Modeling opioid use disorder in hand surgery patients

From 1999 to 2022, nearly 300,000 people died from overdoses involving prescription opioids. Commonly used for the management of acute post-surgical pain, prescription opioids remain a leading cause of opioid misuse and abuse. Among surgical populations, patients who undergo hand surgery have especially high rates of prolonged post-operative opioid use and opioid use disorder (OUD). We built a compartmental model describing the progression from opioid exposure to OUD in hand surgery patients and parameterized it using empirical patient data. Using this model, we investigated the functional relationship between the number of opioid prescriptions received and opioid abuse. We found that, depending on the response curve used to describe opioid addiction risk, different numbers of prescriptions pose higher risks than others, advancing our understanding of how prescription patterns influence OUD development.

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Publication Details

Journal
Mathematical Medicine and Biology A Journal of the IMA
Published
2026-01-14
DOI
https://doi.org/10.1093/imammb/dqag001
Primary Topic
Opioid Use Disorder Treatment
Type
article
Field-Weighted Citation Impact
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article

Modeling opioid use disorder in hand surgery patients

Julie C. Blackwood, Eli E. Goldwyn, Kathryn J. Montovan, Grace Bowman
Mathematical Medicine and Biology A Journal of the IMA
Opioid Use Disorder Treatment
article

Modeling opioid use disorder in hand surgery patients

Julie C. Blackwood, Eli E. Goldwyn, Kathryn J. Montovan, Grace Bowman
article en

Abstract

From 1999 to 2022, nearly 300,000 people died from overdoses involving prescription opioids. Commonly used for the management of acute post-surgical pain, prescription opioids remain a leading cause of opioid misuse and abuse. Among surgical populations, patients who undergo hand surgery have especially high rates of prolonged post-operative opioid use and opioid use disorder (OUD). We built a compartmental model describing the progression from opioid exposure to OUD in hand surgery patients and parameterized it using empirical patient data. Using this model, we investigated the functional relationship between the number of opioid prescriptions received and opioid abuse. We found that, depending on the response curve used to describe opioid addiction risk, different numbers of prescriptions pose higher risks than others, advancing our understanding of how prescription patterns influence OUD development.

Mathematical Medicine and Biology A Journal of the IMAVol. 43(1)
University of Colorado Boulder (US), Williams College (US), University of Portland (US), Bennington College (US)
Good health and well-being
Openalex Percentile: Top 84%
Opioid Use Disorder Treatment
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