Prediction Model for Two-Year Risk of Opioid Overdose Among Patients Prescribed Chronic Opioid Therapy.
Ontology highlight
ABSTRACT: Background
Naloxone is a life-saving opioid antagonist. Chronic pain guidelines recommend that physicians co-prescribe naloxone to patients at high risk for opioid overdose. However, clinical tools to efficiently identify patients who could benefit from naloxone are lacking.Objective
To develop and validate an overdose predictive model which could be used in primary care settings to assess the need for naloxone.Design
Retrospective cohort.Setting
Derivation site was an integrated health system in Colorado; validation site was a safety-net health system in Colorado.Participants
We developed a predictive model in a cohort of 42,828 patients taking chronic opioid therapy and externally validated the model in 10,708 patients.Main measures
Potential predictors and outcomes (nonfatal pharmaceutical and heroin overdoses) were extracted from electronic health records. Fatal overdose outcomes were identified from state vital records. To match the approximate shelf-life of naloxone, we used Cox proportional hazards regression to model the 2-year risk of overdose. Calibration and discrimination were assessed.Key results
A five-variable predictive model showed good calibration and discrimination (bootstrap-corrected c-statistic?=?0.73, 95% confidence interval [CI] 0.69-0.78) in the derivation site, with sensitivity of 66.1% and specificity of 66.6%. In the validation site, the model showed good discrimination (c-statistic?=?0.75, 95% CI 0.70-0.80) and less than ideal calibration, with sensitivity and specificity of 82.2% and 49.5%, respectively.Conclusions
Among patients on chronic opioid therapy, the predictive model identified 66-82% of all subsequent opioid overdoses. This model is an efficient screening tool to identify patients who could benefit from naloxone to prevent overdose deaths. Population differences across the two sites limited calibration in the validation site.
SUBMITTER: Glanz JM
PROVIDER: S-EPMC6153224 | biostudies-literature | 2018 Oct
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:ImportanceAttempts to discontinue opioid therapy to reduce the risk of overdose and adhere to prescribing guidelines may lead patients to be exposed to variability in opioid dosing. Such dose variability may increase the risk of opioid overdose even if therapy discontinuation is associated with a reduction in risk.ObjectiveTo examine the association between opioid dose variability and opioid overdose.Design, setting, and participantsA nested case-control study was conducted in a large Colorado integrated health plan and delivery system from January 1, 2006, through June 30, 2018. Cohort members were individuals prescribed long-term opioid therapy.ExposuresDose variability was defined as the SD of the milligrams of morphine equivalents across each patient's follow-up and categorized based on the quintile distribution of the SD in the cohort (0-5.3, 5.4-9.1, 9.2-14.6, 14.7-27.2, and >27.2 mg of morphine equivalents).Main outcomes and measuresOpioid overdose cases were identified using International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes. Each case patient with overdose was matched to up to 20 control patients using risk set sampling. Conditional logistic regression models were used to generate matched odds ratios and 95% CIs, adjusted for age, sex, race/ethnicity, drug or alcohol use disorder, tobacco use, benzodiazepine dispensings, medical comorbidities, mental health disorder, opioid dose, and opioid formulation.ResultsIn a cohort of 14 898 patients (mean [SD] age, 56.3 [16.0] years; 8988 [60.3%] female) prescribed long-term opioid therapy, 228 case patients with incident opioid overdose were matched to 3547 control patients. The mean (SD) duration of opioid therapy was 36.7 (33.7) months in case patients and 33.0 (30.9) months in control patients. High-dose variability (SD >27.2 mg of morphine equivalents) was associated with a significantly increased risk of overdose compared with low-dose variability (matched odds ratio, 3.32; 95% CI, 1.63-6.77) independent of opioid dose.Conclusions and relevanceVariability in opioid dose may be a risk factor for opioid overdose, suggesting that practitioners should seek to minimize dose variability when managing long-term opioid therapy.
| S-EPMC6481879 | biostudies-literature
Project description:BACKGROUND:High opioid dosage has been associated with overdose, and clinical guidelines have cautioned against escalating dosages above 100 morphine-equivalent mg (MEM) based on the potential harm and the absence of evidence of benefit from high dosages. However, this 100 MEM threshold was chosen somewhat arbitrarily. OBJECTIVE:To examine the association of prescribed opioid dosage as a continuous measure in relation to risk of unintentional opioid overdose to identify the range of dosages associated with risk of overdose at a detailed level. METHODS:In this nested case-control study with risk-set sampling of controls, cases (opioid overdose decedents) and controls were identified from a population of patients of the Veterans Health Administration who were prescribed opioids and who have a chronic pain diagnosis. Unintentional fatal opioid analgesic overdose was measured from National Death Index records and prescribed opioid dosage from pharmacy records. RESULTS:The average prescribed opioid dosage was higher (P<0.001) for cases (mean=98.1 MEM, SD=112.7; median=60, interquartile range, 30-120), than controls (mean=47.7 MEM, SD=65.2; median=25, interquartile range, 15-45). In a ROC analysis, dosage was a moderately good "predictor" of opioid overdose death, indicating that, on average, overdose cases had a prescribed opioid dosage higher than 71% of controls. CONCLUSIONS:A clear cut-point in opioid dosage to distinguish between overdose cases and controls was not found. However, lowering the recommended dosage threshold below the 100 MEM used in many recent guidelines would affect proportionately few patients not at risk for overdose while potentially benefitting many of those at risk for overdose.
| S-EPMC6626611 | biostudies-literature
Project description:BackgroundOpioid overdose is a public health crisis. This study describes efforts to develop and validate the Brief Opioid Overdose Knowledge (BOOK) questionnaire to assess patient knowledge gaps related to opioid overdose risks.MethodsTwo samples of illicit opioid users and a third sample of patients receiving an opioid for the treatment of chronic pain (total N = 848) completed self-report items pertaining to opioid overdose risks.ResultsA 3-factor scale was established, representing Opioid Knowledge (4 items), Opioid Overdose Knowledge (4 items), and Opioid Overdose Response Knowledge (4 items). The scale had strong internal and face validity. Patients with chronic pain performed worse than illicit drug users in almost all items assessed, highlighting the need to increase knowledge of opioid overdose risk to this population.ConclusionsThis study sought to develop a brief, internally valid method for quickly assessing deficits in opioid overdose risk areas within users of illicit and prescribed opioids, to provide an efficient metric for assessing and comparing educational interventions, facilitate conversations between physicians and patients about overdose risks, and help formally identify knowledge deficits in other patient populations.
| S-EPMC5042823 | biostudies-literature
Project description:BackgroundNonfatal opioid overdose (OD) is an opportunity to identify patients who may benefit from interventions to reduce repeated overdose (rOD). In this study, we sought to determine risk and protective factors associated with rOD.MethodsIn this retrospective cohort study of 4,155 patients aged 18-64 who presented to one of 16 emergency departments in a single Western Pennsylvania health system between July 2015 and January 2018 for index opioid overdose (iOD) and survived to discharge, we identified demographic and clinical factors association with rOD within one-year. Relative risk of repeated opioid overdose was estimated using adjusted Cox proportional hazard ratios (aHRs).Results14.9 % of patients (95 % CI 13.9-16.1) had a rOD, with 29 % occurring within 30 days from iOD. The adjusted hazard of opioid overdose was increased for male patients (aHR = 1.19; 95 % CI 1.01, 1.41), those with pre-iOD diagnoses of anxiety (aHR = 1.41; 95 % CI1.13, 1.77), depression (aHR = 1.44; 95 % CI 1.17, 1.78), substance use disorders (aHR = 1.30; 95 % CI 1.09, 1.55), and alcohol use disorder (aHR = 1.52; 95 % CI 1.02, 2.25). The hazard was lower for individuals prescribed an opioid in the 90 days prior to iOD (aHR = 0.59; 95 % CI 0.37, 0.97) and those admitted to the hospital for iOD (aHR = 0.56; 95 % CI 0.37, 0.86).ConclusionWe found that, among ED patients who survive an initial OD, mental health and substance use diagnoses are associated with a higher hazard of repeated overdoses whereas opioids prescriptions and admission are associated with lower hazards.
| S-EPMC7127977 | biostudies-literature
Project description:Importance:Family members are cited as a common source of prescription opioids used for nonmedical reasons. However, the overdose risk associated with exposure to opioids prescribed to family members among adolescents and young adults is not well established. Objective:To assess the association of opioids prescribed to family members with pharmaceutical opioid overdose among youth. Design, Setting, and Participants:This cohort study included 45?145 family units with a total of 72?040 adolescents and young adults aged 11 to 26 years enrolled in a Kaiser Permanente Colorado health plan in 2006 and observed through June 2018. Exposures:Opioid prescriptions and dosage dispensed to family members and youth in the past month. Main Outcomes and Measures:Fatal pharmaceutical opioid overdoses identified in vital records and nonfatal pharmaceutical opioid overdoses identified in emergency department and inpatient settings. Time to first overdose was modeled using Cox regression. Results:The study population consisted of 72?040 adolescents and young adults (mean [SD] age across follow-up, 19.3 [3.7] years; 36?646 [50.9%] girls and women) nested in 45?145 family units. Youth were more commonly exposed to prescription opioids dispensed to a family member than through their own prescriptions. During follow-up, 26?284 youth (36.5%) filled at least 1 opioid prescription, and 47?461 youth (65.9%) had at least 1 family member with a prescription. Exposure to family members with opioid prescriptions in the past month was associated with increased risk of pharmaceutical opioid overdose (adjusted hazard ratio [aHR], 2.17; 95% CI, 1.24-3.79) independent of opioids prescribed to youth (aHR, 6.62; 95% CI, 3.39-12.91). Concurrent exposure to opioid prescriptions from youth and family members was associated with substantially increased overdose risk (aHR, 12.99; 95% CI, 5.08-33.25). High dosage of total morphine milligram equivalents (MME) prescribed to family members in the past month was associated with youth overdose (0 MME vs >0 to <200 MME: aHR, 1.39; 95% CI, 0.51-3.81; 0 MME vs 200 to <600 MME: aHR, 1.49; 95% CI, 0.59-3.77; 0 MME vs ?600 MME: aHR, 2.93; 95% CI, 1.55-5.56). Conclusions and Relevance:In this study of youth linked to family members, exposure to family members' prescribed opioids was associated with increased risk of pharmaceutical opioid overdose, independent of opioids prescribed to youth. Further interventions targeting youth and families are needed, including counseling patients about the risks of opioids to youth in their families.
| S-EPMC7462253 | biostudies-literature
Project description:IntroductionIn the context of an opioid public health crisis, U.S. medical schools have been called upon to strengthen curricula on the appropriate use of opioids, with an emphasis on maximizing benefits while utilizing risk-mitigation strategies to prevent addiction and overdose.MethodsThis self-contained module provides an overview of the opioid crisis and presents recent clinical guidelines on opioid risk mitigation, as well as information regarding prevention and treatment of opioid overdose. This module then gives learners the opportunity to practice these skills by solving an evolving case of back pain.ResultsVerbal and written feedback on the module from students revealed that the majority strongly agreed that, overall, the module was valuable as an educational tool.DiscussionThis module was created to help medical educators update the training of students in risk mitigation strategies and the steps of opioid overdose resuscitation. The feedback to date from students and faculty has been positive and supports its use in undergraduate medical education.
| S-EPMC6338191 | biostudies-literature
Project description:IntroductionRetention in opioid agonist therapy consistently has been linked with improved outcomes among people with opioid use disorder. However, less is known about the links between patterns of engagement in opioid agonist therapy over the long term and overdose risk. This study assesses the association of opioid agonist therapy retention trajectories with nonfatal overdose.MethodsData were drawn from 2 community-recruited prospective cohorts of people who use drugs in Vancouver, Canada. Latent class growth analysis was used to identify trajectories of opioid agonist therapy retention among people with opioid use disorder initiating therapy, and generalized estimating equations assessed the association of these trajectories with nonfatal overdose events after opioid agonist therapy initiation.ResultsBetween 2005 and 2018, among 438 opioid agonist therapy initiators, 4 retention trajectories were identified: consistently high (35.6%), increasing (26.0%), consistently low (23.3%), and decreasing (15.1%) opioid agonist therapy engagement. During the study period, there were 371 nonfatal overdose events, with 179 (40.1%) participants reporting ≥1. In adjusted analysis, the consistently low (AOR=1.73, 95% CI=1.10, 2.71) and decreasing (AOR=1.87, 95% CI=1.18, 2.95) retention trajectories were positively associated with increased odds of nonfatal overdose compared with the consistently high opioid agonist therapy retention class.ConclusionsSuboptimal trajectories of opioid agonist therapy retention were associated with an increased likelihood of nonfatal overdose. These findings suggest that reducing the barriers to sustained engagement in opioid agonist therapy will be critical to address North America's overdose epidemic.
| S-EPMC7978040 | biostudies-literature
Project description:BackgroundOpioid prescribing for a range of health issues is increasing globally. The risk of fatal and non-fatal overdose is increased among people prescribed strong opioids: in high doses in the context of polypharmacy (the use of multiple medications at the same time), especially with other sedatives; and among people with multiple morbidities including cardiorespiratory, hepatic and renal conditions. This study described and quantified the prescribing of strong opioids, comorbidities and other overdose risk factors among those prescribed strong opioids, and factors associated with high/very high opioid dosage in a regional health authority in Scotland as part of a wider service improvement exercise.MethodsParticipating practices ran searches to identify patients prescribed strong opioids and their characteristics, polypharmacy, and other overdose risk factors. Data were anonymised before being analysed at practice and patient-level. Morphine Equivalent Doses were calculated for patients based on drug/dose information and classed as Low/Medium/High/Very High. Descriptive statistics were generated on the strong opioid patient population and overdose risk factors. The relationship between the prescribing of strong opioids and practice/patient-level factors was investigated using linear and logistic regression models.ResultsEighty-five percent (46/54) of GP practices participated. 12.4% (42,382/341,240) of individuals in participating practices were prescribed opioids and, of these, one third (14,079/42,382) were prescribed strong opioids. The most common comorbidities and overdose risk factors among strong opioid recipients were pain (67.2%), cardiovascular disease (43.2%), and mental health problems (39.3%). There was a positive significant relationship between level of social deprivation among practice caseload and level of strong opioid prescribing (p < 0.001). People prescribed strong opioids tended to be older (mean 59.7 years) and female (8638, 61.4%) and, among a subset of patients, age, gender and opioid drug class were significantly associated with prescribing of High/Very High doses.ConclusionsOur findings have identified a large population at potential risk of prescription opioid overdose. There is a need to explore pragmatic models of tailored interventions which may reduce the risk of overdose within this group and clinical practice may need to be tightened to minimise overdose risk for individuals prescribed high dose opioids.
| S-EPMC8223343 | biostudies-literature
Project description:BACKGROUND:Predicting which individuals who are prescribed buprenorphine for opioid use disorder are most likely to experience an overdose can help target interventions to prevent relapse and subsequent consequences. METHODS:We used Maryland prescription drug monitoring data from 2015 to identify risk factors for nonfatal opioid overdoses that were identified in hospital discharge records in 2016. We developed a predictive risk model for prospective nonfatal opioid overdoses among buprenorphine patients (N?=?25,487). We estimated a series of models that included demographics plus opioid, buprenorphine and benzodiazepine prescription variables. We applied logistic regression to generate performance measures. RESULTS:About 3.24% of the study cohort had ?1 nonfatal opioid overdoses. In the model with all predictors, odds of nonfatal overdoses among buprenorphine patients were higher among males (OR?=?1.39, 95% CI:1.21-1.62) and those with more buprenorphine pharmacies (OR?=?1.19, 95% CI:1.11-1.28), 1+ buprenorphine prescription paid by Medicaid (OR?=?1.21, 95% CI:1.02-1.48), Medicare (OR?=?1.93, 95% CI:1.63-2.43), or a commercial plan (OR?=?1.98, 95% CI:1.30-2.89), 1+ opioid prescription paid by Medicare (OR?=?1.30, 95% CI:1.03-1.68), and more benzodiazepine prescriptions (OR?=?1.04, 95% CI:1.02-1.05). The odds were lower among those with longer days of buprenorphine (OR?=?0.64, 95% CI:0.60-0.69) or opioid (OR?=?0.79, 95% CI:0.65-0.95) supply. The model had moderate predictive ability (c-statistic?=?0.69). CONCLUSIONS:Several modifiable risk factors, such as length of buprenorphine treatment, may be targets for interventions to improve clinical care and reduce harms. This model could be practically implemented with common prescription-related information and allow payers and clinical systems to better target overdose risk reduction interventions, such as naloxone distribution.
| S-EPMC6713520 | biostudies-literature
Project description:Opioid-related mortality continues to increase in the United States. The current study assesses demographic and behavioral predictors of perceived overdose risk among individuals who use opioids illicitly. By examining these correlates in the context of established overdose risk factors, we aim to assess whether characteristics and behaviors that have been associated with actual overdose risk translate to higher perception of risk.We conducted a cross-sectional survey of 172 adult illicit opioid users in San Francisco, CA and used multivariable logistic regression to identify predictors of perception of high risk for opioid overdose.Age (aOR=0.96, 95%CI=0.93-1.00) and number of injection days per month (0.91, 0.86-0.97) were associated with a lower odds of perceived high overdose risk. There was no independent association between use of opioid analgesics, concurrent use of opioids and benzodiazepines or cocaine, or HIV status and overdose risk perception.Opioid users who injected more frequently and those who were older were less likely to perceive themselves as being at risk of overdose, notwithstanding that those who inject more are at higher risk of overdose and those who are older are at higher risk overdose mortality. In addition, despite being established overdose risk factors, there was no relationship between use of opioid analgesics, concurrent use of opioids and cocaine or benzodiazepines, or self-reported HIV status and overdose risk perception. These findings highlight key populations of opioid users and established risk factors that may merit focused attention as part of education-based overdose prevention and opioid management strategies.
| S-EPMC4734628 | biostudies-literature