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Objective: To validate a risk index that estimates the likelihood of overdose or serious opioid-induced respiratory depression (OIRD) among medical users of prescription opioids., Subjects and Methods: A case-control analysis of 18,365,497 patients with an opioid prescription from 2009 to 2013 in the IMS PharMetrics Plus commercially insured health plan claims database (CIP). An OIRD event occurred in 7,234 cases. Four controls were selected per case. Validity of the Risk Index for Overdose or Serious Opioid-induced Respiratory Depression (RIOSORD), developed previously using Veterans Health Administration (VHA) patient data, was assessed. Multivariable logistic regression was used within the CIP study population to develop a slightly refined RIOSORD. The composition and performance of the CIP-based RIOSORD was evaluated and compared with VHA-based RIOSORD., Results: VHA-RIOSORD performed well in discriminating OIRD events in CIP (C-statistic = 0.85). Additionally, re-estimation of logistic model coefficients in CIP yielded a 0.90 C-statistic. The resulting comorbidity and pharmacotherapy variables most highly associated with OIRD and retained in the CIP-RIOSORD were largely concordant with VHA-RIOSORD. These variables included neuropsychiatric and cardiopulmonary disorders, impaired drug excretion, opioid characteristics, and concurrent psychoactive medications. The average predicted probability of OIRD ranged from 2% to 83%, with excellent agreement between predicted and observed incidence across risk classes., Conclusions: RIOSORD had excellent predictive accuracy in a large population of US medical users of prescription opioids, similar to its performance in VHA. This practical risk index is designed to support clinical decision-making for safer opioid prescribing, and its clinical utility should be evaluated prospectively., (© 2017 American Academy of Pain Medicine.)

Objective: To characterize the risk factors associated with overdose or serious opioid-induced respiratory depression (OIRD) among medical users of prescription opioids in a commercially insured population (CIP) and to compare risk factor profiles between the CIP and Veterans Health Administration (VHA) population., Subjects and Methods: Analysis of data from 18,365,497 patients in the IMS PharMetrics Plus health plan claims database (CIP) who were dispensed a prescription opioid in 2009 to 2013. Baseline factors associated with an event of serious OIRD among 7,234 cases and 28,932 controls were identified using multivariable logistic regression. The CIP risk factor profile was compared with that from a corresponding logistic regression among 817 VHA cases and 8,170 controls in 2010 to 2012., Results: The strongest associations with serious OIRD in CIP were diagnosed substance use disorder (odds ratio [OR] = 10.20, 95% confidence interval [CI] = 9.06-11.40) and depression (OR = 3.12, 95% CI = 2.84-3.42). Other strongly associated factors included other mental health disorders; impaired liver, renal, vascular, and pulmonary function; prescribed fentanyl, methadone, and morphine; higher daily opioid doses; and concurrent psychoactive medications. These risk factors, except depression, vascular disease, and specific opioids, largely aligned with VHA despite CIP being substantially younger, including more females and less chronic disease, and having greater prescribing prevalence of higher daily opioid doses, specific opioids, and most selected nonopioids., Conclusions: Risk factor profiles for serious OIRD among US medical users of prescription opioids with private or public health insurance were largely concordant despite substantial differences between the populations in demographics, clinical conditions, health care delivery systems, and clinical practices., (© 2017 American Academy of Pain Medicine.)

Objective: Develop a risk index to estimate the likelihood of life-threatening respiratory depression or overdose among medical users of prescription opioids., Subjects, Design, and Methods: A case-control analysis of administrative health care data from the Veterans' Health Administration identified 1,877,841 patients with a pharmacy record for an opioid prescription between October 1, 2010 and September 30, 2012. Overdose or serious opioid-induced respiratory depression (OSORD) occurred in 817. Ten controls were selected per case (n = 8,170). Items for an OSORD risk index (RIOSORD) were selected through logistic regression modeling, with point values assigned to each predictor. Modeling of risk index scores produced predicted probabilities of OSORD; risk classes were defined by the predicted probability distribution., Results: Fifteen variables most highly associated with OSORD were retained as items, including mental health disorders and pharmacotherapy; impaired drug metabolism or excretion; pulmonary disorders; specific opioid characteristics; and recent hospital visits. The average predicted probability of experiencing OSORD ranged from 3% in the lowest risk decile to 94% in the highest, with excellent agreement between predicted and observed incidence across risk classes. The model's C-statistic was 0.88 and Hosmer-Lemeshow goodness-of-fit statistic 10.8 (P > 0.05)., Conclusion: RIOSORD performed well in identifying medical users of prescription opioids within the Veterans' Health Administration at elevated risk of overdose or life-threatening respiratory depression, those most likely to benefit from preventive interventions. This novel, clinically practical, risk index is intended to provide clinical decision support for safer pain management. It should be assessed, and refined as necessary, in a more generalizable population, and prospectively evaluated., (© 2015 The Authors Pain Medicine published by Wiley Periodicals, Inc. on behalf of American Academy of Pain Medicine.)

Objective: Prescription opioid use and deaths related to serious toxicity, including overdose, have increased dramatically in the United States since 1999. However, factors associated with serious opioid-related respiratory or central nervous system (CNS) depression or overdose in medical users are not well characterized. The objective of this study was to examine the factors associated with serious toxicity in medical users of prescription opioids., Design: Retrospective, nested, case-control analysis of Veterans Health Administration (VHA) medical, pharmacy, and health care resource utilization administrative data., Subjects: Patients dispensed an opioid by VHA between October 1, 2010 and September 30, 2012 (N=8,987)., Methods: Cases (N=817) experienced life-threatening opioid-related respiratory/CNS depression or overdose. Ten controls were randomly assigned to each case (N=8,170). Logistic regression was used to examine associations with the outcome., Results: The strongest associations were maximum prescribed daily morphine equivalent dose (MED)≥ 100 mg (odds ratio [OR]=4.1, 95% confidence interval [CI], 2.6-6.5), history of opioid dependence (OR=3.9, 95% CI, 2.6-5.8), and hospitalization during the 6 months before the serious toxicity or overdose event (OR=2.9, 95% CI, 2.3-3.6). Liver disease, extended-release or long-acting opioids, and daily MED of 20 mg or more were also significantly associated., Conclusions: Substantial risk for serious opioid-related toxicity and overdose exists at even relatively low maximum prescribed daily MED, especially in patients already vulnerable due to underlying demographic factors, comorbid conditions, and concomitant use of CNS depressant medications or substances. Screening patients for risk, providing education, and coprescribing naloxone for those at elevated risk may be effective at reducing serious opioid-related respiratory/CNS depression and overdose in medical users of prescription opioids., (Wiley Periodicals, Inc.)