Factors Associated with Opioid Overdose after an Initial Opioid Prescription

Importance: The opioid epidemic continues to be a public health crisis in the US. Objective: To assess the patient factors and early time-varying prescription-related factors associated with opioid-related fatal or nonfatal overdose. Design, Setting, and Participants: This cohort study evaluated opioid-naive adult patients in Oregon using data from the Oregon Comprehensive Opioid Risk Registry, which links all payer claims data to other health data sets in the state of Oregon. The observational, population-based sample filled a first (index) opioid prescription in 2015 and was followed up until December 31, 2018. Data analyses were performed from March 1, 2020, to June 15, 2021. Exposures: Overdose after the index opioid prescription. Main Outcomes and Measures: The outcome was an overdose event. The sample was followed up to identify fatal or nonfatal opioid overdoses. Patient and prescription characteristics were identified. Prescription characteristics in the first 6 months after the index prescription were modeled as cumulative, time-dependent measures that were updated monthly through the sixth month of follow-up. A time-dependent Cox proportional hazards regression model was used to assess patient and prescription characteristics that were associated with an increased risk for overdose events. Results: The cohort comprised 236921 patients (133 839 women [56.5%]), of whom 667 (0.3%) experienced opioid overdose. Risk of overdose was highest among individuals 75 years or older (adjusted hazard ratio [aHR], 3.22; 95% CI, 1.94-5.36) compared with those aged 35 to 44 years; men (aHR, 1.29; 95% CI, 1.10-1.51); those who were dually eligible for Medicaid and Medicare Advantage (aHR, 4.37; 95% CI, 3.09-6.18), had Medicaid (aHR, 3.77; 95% CI, 2.97-4.80), or had Medicare Advantage (aHR, 2.18; 95% CI, 1.44-3.31) compared with those with commercial insurance; those with comorbid substance use disorder (aHR, 2.74; 95% CI, 2.15-3.50), with depression (aHR, 1.26; 95% CI, 1.03-1.55), or with 1 to 2 comorbidities (aHR, 1.32; 95% CI, 1.08-1.62) or 3 or more comorbidities (aHR, 1.90; 95% CI, 1.42-2.53) compared with none. Patients were at an increased overdose risk if they filled oxycodone (aHR, 1.70; 95% CI, 1.04-2.77) or tramadol (aHR, 2.80; 95% CI, 1.34-5.84) compared with codeine; used benzodiazepines (aHR, 1.06; 95% CI, 1.01-1.11); used concurrent opioids and benzodiazepines (aHR, 2.11; 95% CI, 1.70-2.62); or filled opioids from 3 or more pharmacies over 6 months (aHR, 1.38; 95% CI, 1.09-1.75). Conclusions and Relevance: This cohort study used a comprehensive data set to identify patient and prescription-related risk factors that were associated with opioid overdose. These findings may guide opioid counseling and monitoring, the development of clinical decision-making tools, and opioid prevention and treatment resources for individuals who are at greatest risk for opioid overdose

Opioid-Prescribing Continuity and Risky Opioid Prescriptions

We aimed to better understand the association between opioid-prescribing continuity, risky prescribing patterns, and overdose risk. For this retrospective cohort study, we included patients with long-term opioid use, pulling data from Oregon\u27s Prescription Drug Monitoring Program (PDMP), vital records, and hospital discharge registry. A continuity of care index (COCI) score was calculated for each patient, and we defined metrics to describe risky prescribing and overdose. As prescribing continuity increased, likelihood of filling risky opioid prescriptions and overdose hospitalization decreased. Prescribing continuity is an important factor associated with opioid harms and can be calculated using administrative pharmacy data

Use of Prescription Opioids Before and After an Operation for Chronic Pain (Lumbar Fusion Surgery)

Lumbar fusion surgery is usually prompted by chronic back pain, and many patients receive long-term preoperative opioid analgesics. Many expect surgery to eliminate the need for opioids. We sought to determine what fraction of long-term preoperative opioid users discontinue or reduce dosage postoperatively; what fraction of patients with little preoperative use initiate long-term use; and what predicts long-term postoperative use. This retrospective cohort study included 2491 adults undergoing lumbar fusion surgery for degenerative conditions, using Oregon\u27s prescription drug monitoring program to quantify opioid use before and after hospitalization. We defined long-term postoperative use as ≥ 4 prescriptions filled in the 7 months after hospitalization, with at least 3 occurring \u3e 30 days after hospitalization. Overall, 1045 patients received long-term opioids preoperatively, and 1094 postoperatively. Among long-term preoperative users, 77.1% continued long-term postoperative use, and 13.8 % had episodic use. Only 9.1 % discontinued or had short-term postoperative use. Among preoperative users, 34.4% received a lower dose postoperatively, but 44.8% received a higher long-term dose. Among patients with no preoperative opioids, 12.8 % became long-term users. In multivariable models, the strongest predictor of long-term postoperative use was cumulative preoperative opioid dose (odds ratio of 15.47 [ 95% confidence interval 8.53-28.06] in the highest quartile ) . Cumulative dose and number of opioid prescribers in the 30-day postoperative period were also associated with long-term use. Thus, lumbar fusion surgery infrequently eliminated long-term opioid use. Opioid-naive patients had a substantial risk of initiating long-term use. Patients should have realistic expectations regarding opioid use after lumbar fusion surgery

Factors associated with opioid overdose after an initial opioid prescription.

IMPORTANCE: The opioid epidemic continues to be a public health crisis in the US. OBJECTIVE: To assess the patient factors and early time-varying prescription-related factors associated with opioid-related fatal or nonfatal overdose. DESIGN, SETTING, AND PARTICIPANTS: This cohort study evaluated opioid-naive adult patients in Oregon using data from the Oregon Comprehensive Opioid Risk Registry, which links all payer claims data to other health data sets in the state of Oregon. The observational, population-based sample filled a first (index) opioid prescription in 2015 and was followed up until December 31, 2018. Data analyses were performed from March 1, 2020, to June 15, 2021. EXPOSURES: Overdose after the index opioid prescription. MAIN OUTCOMES AND MEASURES: The outcome was an overdose event. The sample was followed up to identify fatal or nonfatal opioid overdoses. Patient and prescription characteristics were identified. Prescription characteristics in the first 6 months after the index prescription were modeled as cumulative, time-dependent measures that were updated monthly through the sixth month of follow-up. A time-dependent Cox proportional hazards regression model was used to assess patient and prescription characteristics that were associated with an increased risk for overdose events. RESULTS: The cohort comprised 236 921 patients (133 839 women [56.5%]), of whom 667 (0.3%) experienced opioid overdose. Risk of overdose was highest among individuals 75 years or older (adjusted hazard ratio [aHR], 3.22; 95% CI, 1.94-5.36) compared with those aged 35 to 44 years; men (aHR, 1.29; 95% CI, 1.10-1.51); those who were dually eligible for Medicaid and Medicare Advantage (aHR, 4.37; 95% CI, 3.09-6.18), had Medicaid (aHR, 3.77; 95% CI, 2.97-4.80), or had Medicare Advantage (aHR, 2.18; 95% CI, 1.44-3.31) compared with those with commercial insurance; those with comorbid substance use disorder (aHR, 2.74; 95% CI, 2.15-3.50), with depression (aHR, 1.26; 95% CI, 1.03-1.55), or with 1 to 2 comorbidities (aHR, 1.32; 95% CI, 1.08-1.62) or 3 or more comorbidities (aHR, 1.90; 95% CI, 1.42-2.53) compared with none. Patients were at an increased overdose risk if they filled oxycodone (aHR, 1.70; 95% CI, 1.04-2.77) or tramadol (aHR, 2.80; 95% CI, 1.34-5.84) compared with codeine; used benzodiazepines (aHR, 1.06; 95% CI, 1.01-1.11); used concurrent opioids and benzodiazepines (aHR, 2.11; 95% CI, 1.70-2.62); or filled opioids from 3 or more pharmacies over 6 months (aHR, 1.38; 95% CI, 1.09-1.75). CONCLUSIONS AND RELEVANCE: This cohort study used a comprehensive data set to identify patient and prescription-related risk factors that were associated with opioid overdose. These findings may guide opioid counseling and monitoring, the development of clinical decision-making tools, and opioid prevention and treatment resources for individuals who are at greatest risk for opioid overdose