Analysis and development of risk prediction models for chronic opioid use after surgery: a cohort study using the nationwide database

Background: Chronic opioid use has become a socioeconomic as well as a medical problem. This study aimed to identify risk factors and develop prediction models for postoperative chronic opioid use (PCOU).Methods: This retrospective cohort study used data from the Korean National Health Insurance Ser...

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Published in:	Korean journal of anesthesiology Vol. 78; no. 5; pp. 429 - 442
Main Authors:	Kim, Jonghae, Yang, Hyun-Lim, Kim, Eugene, Lee, Hyung-Chul, Yoon, Hyun-Kyu, Kim, Yun Jin, Kim, Kyu-Nam, Kim, Ji-Yoon, Sung, Jeong Min, Lee, Tagkeun
Format:	Journal Article
Language:	English
Published:	Korea (South) Korean Society of Anesthesiologists 01.10.2025 대한마취통증의학회
Subjects:	Adolescent Adult Aged Analgesics, Opioid - administration & dosage Analgesics, Opioid - adverse effects Child Cohort Studies Databases, Factual - trends dependence, opioid Female gradient boosting algorithms Humans Machine Learning Male Middle Aged Opioid-Related Disorders - diagnosis Opioid-Related Disorders - epidemiology Opioid-Related Disorders - etiology Pain, Postoperative - diagnosis Pain, Postoperative - drug therapy Pain, Postoperative - epidemiology postoperative period prediction methods, machine Republic of Korea - epidemiology Retrospective Studies Risk Assessment - methods Risk Factors surgical procedures, operative Young Adult 마취과학 Republic of Korea Gradient boosting algorithms Dependence, opioid Prediction methods, machine Surgical procedures, operative Postoperative period Machine learning
ISSN:	2005-6419, 2005-7563, 2005-7563
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Abstract	Background: Chronic opioid use has become a socioeconomic as well as a medical problem. This study aimed to identify risk factors and develop prediction models for postoperative chronic opioid use (PCOU).Methods: This retrospective cohort study used data from the Korean National Health Insurance Service (NHIS) between January 2008 and December 2018. Of 2 077 825 patients aged seven years or older who underwent surgery, survived at least one year, and had no additional surgeries, 1 108 119 were randomly selected. Logistic regression (LR) and machine learning models were developed to identify risk factors for PCOU. PCOU was defined as having filled 10 or more prescriptions or receiving more than 120 days’ supply between postoperative days 91 and 365. Age, sex, medical comorbidities (systemic diseases, psychological disorders, and substance use disorders), preoperative medications (antidepressants, antipsychotics, anticonvulsants, benzodiazepines, opioids, and nonopioid analgesics), and type of surgery were assessed as potential risk factors.Results: PCOU occurred in 9308 patients (0.84%). Older age, preoperative history of opioid use, and high in-hospital opioid doses were the three most important predictors. Among the 28 most commonly performed surgical procedures in Korea, lung surgery, general spinal surgery, and total knee arthroplasty were most strongly associated with chronic opioid use.Conclusions: According to the best-performing gradient boosting model, older age, longer hospital stay, high in-hospital opioid consumption, and preoperative opioid use were the most important risk factors for PCOU.
AbstractList	Background: Chronic opioid use has become a socioeconomic as well as a medical problem. This study aimed to identify risk factors and develop prediction models for postoperative chronic opioid use (PCOU).Methods: This retrospective cohort study used data from the Korean National Health Insurance Service (NHIS) between January 2008 and December 2018. Of 2 077 825 patients aged seven years or older who underwent surgery, survived at least one year, and had no additional surgeries, 1 108 119 were randomly selected. Logistic regression (LR) and machine learning models were developed to identify risk factors for PCOU. PCOU was defined as having filled 10 or more prescriptions or receiving more than 120 days’ supply between postoperative days 91 and 365. Age, sex, medical comorbidities (systemic diseases, psychological disorders, and substance use disorders), preoperative medications (antidepressants, antipsychotics, anticonvulsants, benzodiazepines, opioids, and nonopioid analgesics), and type of surgery were assessed as potential risk factors.Results: PCOU occurred in 9308 patients (0.84%). Older age, preoperative history of opioid use, and high in-hospital opioid doses were the three most important predictors. Among the 28 most commonly performed surgical procedures in Korea, lung surgery, general spinal surgery, and total knee arthroplasty were most strongly associated with chronic opioid use.Conclusions: According to the best-performing gradient boosting model, older age, longer hospital stay, high in-hospital opioid consumption, and preoperative opioid use were the most important risk factors for PCOU. Chronic opioid use has become a socioeconomic as well as a medical problem. This study aimed to identify risk factors and develop prediction models for postoperative chronic opioid use (PCOU). This retrospective cohort study used data from the Korean National Health Insurance Service (NHIS) between January 2008 and December 2018. Of 2 077 825 patients aged seven years or older who underwent surgery, survived at least one year, and had no additional surgeries, 1 108 119 were randomly selected. Logistic regression (LR) and machine learning models were developed to identify risk factors for PCOU. PCOU was defined as having filled 10 or more prescriptions or receiving more than 120 days' supply between postoperative days 91 and 365. Age, sex, medical comorbidities (systemic diseases, psychological disorders, and substance use disorders), preoperative medications (antidepressants, antipsychotics, anticonvulsants, benzodiazepines, opioids, and nonopioid analgesics), and type of surgery were assessed as potential risk factors. PCOU occurred in 9308 patients (0.84%). Older age, preoperative history of opioid use, and high in-hospital opioid doses were the three most important predictors. Among the 28 most commonly performed surgical procedures in Korea, lung surgery, general spinal surgery, and total knee arthroplasty were most strongly associated with chronic opioid use. According to the best-performing gradient boosting model, older age, longer hospital stay, high in-hospital opioid consumption, and preoperative opioid use were the most important risk factors for PCOU. Chronic opioid use has become a socioeconomic as well as a medical problem. This study aimed to identify risk factors and develop prediction models for postoperative chronic opioid use (PCOU).BackgroundChronic opioid use has become a socioeconomic as well as a medical problem. This study aimed to identify risk factors and develop prediction models for postoperative chronic opioid use (PCOU).This retrospective cohort study used data from the Korean National Health Insurance Service (NHIS) between January 2008 and December 2018. Of 2 077 825 patients aged seven years or older who underwent surgery, survived at least one year, and had no additional surgeries, 1 108 119 were randomly selected. Logistic regression (LR) and machine learning models were developed to identify risk factors for PCOU. PCOU was defined as having filled 10 or more prescriptions or receiving more than 120 days' supply between postoperative days 91 and 365. Age, sex, medical comorbidities (systemic diseases, psychological disorders, and substance use disorders), preoperative medications (antidepressants, antipsychotics, anticonvulsants, benzodiazepines, opioids, and nonopioid analgesics), and type of surgery were assessed as potential risk factors.MethodsThis retrospective cohort study used data from the Korean National Health Insurance Service (NHIS) between January 2008 and December 2018. Of 2 077 825 patients aged seven years or older who underwent surgery, survived at least one year, and had no additional surgeries, 1 108 119 were randomly selected. Logistic regression (LR) and machine learning models were developed to identify risk factors for PCOU. PCOU was defined as having filled 10 or more prescriptions or receiving more than 120 days' supply between postoperative days 91 and 365. Age, sex, medical comorbidities (systemic diseases, psychological disorders, and substance use disorders), preoperative medications (antidepressants, antipsychotics, anticonvulsants, benzodiazepines, opioids, and nonopioid analgesics), and type of surgery were assessed as potential risk factors.PCOU occurred in 9 308 patients (0.84%). Older age, preoperative history of opioid use, and high in-hospital opioid doses were the three most important predictors. Among the 28 most commonly performed surgical procedures in Korea, lung surgery, general spinal surgery, and total knee arthroplasty were most strongly associated with chronic opioid use.ResultsPCOU occurred in 9 308 patients (0.84%). Older age, preoperative history of opioid use, and high in-hospital opioid doses were the three most important predictors. Among the 28 most commonly performed surgical procedures in Korea, lung surgery, general spinal surgery, and total knee arthroplasty were most strongly associated with chronic opioid use.According to the best-performing gradient boosting model, older age, longer hospital stay, high in-hospital opioid consumption, and preoperative opioid use were the most important risk factors for PCOU.ConclusionsAccording to the best-performing gradient boosting model, older age, longer hospital stay, high in-hospital opioid consumption, and preoperative opioid use were the most important risk factors for PCOU. Background: Chronic opioid use has become a socioeconomic as well as a medical problem. This study aimed to identify risk factors and develop prediction models for postoperative chronic opioid use (PCOU).Methods: This retrospective cohort study used data from the Korean National Health Insurance Service (NHIS) between January 2008 and December 2018. Of 2 077 825 patients aged seven years or older who underwent surgery, survived at least one year, and had no additional surgeries, 1 108 119 were randomly selected. Logistic regression (LR) and machine learning models were developed to identify risk factors for PCOU. PCOU was defined as having filled 10 or more prescriptions or receiving more than 120 days’ supply between postoperative days 91 and 365. Age, sex, medical comorbidities (systemic diseases, psychological disorders, and substance use disorders), preoperative medications (antidepressants, antipsychotics, anticonvulsants, benzodiazepines, opioids, and nonopioid analgesics), and type of surgery were assessed as potential risk factors.Results: PCOU occurred in 9308 patients (0.84%). Older age, preoperative history of opioid use, and high in-hospital opioid doses were the three most important predictors. Among the 28 most commonly performed surgical procedures in Korea, lung surgery, general spinal surgery, and total knee arthroplasty were most strongly associated with chronic opioid use.Conclusions: According to the best-performing gradient boosting model, older age, longer hospital stay, high in-hospital opioid consumption, and preoperative opioid use were the most important risk factors for PCOU. KCI Citation Count: 0
Author	Lee, Hyung-Chul Kim, Ji-Yoon Lee, Tagkeun Kim, Eugene Sung, Jeong Min Kim, Jonghae Yoon, Hyun-Kyu Kim, Yun Jin Yang, Hyun-Lim Kim, Kyu-Nam
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Snippet	Background: Chronic opioid use has become a socioeconomic as well as a medical problem. This study aimed to identify risk factors and develop prediction models... Chronic opioid use has become a socioeconomic as well as a medical problem. This study aimed to identify risk factors and develop prediction models for... Background Chronic opioid use has become a socioeconomic as well as a medical problem. This study aimed to identify risk factors and develop prediction models...
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SubjectTerms	Adolescent Adult Aged Analgesics, Opioid - administration & dosage Analgesics, Opioid - adverse effects Child Cohort Studies Databases, Factual - trends dependence, opioid Female gradient boosting algorithms Humans Machine Learning Male Middle Aged Opioid-Related Disorders - diagnosis Opioid-Related Disorders - epidemiology Opioid-Related Disorders - etiology Pain, Postoperative - diagnosis Pain, Postoperative - drug therapy Pain, Postoperative - epidemiology postoperative period prediction methods, machine Republic of Korea - epidemiology Retrospective Studies Risk Assessment - methods Risk Factors surgical procedures, operative Young Adult 마취과학
Title	Analysis and development of risk prediction models for chronic opioid use after surgery: a cohort study using the nationwide database
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