RESUMO
OBJECTIVE: The objective of this work was to develop a risk prediction model for opioid overdose and opioid use disorder for patients at first opioid prescription and compare the predictive accuracy of morphine equivalent total dosage with the predictive accuracy of daily dosage . DESIGN: Records from patients 18-79 years of age with opioid prescriptions between January 1, 2016, and June 30, 2019, no prior history of adverse outcomes, and no malignant cancer diagnoses were collected from the electronic health record system of a medium-sized central Ohio health care system (n = 219,276). A Cox proportional-hazards model was developed to predict the adverse outcomes of opioid overdose and opioid use disorder from patient sociodemographic, pharmacological, and clinical diagnosis factors. RESULTS: During the study time frame, 573 patients experienced overdoses, and 2,571 patients were diagnosed with opioid use disorder. Morphine equivalent total dosage of opioid prescriptions was identified as a stronger predictor of adverse outcomes (C = 0.797) than morphine equivalent daily dosage (C = 0.792), with the best predictions coming from a model that includes both predictors (C = 0.803). In the model with both daily and total dosage predictors, patients receiving a high total / low daily dosage experienced a higher risk (hazard ratio [HR] = 2.17) than those receiving a low total / high daily dosage (HR = 2.02). Those receiving a high total / high daily dosage experienced the greatest risk of all (HR = 3.09). CONCLUSIONS: These findings demonstrate the value of including morphine equivalent total dosage as a predictor of adverse opioid outcomes and suggest that total dosage may be more strongly correlated with increased risk than daily dosage.