Incidence and Variables Associated With Inconsistencies in Opioid Prescribing at Hospital Discharge and Its Associated Adverse Drug Outcomes.

Abstract

OBJECTIVES\nOpioid-related medication errors (MEs) can have a significant impact on patient health and contribute to opioid misuse. The objective of this study was to estimate the incidence of and variables associated with the receipt of an opioid prescription and opioid-related MEs (omissions, duplications, or dose changes) at hospital discharge. We also determined rates of adverse drug events and risks of emergency department visits, readmissions, or death 30 days and 90 days post discharge associated with MEs.\n\n\nMETHODS\nA cohort of hospitalized patients discharged from the McGill University Health Centre between 2014 and 2016 was assembled. The impact of opioid-related MEs was assessed in a propensity score-adjusted logistic regression models. Multivariable logistic regression was used to determine characteristics associated with MEs and discharge opioid prescription.\n\n\nRESULTS\nA total of 1530 (43.9%) of 3486 patients were prescribed opioids, of which 13.4% (n\xa0= 205) of patients had at least 1 opioid-related ME. Rates of MEs were higher in handwritten prescriptions compared to the electronic reconciliation discharge prescription group (20.6% vs 1.2%). Computer-based prescriptions were associated with a 69% lower risk of opioid-related MEs (adjusted odds ratio: 0.31, 95% confidence interval: 0.14-0.65) as well as 63% lower risk of receiving an opioid prescription. Opioid-related MEs were associated with a 2.3 times increased risk of healthcare utilization in the 30 days postdischarge period (adjusted odds ratio: 2.32, 95% confidence interval: 1.24-4.32).\n\n\nCONCLUSIONS\nOpioid-related MEs are common in handwritten discharge prescriptions. Our findings highlight the need for computer-based prescribing platforms and careful review of medications during critical periods of care such as hospital transitions.