There are ongoing concerns regarding the inappropriate, excessive, and unsafe prescription of opioid analgesia after surgery2,3. Such practices are associated with worse patient outcomes, greater healthcare demands, and the ‘opioid epidemic’4,5.
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