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Home Research Research Library A Comparative Effectiveness Study on Opioid Use Disorder Prediction Using Artificial Intelligence and Existing Risk Models A Comparative Effectiveness Study on Opioid Use Disorder Prediction Using Artificial Intelligence and Existing Risk Models 2023 Author(s) Fouladvand, Sajjad, Talbert, Jeffery, Dwoskin, Linda P, Bush, Heather, Meadows, Amy L, Peterson, Lars E, Mishra, Yash R, Roggenkamp, Steven K, Wang, Fei, Kavuluru, Ramakanth, and Chen, Jin Topic(s) Role of Primary Care, and Achieving Health System Goals Keyword(s) Practice Innovations Volume IEEE Journal of Biomedical and Health Informatics Source IEEE Journal of Biomedical and Health Informatics Opioid use disorder (OUD) is a leading cause of death in the United States placing a tremendous burden on patients, their families, and health care systems. Artificial intelligence (AI) can be harnessed with available healthcare data to produce automated OUD prediction tools. In this retrospective study, we developed AI based models for OUD prediction and showed that AI can predict OUD more effectively than existing clinical tools including the unweighted opioid risk tool (ORT). Data include 474,208 patients’ data over 10 years; 269,748 were females with an average age of 56.78 years. Cases are prescription opioid users with at least one diagnosis of OUD or at least one prescription for buprenorphine or methadone. Controls are prescription opioid users with no OUD diagnoses or buprenorphine or methadone prescriptions. On 100 randomly selected test sets including 47,396 patients, our proposed transformer-based AI model can predict OUD more efficiently (AUC=0.742 ±0.021) compared to logistic regression (AUC=0.651 ±0.025), random forest (AUC=0.679 ±0.026), xgboost (AUC=0.690 ±0.027), long short-term memory model (AUC=0.706 ±0.026), transformer (AUC=0.725 ±0.024), and unweighted ORT model (AUC=0.559 ±0.025). Our results show that embedding AI algorithms into clinical care may assist clinicians in risk stratification and management of patients receiving opioid therapy. Read More ABFM Research Read all 2024 Addressing Social Determinants of Health in Family Medicine Practices Go to Addressing Social Determinants of Health in Family Medicine Practices 2024 How Early Career Family Medicine Women Physicians Negotiate Their First Job After Residency. Go to How Early Career Family Medicine Women Physicians Negotiate Their First Job After Residency. 2022 Barriers to care for perinatal patients with opioid use disorder: family physician perspectives Go to Barriers to care for perinatal patients with opioid use disorder: family physician perspectives 2022 Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health Go to Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health
Author(s) Fouladvand, Sajjad, Talbert, Jeffery, Dwoskin, Linda P, Bush, Heather, Meadows, Amy L, Peterson, Lars E, Mishra, Yash R, Roggenkamp, Steven K, Wang, Fei, Kavuluru, Ramakanth, and Chen, Jin Topic(s) Role of Primary Care, and Achieving Health System Goals Keyword(s) Practice Innovations Volume IEEE Journal of Biomedical and Health Informatics Source IEEE Journal of Biomedical and Health Informatics
ABFM Research Read all 2024 Addressing Social Determinants of Health in Family Medicine Practices Go to Addressing Social Determinants of Health in Family Medicine Practices 2024 How Early Career Family Medicine Women Physicians Negotiate Their First Job After Residency. Go to How Early Career Family Medicine Women Physicians Negotiate Their First Job After Residency. 2022 Barriers to care for perinatal patients with opioid use disorder: family physician perspectives Go to Barriers to care for perinatal patients with opioid use disorder: family physician perspectives 2022 Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health Go to Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health
2024 Addressing Social Determinants of Health in Family Medicine Practices Go to Addressing Social Determinants of Health in Family Medicine Practices
2024 How Early Career Family Medicine Women Physicians Negotiate Their First Job After Residency. Go to How Early Career Family Medicine Women Physicians Negotiate Their First Job After Residency.
2022 Barriers to care for perinatal patients with opioid use disorder: family physician perspectives Go to Barriers to care for perinatal patients with opioid use disorder: family physician perspectives
2022 Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health Go to Primary Care: The Actual Intelligence Required for Artificial Intelligence to Advance Health Care and Improve Health