Association Between Opioid Dose Variability and Opioid Overdose Among Adults Prescribed Long-term Opioid Therapy

Independent and joint contributions of physical disability and chronic pain to incident opioid use disorder and opioid overdose among Medicaid patients

BACKGROUND

Chronic pain has been extensively explored as a risk factor for opioid misuse, resulting in increased focus on opioid prescribing practices for individuals with such conditions. Physical disability sometimes co-occurs with chronic pain but may also represent an independent risk factor for opioid misuse. However, previous research has not disentangled whether disability contributes to risk independent of chronic pain.

METHODS

Here, we estimate the independent and joint adjusted associations between having a physical disability and co-occurring chronic pain condition at time of Medicaid enrollment on subsequent 18-month risk of incident opioid use disorder (OUD) and non-fatal, unintentional opioid overdose among non-elderly, adult Medicaid beneficiaries (2016-2019).

RESULTS

We find robust evidence that having a physical disability approximately doubles the risk of incident OUD or opioid overdose, and physical disability co-occurring with chronic pain increases the risks approximately sixfold as compared to having neither chronic pain nor disability. In absolute numbers, those with neither a physical disability nor chronic pain condition have a 1.8% adjusted risk of incident OUD over 18 months of follow-up, those with physical disability alone have an 2.9% incident risk, those with chronic pain alone have a 3.6% incident risk, and those with co-occurring physical disability and chronic pain have a 11.1% incident risk.

CONCLUSIONS

These findings suggest that those with a physical disability should receive increased attention from the medical and healthcare communities to reduce their risk of opioid misuse and attendant negative outcomes.

Prescription Opioid Dose Reductions and Potential Adverse Events: a Multi-site Observational Cohort Study in Diverse US Health Systems

BACKGROUND

In response to the opioid crisis in the United States, population-level prescribing of opioids has been decreasing; there are concerns, however, that dose reductions are related to potential adverse events.

OBJECTIVE

Examine associations between opioid dose reductions and risk of 1-month potential adverse events (emergency department (ED) visits, opioid overdose, benzodiazepine prescription fill, all-cause mortality).

DESIGN

This observational cohort study used electronic health record and claims data from eight United States health systems in a prescription opioid registry (Clinical Trials Network-0084). All opioid fills (excluding buprenorphine) between 1/1/2012 and 12/31/2018 were used to identify baseline periods with mean morphine milligram equivalents daily dose of  ≥ 50 during six consecutive months.

PATIENTS

We identified 60,040 non-cancer patients with  ≥ one 2-month dose reduction period (600,234 unique dose reduction periods).

MAIN MEASURES

Analyses examined associations between dose reduction levels (1- < 15%, 15- < 30%, 30- < 100%, 100% over 2 months) and potential adverse events in the month following a dose reduction using logistic regression analysis, adjusting for patient characteristics.

KEY RESULTS

Overall, dose reduction periods involved mean reductions of 18.7%. Compared to reductions of 1- < 15%, dose reductions of 30- < 100% were associated with higher odds of ED visits (OR 1.14, 95% CI 1.10, 1.17), opioid overdose (OR 1.41, 95% CI 1.09-1.81), and all-cause mortality (OR 1.39, 95% CI 1.16-1.67), but lower odds of a benzodiazepine fill (OR 0.83, 95% CI 0.81-0.85). Dose reductions of 15- < 30%, compared to 1- < 15%, were associated with higher odds of ED visits (OR 1.08, 95% CI 1.05-1.11) and lower odds of a benzodiazepine fill (OR 0.93, 95% CI 0.92-0.95), but were not associated with opioid overdose and all-cause mortality.

CONCLUSIONS

Larger reductions for patients on opioid therapy may raise risk of potential adverse events in the month after reduction and should be carefully monitored.

Determination of trace morphine and its metabolites in mouse urine using a TpBD functionalized bivalve magnetic nano-adsorbent

In this study, a new type of covalent organic framework (TpBD) functionalized bivalved magnetic microsphere (TpBD-DS MNS) adsorbent was applied for the enrichment and detection of trace morphine and its metabolites in mouse urine. The main factors affecting the efficiency of magnetic solid phase extraction were optimized, and the optimal MSPE conditions were obtained. Combined with the UPLC-MS/MS technique, a new method for determining trace morphine and its metabolites in urine was established. The detection (LOD) and quantification (LOQ) limits for morphine and its metabolites ranged from 0.16 pg mL-1 to 0.53 pg mL-1 and 0.26 pg mL-1 to 1.25 pg mL-1, respectively. The recovery of the methods ranged from 87.4-97.3%, and the RSD was less than 5%. By employing this methodology, we successfully obtained the temporal change curve of morphine and its metabolites in mouse urine through collection and measurement post intravenous administration of morphine. This approach not only presents a novel means for investigating pharmacokinetics and drug monitoring but also demonstrates significant potential in the fields of forensic toxicology and drug abuse surveillance.

Impact of 30-day prescribed opioid dose trajectory on fatal overdose risk: A population-based, statewide cohort study

BACKGROUND

Both increases and decreases in patients' prescribed daily opioid dose have been linked to increased overdose risk, but associations between 30-day dose trajectories and subsequent overdose risk have not been systematically examined.

OBJECTIVE

To examine the associations between 30-day prescribed opioid dose trajectories and fatal opioid overdose risk during the subsequent 15 days.

DESIGN

Statewide cohort study using linked prescription drug monitoring program and death certificate data. We constructed a multivariable Cox proportional hazards model that accounted for time-varying prescription-, prescriber-, and pharmacy-level factors.

PARTICIPANTS

All patients prescribed an opioid analgesic in California from March to December, 2013 (5,326,392 patients).

MAIN MEASURES

Dependent variable: fatal drug overdose involving opioids. Primary independent variable: a 16-level variable denoting all possible opioid dose trajectories using the following categories for current and 30-day previously prescribed daily dose: 0-29, 30-59, 60-89, or ≥90 milligram morphine equivalents (MME).

KEY RESULTS

Relative to patients prescribed a stable daily dose of 0-29 MME, large (≥2 categories) dose increases and having a previous or current dose ≥60 MME per day were associated with significantly greater 15-day overdose risk. Patients whose dose decreased from ≥90 to 0-29 MME per day had significantly greater overdose risk compared to both patients prescribed a stable daily dose of ≥90 MME (aHR 3.56, 95%CI 2.24-5.67) and to patients prescribed a stable daily dose of 0-29 MME (aHR 7.87, 95%CI 5.49-11.28). Patients prescribed benzodiazepines also had significantly greater overdose risk; being prescribed Z-drugs, carisoprodol, or psychostimulants was not associated with overdose risk.

CONCLUSIONS

Large (≥2 categories) 30-day dose increases and decreases were both associated with increased risk of fatal opioid overdose, particularly for patients taking ≥90 MME whose opioids were abruptly stopped. Results align with 2022 CDC guidelines that urge caution when reducing opioid doses for patients taking long-term opioid for chronic pain.

An individual segmented trajectory approach for identifying opioid use patterns using longitudinal dispensing data

PURPOSE

The aim of this study is to use electronic opioid dispensing data to develop an individual segmented trajectory approach for identifying opioid use patterns. The resulting opioid use patterns can be used for examining the association between opioid use and drug overdose.

METHODS

We retrospectively assembled a cohort of members on long-term opioid therapy (LTOT) between January 1, 2006 and June 30, 2019 who were 18 years and older and enrolled in one of three health care systems in the US. We have developed an individual segmented trajectory analysis for identifying various opioid use patterns by scanning over the follow-up and finding distinct opioid use patterns based on variability measured with coefficient of variation and trends of milligram morphine equivalents levels.

RESULTS

Among 31, 865 members who were on LTOT between January 1, 2006 and June 30, 2019, 58.3% were female, and the average age was 55.4 years (STD = 15.4). The study population had 152 557 person-years of follow-up, with an average follow-up of 4.4 years per enrollment per person (STD = 3.4). This novel approach identified up to 13 distinct patterns including 88 756 episodes of "stable" pattern (42.1%) with an average follow-up of 11.2 months, 29 140 episodes of "increasing" pattern (13.8%) with an average follow-up of 6.0 months, 13 201 episodes of ≤10% dose reduction (6.3%) with an average follow-up of 10.4 months, 7286 episodes of 11%-20% dose reduction (3.5%) with an average follow-up of 5.3 months, 4457 episodes of 21%-30% dose reduction (2.1%) with an average follow-up of 4.0 months, and 9903 episodes of >30% dose reduction (4.7%) with an average follow-up of 2.6 months.

CONCLUSIONS

A novel approach was developed to identify 13 distinct opioid use patterns using each individual's longitudinal dispensing data and these patterns can be used in examining overdose risk during the time that these patterns are ongoing.

Psychiatric comorbidities in adults with sickle cell disease: A narrative review

Although descriptions of quality of life and patient reports of mood in sickle cell disease (SCD) have become more common in the literature, less is known about psychiatric illness prevalence, presentation, and treatment, particularly for adults. We provide a narrative review of what is known about common and debilitating psychiatric conditions such as depression, anxiety, and cognitive impairment, specifically for adults with SCD. We discuss the limitations of the current evidence, make provisional recommendations, and identify opportunities for research and improved care.

Longitudinal dose patterns among patients newly initiated on long-term opioid therapy in the United States, 2018 to 2019: an observational cohort study and time-series cluster analysis

ABSTRACT

Opioid prescribing varies widely, and prescribed opioid dosages for an individual can fluctuate over time. Patterns in daily opioid dosage among patients prescribed long-term opioid therapy have not been previously examined. This study uses a novel application of time-series cluster analysis to characterize and visualize daily opioid dosage trajectories and associated demographic characteristics of patients newly initiated on long-term opioid therapy. We used 2018 to 2019 data from the IQVIA Longitudinal Prescription (LRx) all-payer pharmacy database, which covers 92% of retail pharmacy prescriptions dispensed in the United States. We identified a cohort of 277,967 patients newly initiated on long-term opioid therapy during 2018. Patients were stratified into 4 categories based on their mean daily dosage during a 90-day baseline period (<50, 50-89, 90-149, and ≥150 morphine milligram equivalent [MME]) and followed for a 270-day follow-up period. Time-series cluster analysis identified 2 clusters for each of the 3 baseline dosage categories <150 MME and 3 clusters for the baseline dosage category ≥150 MME. One cluster in each baseline dosage category comprised opioid dosage trajectories with decreases in dosage at the end of the follow-up period (80.7%, 98.7%, 98.7%, and 99.0%, respectively), discontinuation (58.5%, 80.0%, 79.3%, and 81.7%, respectively), and rapid tapering (50.8%, 85.8%, 87.5%, and 92.9%, respectively). These findings indicate multiple clusters of patients newly initiated on long-term opioid therapy who experience discontinuation and rapid tapering and highlight potential areas for clinician training to advance evidence-based guideline-concordant opioid prescribing, including strategies to minimize sudden dosage changes, discontinuation, or rapid tapering, and the importance of shared decision-making.

Are opioids effective analgesics and is physiological opioid dependence benign? Revising current assumptions to effectively manage long-term opioid therapy and its deprescribing

A re-examination of clinical principles of long-term opioid therapy (LTOT) for chronic pain is long overdue amid the ongoing opioid crisis. Most patients on LTOT report ineffectiveness (poor pain control, function and health) but still find deprescribing challenging. Although prescribed as analgesics, opioids more likely provide pain relief primarily through reward system actions (enhanced relief and motivation) and placebo effect and less through antinociceptive effects. The unavoidable physiologic LTOT dependence can automatically lead to a paradoxical worsening of pain, disability and medical instability (maladaptive opioid dependence) without addiction due to allostatic opponent neuroadaptations involving reward/antireward and nociceptive/antinociceptive systems. This opioid-induced chronic pain syndrome (OICP) can persist/progress whether LTOT dose is maintained at the same level, increased, decreased or discontinued. Current conceptualization of LTOT as a straightforward long-term analgesic therapy appears incongruous in view of the complex mechanisms of opioid action, LTOT dependence and OICP. LTOT can be more appropriately conceptualized as therapeutic induction and maintenance of an adaptive LTOT dependence for functional improvement irrespective of analgesic benefits. Adaptive LTOT dependence should be ideally used for a limited time to achieve maximum functional recovery and deprescribed while maintaining functional gains. Patients on LTOT should be regularly re-evaluated to identify if maladaptive LTOT dependence with OICP has diminished any functional gains or leads to ineffectiveness. Ineffective LTOT (with maladaptive LTOT dependence) should be modified to make it safer and more effective. An adequately functional life without opioids is the ideal healthy long-term goal for both LTOT initiation and LTOT modification.

Predictors of fatal and nonfatal overdose after prescription of opioids for chronic pain: a systematic review and meta-analysis of observational studies

BACKGROUND

Higher doses of opioids, mental health comorbidities, co-prescription of sedatives, lower socioeconomic status and a history of opioid overdose have been reported as risk factors for opioid overdose; however, the magnitude of these associations and their credibility are unclear. We sought to identify predictors of fatal and nonfatal overdose from prescription opioids.

METHODS

We systematically searched MEDLINE, Embase, CINAHL, PsycINFO and Web of Science up to Oct. 30, 2022, for observational studies that explored predictors of opioid overdose after their prescription for chronic pain. We performed random-effects meta-analyses for all predictors reported by 2 or more studies using odds ratios (ORs) and 95% confidence intervals (CIs).

RESULTS

Twenty-eight studies (23 963 716 patients) reported the association of 103 predictors with fatal or nonfatal opioid overdose. Moderate- to high-certainty evidence supported large relative associations with history of overdose (OR 5.85, 95% CI 3.78-9.04), higher opioid dose (OR 2.57, 95% CI 2.08-3.18 per 90-mg increment), 3 or more prescribers (OR 4.68, 95% CI 3.57-6.12), 4 or more dispensing pharmacies (OR 4.92, 95% CI 4.35-5.57), prescription of fentanyl (OR 2.80, 95% CI 2.30-3.41), current substance use disorder (OR 2.62, 95% CI 2.09-3.27), any mental health diagnosis (OR 2.12, 95% CI 1.73-2.61), depression (OR 2.22, 95% CI 1.57-3.14), bipolar disorder (OR 2.07, 95% CI 1.77-2.41) or pancreatitis (OR 2.00, 95% CI 1.52-2.64), with absolute risks among patients with the predictor ranging from 2-6 per 1000 for fatal overdose and 4-12 per 1000 for nonfatal overdose.

INTERPRETATION

We identified 10 predictors that were strongly associated with opioid overdose. Awareness of these predictors may facilitate shared decision-making regarding prescribing opioids for chronic pain and inform harm-reduction strategies SYSTEMATIC REVIEW REGISTRATION: Open Science Framework (https://osf.io/vznxj/).

A Diagram of the Social-Ecological Conditions of Opioid Misuse and Overdose

The United States is experiencing a crisis of opioid misuse and overdose. To understand the underlying factors, researchers have begun looking upstream to identify social and structural determinants. However, no study has yet aggregated these into a comprehensive ecology of opioid overdose. We scoped 68 literature sources and compiled a master list of opioid misuse and overdose conditions. We grouped the conditions and used the Social Ecological Model to organize them into a diagram. We reviewed the diagram with nine subject matter experts (SMEs) who provided feedback on its content, design, and usefulness. From a literature search and SME interviews, we identified 80 unique conditions of opioid overdose and grouped them into 16 categories. In the final diagram, we incorporated 40 SME-recommended changes. In commenting on the diagram's usefulness, SMEs explained that the diagram could improve intervention planning by demonstrating the complexity of opioid overdose and highlighting structural factors. However, care is required to strike a balance between comprehensiveness and legibility. Multiple design formats may be useful, depending on the communication purpose and audience. This ecological diagram offers a visual perspective of the conditions of opioid overdose.

Dose Changes for Long-term Opioid Patients Following a State Opioid Prescribing Policy

BACKGROUND

In 2018, Nevada implemented opioid prescribing legislation (AB474) to support the uptake of CDC pain care guidelines. We studied the law's association with doses over threshold levels of morphine milligram equivalents (MMEs) and with time to dose increases and decreases, among long-term opioid patients.

METHODS

A difference-in-difference study examined dosing changes across opioid prescription episodes (ie, prescriptions within 30 day and within the same dosing threshold). Patients with at least 120 days supply over 6 months in Nevada and Colorado Medicaid pharmacy claims were included. Using a logistic regression model, we compare the predicted probabilities that opioid episodes exceeded 50 MME before and after implementation of the law, in both states. Adjusted hazard ratios (aHR) from a gap time survival model estimated time to escalate above 50 MME among low-dose episodes (<50 MME), and time to de-escalate below 50 MME among high-dose episodes (≥50 MME).

RESULTS

Among 453,577 episodes (74,292 patients), the Nevada law was associated with a 2.9% reduction in prescriptions over 50 MME (95% CI: -3.5, -2.3) compared with Colorado. While the law was also associated with slower escalation (Nevada: aHR = 0.75; 95% CI: 0.72, 0.77, Colorado: aHR = 1.04; 95% CI: 1.01, 1.06), it was also associated with slower de-escalation (Nevada: aHR = 0.87; 95% CI: 0.84, 0.89, Colorado: aHR = 0.97; 95% CI: 0.96, 0.99).

CONCLUSIONS

Slower dose escalations, rather than faster dose de-escalation, likely explain post-law reductions in doses over 50 MME. Slower dose de-escalations may be due to longer days supply post-policy.

Update of a Multivariable Opioid Overdose Risk Prediction Model to Enhance Clinical Care for Long-term Opioid Therapy Patients

BACKGROUND

Clinical opioid overdose risk prediction models can be useful tools to reduce the risk of overdose in patients prescribed long-term opioid therapy (LTOT). However, evolving overdose risk environments and clinical practices in addition to potential harmful model misapplications require careful assessment prior to widespread implementation into clinical care. Models may need to be tailored to meet local clinical operational needs and intended applications in practice.

OBJECTIVE

To update and validate an existing opioid overdose risk model, the Kaiser Permanente Colorado Opioid Overdose (KPCOOR) Model, in patients prescribed LTOT for implementation in clinical care.

DESIGN, SETTING, AND PARTICIPANTS

The retrospective cohort study consisted of 33, 625 patients prescribed LTOT between January 2015 and June 2019 at Kaiser Permanente Colorado, with follow-up through June 2021.

MAIN MEASURES

The outcome consisted of fatal opioid overdoses identified from vital records and non-fatal opioid overdoses from emergency department and inpatient settings. Predictors included demographics, medication dispensings, substance use disorder history, mental health history, and medical diagnoses. Cox proportional hazards regressions were used to model 2-year overdose risk.

KEY RESULTS

During follow-up, 65 incident opioid overdoses were observed (111.4 overdoses per 100,000 person-years) in the study cohort, of which 11 were fatal. The optimal risk model needed to risk-stratify patients and to be easily interpreted by clinicians. The original 5-variable model re-validated on the new study cohort had a bootstrap-corrected C-statistic of 0.73 (95% CI, 0.64-0.85) compared to a C-statistic of 0.80 (95% CI, 0.70-0.88) in the updated model and 0.77 (95% CI, 0.66-0.87) in the final adapted 7-variable model, which was also well-calibrated.

CONCLUSIONS

Updating and adapting predictors for opioid overdose in the KPCOOR Model with input from clinical partners resulted in a parsimonious and clinically relevant model that was poised for integration in clinical care.

Opioid Overdose Risk Following Hospital Discharge Among Individuals Prescribed Long-Term Opioid Therapy: a Risk Interval Analysis

BACKGROUND

Individuals prescribed long-term opioid therapy (LTOT) have increased risk of readmission and death after hospital discharge. The risk of opioid overdose during the immediate post-discharge time period is unknown.

OBJECTIVE

To examine the association between time since hospital discharge and opioid overdose among individuals prescribed LTOT.

DESIGN

Self-controlled risk interval analysis.

PARTICIPANTS

Adults prescribed LTOT with at least one hospital discharge at a safety-net health system and a non-profit healthcare organization in Colorado.

MAIN MEASURES

We identified individuals prescribed LTOT who were discharged from January 2006 through June 2019. The outcome was a composite of fatal and non-fatal opioid overdoses during a 90-day post-discharge observation period, identified using electronic health record (EHR) and vital statistics data. Risk intervals included days 0-6 after index and subsequent hospital discharges. Control intervals ranged from days 7 to 89 after index discharge and included all other time during the observation period that did not fall within a risk interval or time readmitted during a subsequent hospitalization, which was excluded. Poisson regression was used to estimate incidence rate ratios (IRR) and 95% confidence intervals (CI) for overdose events during risk in comparison to control intervals.

KEY RESULTS

We identified 7695 adults (63.3% over 55 years, 59.4% female, 20.3% Hispanic) who experienced 9499 total discharges during the study period. Twenty-one overdoses occurred during their observation periods (1174 per 100,000 person-years [9 in risk, 12 in control]). Overdose risk was significantly higher during the risk interval in comparison to the control interval (IRR 6.92; 95% CI 2.92-16.43).

CONCLUSION

During the first 7 days after hospital discharge, individuals prescribed LTOT appear to be at elevated risk for opioid overdose. Clarifying mechanisms of overdose risk may help inform in-hospital and post-discharge prevention strategies.

Long-term opioid therapy trajectories and overdose in patients with and without cancer

Objective

Pain is experienced by most patients with cancer and opioids are a cornerstone of management. Our objectives were (1) to identify patterns or trajectories of long-term opioid therapy (LTOT) and their correlates among patients with and without cancer and (2) to assess the association between trajectories and risk for opioid overdose, considering the potential moderating role of cancer.

Methods and Analysis

We conducted a retrospective cohort study among individuals in the US Veterans Health Administration (VHA) database with incident LTOT with and without cancer (N=44,351; N=285,772, respectively) between 2010-2017. We investigated the relationship between LTOT trajectory and all International Classification of Diseases-9 and 10-defined accidental and intentional opioid-related overdoses.

Results

Trajectories of opioid receipt observed in patients without cancer and replicated in patients with cancer were: low-dose/stable trend, low-dose/de-escalating trend, moderate-dose/stable trend, moderate-dose/escalating with quadratic downturn trend, and high-dose/escalating with quadratic downturn trend. Time to first overdose was significantly predicted by higher-dose and escalating trajectories; the two low-dose trajectories conferred similar, lower risk. Conditional hazard ratios (99% CI) for the moderate-dose, moderate-dose/escalating with quadratic downturn and high-dose/escalating with quadratic downturn trends were 1·84 (1·18, 2·85), 2·56 (1·54, 4·25), and 2·41 (1·37, 4·26), respectively. Effects of trajectories on time to overdose did not differ by presence of cancer; inferences were replicated when restricting to patients with stage 3/4 cancer.

Conclusion

Patients with cancer face opioid overdose risks like patients without cancer. Future studies should seek to expand and address our knowledge about opioid risk in cancer patients.

Trial registration

None.

Association Between Opioid Dose Reduction Rates and Overdose Among Patients Prescribed Long-Term Opioid Therapy

BACKGROUND

Tapering long-term opioid therapy is an increasingly common practice, yet rapid opioid dose reductions may increase the risk of overdose. The objective of this study was to compare overdose risk following opioid dose reduction rates of ≤10%, 11% to 20%, 21% to 30%, and >30% per month to stable dosing.

METHODS

We conducted a retrospective cohort study in three health systems in Colorado and Wisconsin. Participants were patients ≥18 years of age prescribed long-term opioid therapy between January 1, 2006, and June 30, 2019. Five opioid dosing patterns and drug overdoses (fatal and nonfatal) were identified using electronic health records, pharmacy records, and the National Death Index. Cox proportional hazard regression was conducted on a propensity score-weighted cohort to estimate adjusted hazard ratios (aHRs) for follow-up periods of 1, 3, 6, 9, and 12 months after a dose reduction.

RESULTS

In a cohort of 17 540 patients receiving long-term opioid therapy, 42.7% of patients experienced a dose reduction. Relative to stable dosing, a dose reduction rate of >30% was associated with an increased risk of overdose and the aHR estimates decreased as the follow-up increased; the aHRs for the 1-, 6- and 12-month follow-ups were 5.33 (95% CI, 1.98-14.34), 1.81 (95% CI,1.08-3.03), and 1.49 (95% CI, 0.97-2.27), respectively. The slower tapering rates were not associated with overdose risk.

CONCLUSIONS

Patients receiving long-term opioid therapy exposed to dose reduction rates of >30% per month had increased overdose risk relative to patients exposed to stable dosing. Results support the use of slow dose reductions to minimize the risk of overdose.

Risk Factors for Emergency Department Presentations after the Initiation of Opioid Analgesics in Non-Cancer Patients in Korea: A Nationwide Study

Background and Objectives: Opioid use in Korea is lower than in other developed countries. However, recent studies have reported an increase in opioid prescriptions and the number of chronic opioid users. The current status of adverse events (AEs) associated with opioid analgesics in Korea is unclear. This nested case–control study aimed to evaluate the influence of opioid analgesic use patterns on all emergency department (ED) visits and opioid-related ED visits after opioid analgesic initiation using the national claims database. Materials and Methods: Adult non-cancer patients who initiated non-injectable opioid analgesics (NIOA) between January 2017 and June 2018 were included. We defined the case group as patients who visited the ED within six months of opioid initiation, and the control group was selected in a 1:1 ratio using an exact matching method. Results: A total of 97,735 patients (13.58%) visited the ED within six months of NIOA initiation. Nearly 32% of cases were linked to opioid-related AEs. The most frequent AEs were falls and fractures (61.27%). After adjusting for covariates, opioid initiation at the ED was associated with all-cause or opioid-related ED visits (adjusted odds ratio (aOR) = 3.19, 95% confidence interval (CI) = 3.09–3.29; aOR = 3.82, 95% CI = 3.62–4.04, respectively). Chronic NIOA use was associated with all-cause and opioid-related ED visits (aOR = 1.32, 95% CI = 1.23–1.40; aOR = 1.56, 95% CI = 1.39–1.76, respectively). Conclusion: This study found that 13% of non-cancer patients visited the ED within six months of NIOA initiation. In addition, the NIOA use pattern was significantly associated with all-cause and opioid-related ED visits.

Association Between Opioid Tapering and Subsequent Health Care Use, Medication Adherence, and Chronic Condition Control

Importance

Opioid tapering has been associated with negative consequences, such as increased overdoses and mental health needs. Tapering could also alter use of health care services and worsen care of comorbid conditions through disruption in primary care.

Objective

To evaluate tapering of stable long-term opioid therapy (LTOT) and subsequent health care service use and chronic condition care.

Design, Setting, and Participants

A retrospective cohort study was conducted from January 1, 2008, to December 31, 2019. Data analysis was performed from July 9, 2020, to December 9, 2022. Data from the Optum Labs Data Warehouse, which contains deidentified retrospective administrative claims data and linked electronic health record data for commercial and Medicare Advantage enrollees, were used. Adults aged 18 years or older prescribed stable doses of LTOT at 50 morphine milligram equivalents or more per day during a 12-month baseline period were included, including subcohorts with hypertension or diabetes.

Exposures

Opioid tapering, with 15% or more relative reduction in mean daily dose in 6 overlapping periods during 6 months.

Main Outcomes and Measures

Emergency department visits, hospitalizations, primary care and specialist visits, antihypertensive or antiglycemic medication adherence, and blood pressure and hemoglobin A1c levels during up to 12 months' follow-up. Covariates included sociodemographic characteristics, comorbidities, health care use, and chronic condition control.

Results

Among 113 604 patients (60 764 [53.5%] women; mean [SD] age, 58.1 [11.8] years) prescribed LTOT, 41 207 had hypertension and 23 335 had diabetes; in all cohorts, approximately half were women, and half were aged 50 to 65 years. In the overall cohort, tapering was associated with more emergency department visits (adjusted incidence rate ratio [aIRR], 1.19; 95% CI, 1.16-1.21) and hospitalizations (aIRR, 1.16; 95% CI, 1.12-1.20), with similar magnitude associations in the hypertension and diabetes subcohorts. Tapering was associated with fewer primary care visits in the overall cohort (aIRR, 0.95; 95% CI, 0.94-0.96) and hypertension subcohort (aIRR, 0.98; 95% CI, 0.97-0.99). For the hypertension or diabetes subcohorts, tapering was associated with reduced medication adherence (hypertension: aIRR, 0.60; 95% CI, 0.59-0.62; diabetes: aIRR, 0.69; 95% CI, 0.67-0.71) and small increases in diastolic blood pressure and hemoglobin A1c level.

Conclusions and Relevance

In this cohort study of patients prescribed LTOT, opioid tapering was associated with more emergency department visits and hospitalizations, fewer primary care visits, and reduced antihypertensive and antidiabetic medication adherence. These outcomes may represent unintended negative consequences of opioid tapering for policy makers and clinicians to consider.

Discontinuation and tapering of prescribed opioids and risk of overdose among people on long-term opioid therapy for pain with and without opioid use disorder in British Columbia, Canada: A retrospective cohort study

BACKGROUND

The overdose crisis in North America has prompted system-level efforts to restrict opioid prescribing for chronic pain. However, little is known about how discontinuing or tapering prescribed opioids for chronic pain shapes overdose risk, including possible differential effects among people with and without concurrent opioid use disorder (OUD). We examined associations between discontinuation and tapering of prescribed opioids and risk of overdose among people on long-term opioid therapy for pain, stratified by diagnosed OUD and prescribed opioid agonist therapy (OAT) status.

METHODS AND FINDINGS

For this retrospective cohort study, we used a 20% random sample of residents in the provincial health insurance client roster in British Columbia (BC), Canada, contained in the BC Provincial Overdose Cohort. The study sample included persons aged 14 to 74 years on long-term opioid therapy for pain (≥90 days with ≥90% of days on therapy) between October 2014 and June 2018 (n = 14,037). At baseline, 7,256 (51.7%) persons were female, the median age was 55 years (quartile 1-3: 47-63), 227 (1.6%) persons had been diagnosed with OUD (in the past 3 years) and recently (i.e., in the past 90 days) been prescribed OAT, and 483 (3.4%) had been diagnosed with OUD but not recently prescribed OAT. The median follow-up duration per person was 3.7 years (quartile 1-3: 2.6-4.0). Marginal structural Cox regression with inverse probability of treatment weighting (IPTW) was used to estimate the effect of prescribed opioid treatment for pain status (discontinuation versus tapered therapy versus continued therapy [reference]) on risk of overdose (fatal or nonfatal), stratified by the following groups: people without diagnosed OUD, people with diagnosed OUD receiving OAT, and people with diagnosed OUD not receiving OAT. In marginal structural models with IPTW adjusted for a range of demographic, prescription, comorbidity, and social-structural exposures, discontinuing opioids (i.e., ≥7-day gap[s] in therapy) was associated with increased overdose risk among people without OUD (adjusted hazard ratio [AHR] = 1.44; 95% confidence interval [CI] 1.12, 1.83; p = 0.004), people with OUD not receiving OAT (AHR = 3.18; 95% CI 1.87, 5.40; p < 0.001), and people with OUD receiving OAT (AHR = 2.52; 95% CI 1.68, 3.78; p < 0.001). Opioid tapering (i.e., ≥2 sequential decreases of ≥5% in average daily morphine milligram equivalents) was associated with decreased overdose risk among people with OUD not receiving OAT (AHR = 0.31; 95% CI 0.14, 0.67; p = 0.003). The main study limitations are that the outcome measure did not capture overdose events that did not result in a healthcare encounter or death, medication dispensation may not reflect medication adherence, residual confounding may have influenced findings, and findings may not be generalizable to persons on opioid therapy in other settings.

CONCLUSIONS

Discontinuing prescribed opioids was associated with increased overdose risk, particularly among people with OUD. Prescribed opioid tapering was associated with reduced overdose risk among people with OUD not receiving OAT. These findings highlight the need to avoid abrupt discontinuation of opioids for pain. Enhanced guidance is needed to support prescribers in implementing opioid therapy tapering strategies with consideration of OUD and OAT status.

CDC Clinical Practice Guideline for Prescribing Opioids for Pain - United States, 2022

This guideline provides recommendations for clinicians providing pain care, including those prescribing opioids, for outpatients aged ≥18 years. It updates the CDC Guideline for Prescribing Opioids for Chronic Pain - United States, 2016 (MMWR Recomm Rep 2016;65[No. RR-1]:1-49) and includes recommendations for managing acute (duration of <1 month), subacute (duration of 1-3 months), and chronic (duration of >3 months) pain. The recommendations do not apply to pain related to sickle cell disease or cancer or to patients receiving palliative or end-of-life care. The guideline addresses the following four areas: 1) determining whether or not to initiate opioids for pain, 2) selecting opioids and determining opioid dosages, 3) deciding duration of initial opioid prescription and conducting follow-up, and 4) assessing risk and addressing potential harms of opioid use. CDC developed the guideline using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework. Recommendations are based on systematic reviews of the scientific evidence and reflect considerations of benefits and harms, patient and clinician values and preferences, and resource allocation. CDC obtained input from the Board of Scientific Counselors of the National Center for Injury Prevention and Control (a federally chartered advisory committee), the public, and peer reviewers. CDC recommends that persons with pain receive appropriate pain treatment, with careful consideration of the benefits and risks of all treatment options in the context of the patient's circumstances. Recommendations should not be applied as inflexible standards of care across patient populations. This clinical practice guideline is intended to improve communication between clinicians and patients about the benefits and risks of pain treatments, including opioid therapy; improve the effectiveness and safety of pain treatment; mitigate pain; improve function and quality of life for patients with pain; and reduce risks associated with opioid pain therapy, including opioid use disorder, overdose, and death.

Opioid Dose Trajectories and Associations With Mortality, Opioid Use Disorder, Continued Opioid Therapy, and Health Plan Disenrollment

IMPORTANCE

Uncertainty remains about the longer-term benefits and harms of different opioid management strategies, such as tapering and dose escalation. For instance, opioid tapering could help patients reduce opioid exposure to prevent opioid use disorder, but patients may also seek care elsewhere and engage in nonprescribed opioid use.

OBJECTIVE

To evaluate the association between opioid dose trajectories observed in practice and patient outcomes.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study was conducted in 3 health systems in Colorado and Wisconsin. The study population included patients receiving long-term opioid therapy between 50 and 200 morphine milligram equivalents between August 1, 2014, and July 31, 2017. Follow-up ended on December 31, 2019. Data were analyzed from January 2020 to August 2022.

EXPOSURES

Group-based trajectory modeling identified 5 dosing trajectories over 1 year: 1 decreasing, 1 high-dose increasing, and 3 stable.

MAIN OUTCOMES AND MEASURES

Primary outcomes assessed after the trajectory period were 1-year all-cause mortality, incident opioid use disorder, continued opioid therapy at 1 year, and health plan disenrollment. Associations were tested using Cox proportional hazards regression and log-binomial models, adjusting for baseline covariates.

RESULTS

A total of 3913 patients (mean [SD] age, 59.2 [14.4] years; 2767 White non-Hispanic [70.7%]; 2237 female patients [57.2%]) were included in the study. Compared with stable trajectories, the decreasing dose trajectory was negatively associated with opioid use disorder (adjusted hazard ratio [aHR], 0.40; 95% CI, 0.29-0.55) and continued opioid therapy (site 1: adjusted relative risk [aRR], 0.39; 95% CI, 0.34-0.44), but was positively associated with health plan disenrollment (aHR, 1.66; 95% CI, 1.24-2.22). The decreasing trajectory was not associated with mortality (aHR, 1.28; 95% CI, 0.87-1.86). In contrast, the high-dose increasing trajectory was positively associated with mortality (aHR, 2.19; 95% CI, 1.44-3.32) and opioid use disorder (aHR, 1.81; 95% CI, 1.39-2.37) but was not associated with disenrollment (aHR, 0.90; 95% CI, 0.56-1.42) or continued opioid therapy (site 1: aRR, 0.98; 95% CI, 0.94-1.03).

CONCLUSIONS AND RELEVANCE

In this cohort study, decreasing opioid dose was associated with reduced risk of opioid use disorder and continued opioid therapy but increased risk of disenrollment compared with stable dosing, whereas the high-dose increasing trajectory was associated with an increased risk of mortality and opioid use disorder. These findings can inform opioid management decision-making.

Randomised, pragmatic, waitlist controlled trial of cannabis added to prescription opioid support on opioid dose reduction and pain in adults with chronic non-cancer pain: study protocol

INTRODUCTION

Chronic, non-cancer pain impacts approximately 50 million adults in the USA (20%), approximately 25% of whom receive chronic prescription opioids for pain despite limited empirical efficacy data and strong dose-related risk for opioid use disorder and opioid overdose. Also despite lack of efficacy data, there are many reports of people using cannabis products to manage chronic pain and replace or reduce chronic opioids. Here we describe the protocol for a randomised trial of the effect of cannabis, when added to a behavioural pain management and prescription opioid taper support programme, on opioid utilisation, pain intensity and pain interference.

METHODS

This is a pragmatic, single-blind, randomised, wait-list controlled trial that aims to enrol 250 adults taking prescription opioids at stable doses of ≥25 morphine milligram equivalents per day for chronic non-cancer pain who express interest in using cannabis to reduce their pain, their opioid dose or both. All participants will be offered a weekly, 24-session Prescription Opioid Taper Support group behavioural pain management intervention. Participants will be randomly assigned in 1:1 ratio to use cannabis products, primarily from commercial cannabis dispensaries or to abstain from cannabis use for 6 months. Coprimary outcomes are change in prescription monitoring programme-verified opioid dose and change in Pain, Enjoyment, General Activity scale scores. Secondary outcomes include quality of life, depression, anxiety, self-reported opioid dose and opioid and cannabis use disorder symptoms. All other outcomes will be exploratory. We will record adverse events.

ETHICS AND DISSEMINATION

This study has ethical approval by the Massachusetts General Brigham Institutional Review Board (#2021P000871). Results will be published in peer-reviewed journals and presented at national conferences.

TRIAL REGISTRATION NUMBER

NCT04827992.

Long-term Risk of Overdose or Mental Health Crisis After Opioid Dose Tapering

IMPORTANCE

Patients prescribed long-term opioid therapy are increasingly undergoing dose tapering. Recent studies suggest that tapering is associated with short-term risks of substance misuse, overdose, and mental health crisis, although lower opioid dose could reduce risks of adverse events over the longer term.

OBJECTIVE

To assess the longer-term risks of overdose or mental health crisis associated with opioid dose tapering.

DESIGN, SETTING, AND PARTICIPANTS

This is a cohort study using an exposure-crossover analysis. Data were obtained from the OptumLabs Data Warehouse, which includes deidentified medical and pharmacy claims and enrollment records for commercial insurance and Medicare Advantage enrollees, representing a diverse mixture of ages, races, ethnicities, and geographical regions across the US. Participants were US adults who underwent opioid dose tapering from 2008 to 2017 after a 12-month baseline period of stable daily dosing of 50 morphine milligram equivalents or higher and who had at least 1 month of long-term follow-up during a postinduction period beginning 12 months after taper initiation. Data analysis was performed from October 2021 to April 2022.

EXPOSURES

Opioid tapering, defined as 15% or more relative reduction in mean daily dose during any of 6 overlapping 60-day windows within a 7-month follow-up period after the stable baseline period.

MAIN OUTCOMES AND MEASURES

Emergency or hospital encounters for drug overdose or withdrawal and mental health crisis (depression, anxiety, or suicide attempt). Outcome counts were assessed in pretaper and postinduction periods (from 12 to 24 months after taper initiation).

RESULTS

The study included 21 515 tapering events among 19 377 patients with a mean (SD) of 9.1 (2.7) months of postinduction follow-up per event (median [IQR], 10 [8-11] months). Patients had a mean (SD) age of 56.9 (11.2) years, 11 581 (53.8%) were female, and 8217 (38.2%) had commercial insurance (vs Medicare Advantage). In conditional negative binomial regression analyses, adjusted incidence rate ratios for the postinduction period compared with the pretaper period were 1.57 (95% CI, 1.42-1.74) for overdose or withdrawal and 1.52 (95% CI, 1.35-1.71) for mental health crisis.

CONCLUSIONS AND RELEVANCE

These findings suggest that opioid tapering was associated with increased rates of overdose, withdrawal, and mental health crisis extending up to 2 years after taper initiation.

Dose tapering, increases, and discontinuity among patients on long-term high-dose opioid therapy in the United States, 2017-2019

BACKGROUND

While reduced exposure to prescription opioids may decrease risks, including overdose and opioid use disorder, abrupt tapering or discontinuation may pose new risks.

OBJECTIVES

To examine potentially unsafe tapering and discontinuation among dosage changes in opioid prescriptions dispensed to US patients on high-dose long-term opioid therapy.

DESIGN

Longitudinal observational study of adults (≥18 years) on stable high-dose (≥50 oral morphine milligram equivalents [MME] daily dosage) long-term opioid therapy during a 180-day baseline and a 360-day follow-up using all-payer pharmaceutical claims data, 2017-2019.

MEASURES

Dosage tapering, increases, and/or stability during follow-up; sustained dosage stability, reductions, or discontinuation at the end of follow-up; and tapering rate. Patients could experience more than one outcome during follow-up.

RESULTS

Among 595,078 patients receiving high-dose long-term opioid therapy in the sample, 26.7% experienced sustained dosage reductions and 9.3% experienced discontinuation. Among patients experiencing tapering, 62.0% experienced maximum taper rates between > 10-40% reductions per month and 36.1% experienced monthly rates ≥ 40%. Among patients with mean baseline daily dosages ≥ 150 MME, 47.7% experienced a maximum taper rate ≥ 40% per month. Relative to baseline, 19.7% of patients experiencing tapering had long-term dosage reductions ≥ 40% per month at the end of follow-up.

IMPLICATIONS

Dosage changes for patients on high-dose long-term opioid therapy may warrant special attention, particularly over shorter intervals, to understand how potentially sudden tapering and discontinuation can be reduced while emphasizing patient safety and shared decision-making. Rapid discontinuation of opioids can increase risk of adverse outcomes including opioid withdrawal.

Risky alcohol use among patients dispensed opioid medications: A clinical community pharmacy study

BACKGROUND

Included among the significant risk factors for opioid overdose is concomitant use of other central nervous system depressants, particularly alcohol. Given the continued expansion of community pharmacy in the continuum of care, it is imperative to characterize alcohol use among pharmacy patients dispensed opioids in order to establish a foundation for identification and intervention in these settings.

METHODS

This secondary analysis utilized data from a one-time, cross-sectional health assessment conducted among patients dispensed opioid medications in 19 community pharmacies in Indiana and Ohio. Adult, English speaking, patients not receiving cancer care who were dispensed opioid medications were asked to self-report alcohol and substance use, behavioral and physical health, and demographic information. Descriptive and logistic regression analyses were employed to characterize alcohol use/risky alcohol use and patient characteristics associated therewith.

RESULTS

The analytical sample included 1494 individuals. Participants were on average 49 years of age (Standard Deviation=14.9)-with 6% being persons of color (n = 89). Weekly drinking was reported by 18.1% (n = 204) and daily drinking was reported by 6.8% (n = 77) of the study sample, with a total of 143 (9.6%) participants reporting moderate/high risk drinking. Males (Adjusted Odds Ratio [AOR]=1.94, 95% CI=1.3,2.9), those with higher pain interference (AOR=1.44, 95% CI=1.0,2.0), overdose history (AOR=1.93, 95% CI=1.1,3.5), sedative use (AOR=2.11, 95% CI=1.3,3.5), and tobacco use (AOR=2.41, 95% CI=1.6,3.7) had increased likelihood of moderate/high risk alcohol use (all p < 0.05).

CONCLUSIONS

Medication labeling and clinical guidelines clearly indicate that patients should abstain from concomitant use of opioids and alcohol. This study has identified rates and associated risk factors of risky alcohol use among a clinical sample of community pharmacy patients dispensed opioid medications. Continuing this line of research and potential clinical service development has the ability to improve patient safety through addressing a significant gap within the current opioid epidemic.

Modeling the population-level impact of opioid agonist treatment on mortality among people accessing treatment between 2001 and 2020 in New South Wales, Australia

BACKGROUND AND AIMS

The individual-level effectiveness of opioid agonist treatment (OAT) in reducing mortality is well established, but there is less evidence on population-level benefits. We use modeling informed with linked data from the OAT program in New South Wales (NSW), Australia, to estimate the impact of OAT provision in the community and prisons on mortality and the impact of eliminating excess mortality during OAT initiation/discontinuation.

DESIGN

Dynamic modeling.

SETTING AND PARTICIPANTS

A cohort of 49 359 individuals who ever received OAT in NSW from 2001 to 2018.

MEASUREMENTS

Receipt of OAT was represented through five stages: (i) first month on OAT, (ii) short (1-9 months) and (iii) longer (9+ months) duration on OAT, (iv) first month following OAT discontinuation and (v) rest of time following OAT discontinuation. Incarceration was represented as four strata: (i) never or not incarcerated in the past year, (ii) currently incarcerated, (iii) released from prison within the past month and (iv) released from prison 1-12 months ago. The model incorporated elevated mortality post-release from prison and OAT impact on reducing mortality and incarceration.

FINDINGS

Among the cohort, mortality was 0.9 per 100 person-years, OAT coverage and retention remained high (> 50%, 1.74 years/episode). During 2001-20, we estimate that OAT provision reduced overdose and other cause mortality among the cohort by 52.8% [95% credible interval (CrI) = 49.4-56.9%] and 26.6% (95% CrI =22.1-30.5%), respectively. We estimate 1.2 deaths averted and 9.7 life-years gained per 100 person-years on OAT. Prison OAT with post-release OAT-linkage accounted for 12.4% (95% CrI = 11.5-13.5%) of all deaths averted by the OAT program, primarily through preventing deaths in the first month post-release. Preventing elevated mortality during OAT initiation and discontinuation could have averted up to 1.4% (95% CrI =  0.8-2.0%) and 3.0% (95% CrI = 2.1-5.3%) of deaths, respectively.

CONCLUSION

The community and prison opioid agonist treatment program in New South Wales, Australia appears to have substantially reduced population-level overdose and all-cause mortality in the past 20 years, partially due to high retention.

Evaluating acceptability and feasibility of a mobile health intervention to improve self-efficacy in prescription opioid tapering in patients with chronic pain: protocol for a pilot randomised, single-blind, controlled trial

INTRODUCTION

Opioid medications are no longer recommended as long-term therapy for chronic non-cancer pain, and many patients are advised to reduce or discontinue opioid medications. Many patients report difficulties in tapering opioid medications, necessitating supporting interventions. This protocol describes a pilot randomised controlled trial (RCT) to investigate the acceptability, feasibility and potential efficacy of a mobile health intervention to improve the opioid tapering self-efficacy of patients with chronic non-cancer pain.

METHODS AND ANALYSIS

The trial will be a single-blind (clinician, data collector and statistician-blinded) pilot RCT with two parallel arms. Forty adult patients with chronic non-cancer pain who are voluntarily reducing their prescribed opioid medications under medical guidance will be recruited from two tertiary pain clinics (Start date 25 August 2021). Participants will be randomly assigned to an intervention or control group. Both groups will receive usual care, including multidisciplinary pain management. In addition to usual care, the intervention group will receive a short informational and testimonial video about opioid tapering and will receive two specifically text messages per day for 28 days. The intervention is codesigned with patients and clinicians to provide evidence-based informational, motivational and emotional support to patients with chronic pain to taper opioid medications. Feasibility of the intervention and a future definitive RCT will be evaluated by measuring patient acceptability, delivery of the intervention, rates and reasons of exclusions and drop-outs, completion rates and missing data in the study questionnaires, and obtaining estimates for sample size determination. Potential efficacy will be evaluated by comparing changes in opioid tapering self-efficacy between the two groups.

ETHICS AND DISSEMINATION

The study protocol was reviewed and approved by the Northern Sydney Local Health District (Australia). Study results will be published in peer-reviewed journals and presented at scientific and professional meetings.

TRIAL REGISTRATION NUMBER

ACTRN12621000795897.

Mental disorder and opioid overdose: a systematic review

PURPOSE

This systematic review summarizes and presents the current state of research quantifying the relationship between mental disorder and overdose for people who use opioids.

METHODS

The protocol was published in Open Science Framework. We used the PECOS framework to frame the review question. Studies published between January 1, 2000, and January 4, 2021, from North America, Europe, the United Kingdom, Australia, and New Zealand were systematically identified and screened through searching electronic databases, citations, and by contacting experts. Risk of bias assessments were performed. Data were synthesized using the lumping technique.

RESULTS

Overall, 6512 records were screened and 38 were selected for inclusion. 37 of the 38 studies included in this review show a connection between at least one aspect of mental disorder and opioid overdose. The largest body of evidence exists for internalizing disorders generally and mood disorders specifically, followed by anxiety disorders, although there is also moderate evidence to support the relationship between thought disorders (e.g., schizophrenia, bipolar disorder) and opioid overdose. Moderate evidence also was found for the association between any disorder and overdose.

CONCLUSION

Nearly all reviewed studies found a connection between mental disorder and overdose, and the evidence suggests that having mental disorder is associated with experiencing fatal and non-fatal opioid overdose, but causal direction remains unclear.

Abrupt Discontinuation From Long-Term Opioid Therapy in Massachusetts, 2015-2018

INTRODUCTION

In response to the opioid overdose crisis, providers were urged to taper and discontinue patients from long-term opioid therapy; however, abrupt discontinuation may lead to poor health outcomes. This study aims to determine abrupt and tapered discontinuation rates and identify the patient and provider characteristics associated with abrupt discontinuation.

METHODS

Data were from the Massachusetts Prescription Monitoring Program, 2015-2018. Patients discontinued from long-term opioid therapy were included in the analysis. Differences between abrupt and tapered discontinuations were identified with bivariate correlations, and variables independently associated with abrupt discontinuation were identified using multivariable Poisson regression analyses. Data were analyzed during 2019-2021.

RESULTS

In total, 277,485 patients experienced 359,320 discontinuations, of which 33.7% (n=120,964) were abrupt. Of all discontinuations, 55.7% were among female patients, and 57.9% were among patients aged >55 years. The ratio of abrupt to tapered discontinuations increased from 1:2.11 in 2015 to 1:1.75 in 2018. In bivariate analysis, prescribers with more patients receiving monthly opioid prescriptions were less likely to abruptly discontinue patients (29.0, IQR=13.9, 55.3 vs 18.8, IQR=5.84, 43.9, p<0.001), as were prescribers who wrote more monthly opioid prescriptions (36.0, IQR=16.8, 70.8 vs 25.4, IQR=7.40, 58.3, p<0.001). Multivariable results indicated that abrupt discontinuation was independently associated with male sex (RR=1.31, 95% CI=1.29, 1.1.32), younger age (RR=0.872, 95% CI=0.869, 0.874), greater distance between patient and prescriber (RR=1.0075, 95% CI=1.0072, 1.0078), and longer long-term opioid therapy duration (RR=1.021, 95% CI=1.021, 1.0122 for every month increase).

CONCLUSIONS

Among all long-term opioid therapy discontinuations, abrupt discontinuation is increasing. Evidence-based approaches to managing and tapering long-term opioid therapy are urgently needed.

Personal experience and awareness of opioid overdose occurrence among peers and willingness to administer naloxone in South Africa: findings from a three-city pilot survey of homeless people who use drugs

Background

Drug overdoses occur when the amount of drug or combination of drugs consumed is toxic and negatively affects physiological functioning. Opioid overdoses are responsible for the majority of overdose deaths worldwide. Naloxone is a safe, fast-acting opioid antagonist that can reverse an opioid overdose, and as such, it should be a critical component of community-based responses to opioid overdose. However, the burden of drug overdose deaths remains unquantified in South Africa, and both knowledge about and access to naloxone is generally poor. The objective of this study was to describe the experiences of overdose, knowledge of responses to overdose events, and willingness to call emergency medical services in response to overdose among people who use drugs in Cape Town, Durban, and Pretoria (South Africa).

Methods

We used convenience sampling to select people who use drugs accessing harm reduction services for this cross-sectional survey from March to July 2019. Participants completed an interviewer-administered survey, assessing selected socio-demographic characteristics, experiences of overdose among respondents and their peers, knowledge about naloxone and comfort in different overdose responses. Data, collected on paper-based tools, were analysed using descriptive statistics and categorised by city.

Results

Sixty-six participants participated in the study. The median age was 31, and most (77%) of the respondents were male. Forty-one per cent of the respondents were homeless. Heroin was the most commonly used drug (79%), and 82% of participants used drugs daily. Overall, 38% (25/66) reported overdosing in the past year. Most (76%, 50/66) knew at least one person who had ever experienced an overdose, and a total of 106 overdose events in peers were reported. Most participants (64%, 42/66) had not heard of naloxone, but once described to them, 73% (48/66) felt comfortable to carry it. More than two-thirds (68%, 45/66) felt they would phone for medical assistance if they witnessed an overdose.

Conclusion

Drug overdose was common among participants in these cities. Without interventions, high overdose-related morbidity and mortality is likely to occur in these contexts. Increased awareness of actions to undertake in response to an overdose (calling for medical assistance, using naloxone) and access to naloxone are urgently required in these cities. Additional data are needed to better understand the nature of overdose in South Africa to inform policy and responses.

Impact of transitioning from long-term to intermittent opioid therapy on the development of opioid-related adverse outcomes: A retrospective cohort study

BACKGROUND

Increasing pressures exist to reduce or discontinue opioid use among patients currently on long-term opioid therapy (LTOT). It is essential to understand the potential effects of opioid reduction.

METHODS

This retrospective cohort study was conducted among veterans with chronic pain and on LTOT. Using 1:1 propensity score-matched samples of veterans switching to intermittent opioid therapy and those continuing LTOT, we examined the development of subsequent substance use disorders (SUD composite; individual SUD types: opioid, non-opioid drug, and alcohol use disorders) and opioid-related adverse outcomes (ORAO composite; individual ORAO types: accidents resulting in wounds/injuries, opioid-related and alcohol/non-opioid medication-related accidents and overdoses, self-inflicted and violence-related injuries). Sensitivity analyses were conducted using logistic regression with stabilized inverse probability of treatment weighting (SIPTW) and instrumental variable (IV) models.

RESULTS

A total of 29,293 veterans switching to intermittent therapy were matched to veterans continuing LTOT. With matched samples, no differences were found in composite SUDs and ORAOs between the groups. With SIPTW, veterans switching to intermittent opioid therapy had higher odds of composite SUDs and ORAOs (SUDs aOR=1.12, 95%CI: 1.07,1.17; ORAOs aOR=1.05, 95%CI:1.00,1.09). IV models found lower risks for composite SUDs and ORAOs among veterans switching to intermittent opioid therapy (SUDs: β = -0.38, 95%CI:-0.63,-0.13; ORAOs: β = -0.27, 95%CI:-0.50,-0.04).

CONCLUSIONS

There were no consistent associations between transitioning patients from LTOT to intermittent opioid therapy and the risk of SUDs and ORAOs.

Impact of changes in opioid funding and clinical policies on rapid tapering of opioids in Ontario, Canada

ABSTRACT

Reports have emerged of abrupt tapering among recipients of long-term prescription opioids to conform new prescribing guidelines. We conducted a population-based, repeated cross-sectional time-series study among very high-dose (≥200 MME) opioid recipients in Ontario, Canada, to examine changes in the monthly prevalence of rapid tapering from 2014 to 2018, defined as recipients experiencing either a ≥50% reduction in daily doses or abrupt discontinuation sustained for 30 days. Interventional autoregressive integrated moving average models were used to test for significant changes following key guidelines and drug policies and programs. A sensitivity analysis examined rapid tapering sustained for 90 days. The monthly prevalence of rapid tapering events was stable from January 2014 to September 2016 (average monthly prevalence: 1.4%) but increased from 1.4% in October 2016 to 1.8% in April 2017 (P = 0.001), coincident with Ontario's Fentanyl Patch-for-Patch Return Program implementation. Transient spikes in the prevalence of rapid tapering also occurred 2 months after Ontario's delisting of publicly funded high-strength opioids and the release of updated Canadian Opioid Prescribing Guideline for Chronic Pain, reaching 2.3% in March 2017 and July 2017, respectively. However, this prevalence decreased to 1.2% in December 2018 (P < 0.0001). Although the prevalence of abrupt opioid discontinuation was lower, similar trends were observed. Our sensitivity analysis examining long-lasting rapid tapering found similar trends but lower prevalence, with no changes in complete discontinuation. These temporary increases in rapid tapering events highlight the need for improved communication and evidence-based resources for prescribers to minimize negative consequences of evolving policies and guidelines.

The Status and Prescription Patterns of Opioid Utilization in a Large Comprehensive Teaching Hospital in China According to the Anatomical Therapeutic Chemical Classification/Defined Daily Dose Methodology

BACKGROUND

Few studies have analyzed opioid consumption and the average daily dose and duration for different patients in hospital settings in China. The aim of this study was to measure the status of and trends in prescribed opioids and the prescribing patterns at the Second Xiangya Hospital.

METHODS

The data were obtained from the prescribed medicine database of the inpatient department. We included patients who were >18 years old and received any level of opioid analgesic between 2012 and 2017. The international Anatomical Therapeutic Chemical Classification/Defined Daily Dose (ATC/DDD) methodology was used to standardize the consumption rates. All opioid units were converted into morphine equivalents (MEs) to analyze the specific opioid usage.

RESULTS

The consumption of prescribed opioids increased from 3.16 to 3.74 DDD/100 bed-days (+18.3%) from 2012 to 2017. Both cancer and noncancer patients had similar administration routes and median daily dosages in MEs, but cancer patients had longer treatment durations (median: 5 days vs. 1 day, respectively). The median average daily dose and treatment duration for all patients were 15 MEs/day and 2 days, respectively, for oral administration, 100 MEs/day and 1 day for parenteral administration, and 47.14 MEs/day and 5 days for both oral and parenteral administration.

CONCLUSION

Although there was a tendency toward an increase in opioid consumption, the overall level of consumption in the Second Xiangya Hospital remained relatively low. Thus, it is urgently necessary to increase the availability of opioids and alter prescription habits for them in order adopt the current concept of pain management developed by the World Health Organization (WHO).

Compulsivity and impulsivity in opioid dependence

OBJECTIVE

Chronic exposure to illicit opioid drugs can cause serious health and social problems. However, less is known about the differential effect of various opioid treatments, such as methadone and buprenorphine, on neurocognitive domains such as compulsivity and impulsivity, despite their relevance to the treatment of opioid dependence.

METHODS

A total of 186 participants were recruited with a cross-sectional design: i) illicit heroin users (n = 27), ii) former heroin users stabilized on methadone MMT (n = 48), iii) a buprenorphine maintenance treatment (BMT) group (n = 18), iv) an abstinent (ABS) group with a history of opioid dependence who were previously stabilized on MMT or BMT (n = 29) and v) healthy controls (HC) (n = 64). We used the Intra-Extra Dimensional Shift (IED) and Cambridge Gambling Task (CGT) paradigms for measuring compulsivity and impulsivity constructs respectively.

RESULTS

Heightened compulsivity persisted in the heroin, buprenorphine and abstinent groups. Heroin, methadone and buprenorphine groups exhibited impaired behavioral responses to feedback, consisting of increased deliberation time and poorer risk adjustment. Higher compulsivity measures were negatively associated with opioid dose which may reflect sedation effects.

CONCLUSIONS

Our results suggest that compulsivity and impulsivity are core neurocognitive dimensions for opioid dependence which differ in their presentation according to the stage of treatment. Participants taking higher morphine equivalent doses performed better in compulsivity measures. These findings have implications for the treatment of opioid dependence and longitudinal studies are warranted.

Risk Factors Associated With Nonfatal Opioid Overdose Leading to Intensive Care Unit Admission: A Cross-sectional Study

BACKGROUND

Opioid overdose (OD) and related deaths have significantly increased in the United States over the last 2 decades. Existing studies have mostly focused on demographic and clinical risk factors in noncritical care settings. Social and behavioral determinants of health (SBDH) are infrequently coded in the electronic health record (EHR) and usually buried in unstructured EHR notes, reflecting possible gaps in clinical care and observational research. Therefore, SBDH often receive less attention despite being important risk factors for OD. Natural language processing (NLP) can alleviate this problem.

OBJECTIVE

The objectives of this study were two-fold: First, we examined the usefulness of NLP for SBDH extraction from unstructured EHR text, and second, for intensive care unit (ICU) admissions, we investigated risk factors including SBDH for nonfatal OD.

METHODS

We performed a cross-sectional analysis of admission data from the EHR of patients in the ICU of Beth Israel Deaconess Medical Center between 2001 and 2012. We used patient admission data and International Classification of Diseases, Ninth Revision (ICD-9) diagnoses to extract demographics, nonfatal OD, SBDH, and other clinical variables. In addition to obtaining SBDH information from the ICD codes, an NLP model was developed to extract 6 SBDH variables from EHR notes, namely, housing insecurity, unemployment, social isolation, alcohol use, smoking, and illicit drug use. We adopted a sequential forward selection process to select relevant clinical variables. Multivariable logistic regression analysis was used to evaluate the associations with nonfatal OD, and relative risks were quantified as covariate-adjusted odds ratios (aOR).

RESULTS

The strongest association with nonfatal OD was found to be drug use disorder (aOR 8.17, 95% CI 5.44-12.27), followed by bipolar disorder (aOR 2.69, 95% CI 1.68-4.29). Among others, major depressive disorder (aOR 2.57, 95% CI 1.12-5.88), being on a Medicaid health insurance program (aOR 2.26, 95% CI 1.43-3.58), history of illicit drug use (aOR 2.09, 95% CI 1.15-3.79), and current use of illicit drugs (aOR 2.06, 95% CI 1.20-3.55) were strongly associated with increased risk of nonfatal OD. Conversely, Blacks (aOR 0.51, 95% CI 0.28-0.94), older age groups (40-64 years: aOR 0.65, 95% CI 0.44-0.96; >64 years: aOR 0.16, 95% CI 0.08-0.34) and those with tobacco use disorder (aOR 0.53, 95% CI 0.32-0.89) or alcohol use disorder (aOR 0.64, 95% CI 0.42-1.00) had decreased risk of nonfatal OD. Moreover, 99.82% of all SBDH information was identified by the NLP model, in contrast to only 0.18% identified by the ICD codes.

CONCLUSIONS

This is the first study to analyze the risk factors for nonfatal OD in an ICU setting using NLP-extracted SBDH from EHR notes. We found several risk factors associated with nonfatal OD including SBDH. SBDH are richly described in EHR notes, supporting the importance of integrating NLP-derived SBDH into OD risk assessment. More studies in ICU settings can help health care systems better understand and respond to the opioid epidemic.

An Italian Expert Consensus on the Use of Opioids for the Management of Chronic Non-Oncological Pain in Clinical Practice: Focus on Buprenorphine

Purpose

The aim of the present work was to evaluate the knowledge and prescriptive habits of clinicians involved in the management of chronic non cancer pain (CNCP), with a special focus on the use of opioids.

Methods

A Delphi method was used. A Board of specialists elaborated and discussed a series of statements, based on available literature and personal clinical expertise, about particularly controversial topics on pain pathophysiology and treatment. A Panel of experts in the field of pain management, selected by the Board, was invited to vote the proposed statements, indicating the level of agreement on a 5-point Likert scale (1: strongly disagree; 2: disagree; 3: partially agree; 4: agree; 5: strongly agree). The threshold for consensus was set at minimum 66.6% of the number of respondents with a level of agreement ≥4 (Agree or Strongly agree).

Results

The Board included 5 pain therapists, 1 pharmacologist and 1 methodology expert and drew up a total of 36 statements (for a total of 40 requested answers)”. A total of 100 clinicians were included in the Expert Panel. Respondents were 89 (89%). Consensus was achieved for 32 out of 40 answers. Most of the lack of consensus was recorded for statements regarding opioids use, and resulted from a low level of agreement (3 on the Likert scale), suggesting a neutral position deriving from a lack of knowledge rather than a strong contrary opinion.

Conclusion

Most of the proposed items reached consensus, suggesting a generally homogeneous approach to CNCP management. However, the lack of consensus recorded for several items regarding opioid use confirms the need to fill important gaps in the knowledge of available agents. A clear explanation of the peculiar pharmacological properties of drugs associated with potential clinical advantages (such as buprenorphine) will help optimize pain treatment in both primary care and hospital settings and improving pain control in CNCP patients.

Assessing opioid overdose risk: a review of clinical prediction models utilizing patient-level data

Drug, and specifically opioid-related, overdoses remain a major public health problem in the United States. Multiple studies have examined individual risk factors associated with overdose risk, but research developing clinical risk prediction tools for overdose has only emerged in the last few years. We conducted a comprehensive review of the literature on patient-level factors associated with opioid-related overdose risk, with an emphasis on clinical risk prediction models for opioid-related overdose in the United States. Studies that developed and/or validated clinical prediction models were closely reviewed and evaluated to determine the state of the field. We identified 12 studies that reported risk prediction models for opioid-related overdose risk. Published models were developed from a variety of data sources, including Veterans Health Administration data, Medicare data, commercial insurance data, and statewide linked datasets. Studies reported model performance using measures of discrimination, usually at good-to-excellent levels, though they did not always assess calibration. C-statistics were better for models that included clinical predictors (c-statistics: 0.75-0.95) compared to models without them (c-statistics: 0.69-0.82). External validation of models was rare, and we found no studies evaluating implementation of models or risk prediction tools into clinical practice. A common feature of these models was a high rate of false positives, largely because opioid-related overdose is rare in the general population. Thus, efforts to implement prediction models into practice should take into account that published models overestimate overdose risk for many low-risk patients. Future prediction models assessing overdose risk should employ external validation and address model calibration. In order to translate findings from prediction models into clinical public health benefit, future studies should focus on developing clinical prediction tools based on prediction models, implementing these tools into clinical practice, and evaluating the impact of these models on treatment decisions, patient outcomes, and, ultimately, opioid overdose rates.

'First Do No Harm': physician discretion, racial disparities and opioid treatment agreements

The increasing use of opioid treatment agreements (OTAs) has prompted debate within the medical community about ethical challenges with respect to their implementation. The focus of debate is usually on the efficacy of OTAs at reducing opioid misuse, how OTAs may undermine trust between physicians and patients and the potential coercive nature of requiring patients to sign such agreements as a condition for receiving pain care. An important consideration missing from these conversations is the potential for racial bias in the current way that OTAs are incorporated into clinical practice and in the amount of physician discretion that current opioid guidelines support. While the use of OTAs has become mandatory in some states for certain classes of patients, physicians are still afforded great leeway in how these OTAs are implemented in clinical practice and how their terms should be enforced. This paper uses the guidelines provided for OTA implementation by the states of Indiana and Pennsylvania as case studies in order to argue that giving physicians certain kinds of discretion may exacerbate racial health disparities. This problem cannot simply be addressed by minimising physician discretion in general, but rather by providing mechanisms to hold physicians accountable for how they treat patients on long-term opioid therapy to ensure that such treatment is equitable.

High-Risk Opioid Prescribing Trends: Prescription Drug Monitoring Program Data From 2010 to 2018

OBJECTIVE

Deaths due to opioids have continued to increase in South Carolina, with 816 opioid-involved overdose deaths reported in 2018, a 9% increase from the prior year. The objective of the current study is to examine longitudinal trends (quarter [Q] 1 2010 through Q4 2018) of opioid prescribing volume and high-risk opioid prescribing behaviors in South Carolina using comprehensive dispensing data available in the South Carolina Prescription Drug Monitoring Program (SC PDMP).

DESIGN

Retrospective analyses of SC PDMP data were performed using general linear models to assess quarterly time trends and change in rate of each outcome Q1 2010 through Q4 2018.

PARTICIPANTS

Opioid analgesic prescription fills from SC state residents between Q1 2010 and Q4 2018.

MAIN OUTCOME MEASURES

High-risk prescribing behaviors included (1) opioid prescribing rate; (2) percentage of patients receiving opioids dispensed 90 or more average morphine milligram equivalents daily; (3) percentage of opioid prescribed days with overlapping opioid and benzodiazepine prescriptions; (4) rate per 100 000 residents of multiple provider episodes; and (5) percentage of patients prescribed extended release opioids who were opioid naive.

RESULTS

A total of 33 027 461 opioid prescriptions were filled by SC state residents within the time period of Q1 2010 through Q4 2018. A 41% decrease in the quarterly prescribing rate of opioids occurred from Q1 2010 to Q4 2018. The decrease in overall opioid prescribing was mirrored by significant decreases in all 4 high-risk prescribing behaviors.

CONCLUSION

PDMPs may represent the most complete data regarding the dispensing of opioid prescriptions and as such be valuable tools to inform and monitor the supply of licit opioids. Our results indicate that public health policy, legislative action, and multiple clinical interventions aimed at reducing high rates of opioid prescribing across the health care ecosystem appear to be succeeding in the state of South Carolina.

Comparative Effectiveness of Cognitive Behavioral Therapy for Chronic Pain and Chronic Pain Self-Management within the Context of Voluntary Patient-Centered Prescription Opioid Tapering: The EMPOWER Study Protocol

Objective. Evidence to date, while sparse, suggests that patients taking long-term opioids require special considerations and protections to prevent potential iatrogenic harms from opioid de-prescribing, such as increased pain or suffering. Following this study protocol, the EMPOWER study seeks to address multiple unmet needs of patients with chronic pain who desire to reduce long-term opioid therapy, and provide the clinical evidence on effective methodology. Methods. EMPOWER applies patient-centered methods for voluntary prescription opioid reduction conducted within a comprehensive, multi-state, 3-arm randomized controlled comparative effectiveness study of three study arms (1) group cognitive behavioral therapy for chronic pain; (2) group chronic pain self-management; and (3) usual care (taper only). Specialized electronic data capture systems collect patient reported symptoms and satisfaction data weekly and monthly during the taper, with real-time clinical alerts and electronic feedback loops informing, documenting, and steering needed care actions. Conclusion. The EMPOWER study seeks to provide granular evidence on patient response to voluntary opioid tapering, and will provide evidence to inform clinical systems changes, clinical care, patient satisfaction, and patient outcomes for opioid reduction.

Patterns of Prescription Opioid Use Prior to Self-reported Heroin Initiation

OBJECTIVES

To determine the association between self-reported heroin initiation and patterns of prescription opioid use.

METHODS

Using linked Oregon Medicaid, prescription drug monitoring program, and Treatment Episodes Data Set data, we conducted a case-control study of individuals reporting heroin initiation between 2015 and 2017 during treatment intake. Prescription drug monitoring program data provided prescription opioid use patterns, including long-term prescription opioid therapy, in the year before self-reported heroin initiation. Four controls were matched to each case on aggregate prescription opioid use and demographics.

RESULTS

About half (49%) of individuals who reported heroin initiation filled an opioid in the year before initiation. Individuals who initiated heroin (n = 306) were more likely to receive prescriptions from multiple prescribers (24% vs 18%, P = 0.007) and pharmacies (12% vs 5%, P < 0.001) compared with matched controls (n = 1224). Long-term opioid therapy (13% vs 14%, P = 0.74) was uncommon and did not differ between groups.

CONCLUSIONS

Although prescription opioid use commonly preceded self-reported heroin initiation, long-term opioid therapy was not common. Although this study did not find an association between opioid discontinuation and heroin initiation, sample size and follow-up limitations preclude definitive conclusions. Efforts to limit prescription opioids should continue to evaluate for unintended harms.

A Brief Screening Tool for Opioid Use Disorder: EMPOWER Study Expert Consensus Protocol

Growing concerns about the safety of long-term opioid therapy and its uncertain efficacy for non-cancer pain have led to relatively rapid opioid deprescribing in chronic pain patients who have been taking opioid for years. To date, empirically supported processes for safe and effective opioid tapering are lacking. Opioid tapering programs have shown high rates of dropouts and increases in patient distress and suicidal ideation. Therefore, safe strategies for opioid deprescribing that are more likely to succeed are urgently needed. In response to this demand, the EMPOWER study has been launched to examine the effectiveness of behavioral medicine strategies within the context of patient-centered opioid tapering in outpatient settings (https://empower.stanford.edu/). The EMPOWER protocol requires an efficient process for ensuring that collaborative opioid tapering would be offered to the most appropriate patients while identifying patients who should be offered alternate treatment pathways. As a first step, clinicians need a screening tool to identify patients with Opioid Use Disorder (OUD) and to assess for OUD severity. Because such a tool is not available, the study team composed of eight chronic pain and/or addiction experts has extended a validated screening instrument to develop a brief and novel consensus screening tool to identify OUD and assess for OUD severity for treatment stratification. Our screening tool has the potential to assist busy outpatient clinicians to assess OUD among patients receiving long-term opioid therapy for chronic pain.

Patient-centered prescription opioid tapering in community outpatients with chronic pain: 2- to 3-year follow-up in a subset of patients

Objective

We previously reported promising results for a 4-month patient-centered voluntary opioid tapering study. Key questions remain about the durability of effects and possible risks after opioid reduction. We provide the longest follow-up data to date for prospective opioid tapering: 2- to 3-year follow-up for pain intensity and daily opioid use in a subset of patients from our original 4-month opioid tapering study.

Methods

Twenty-three patients (44% of original sample) responded to contact attempts through telephone and reported their average pain intensity and current opioid use. Opioid doses were converted to morphine equivalent daily dose (MEDD). Data were analyzed within a repeated-measures model where time (baseline, 4 months, and 2-3 years) was the within-subject factor.

Results

Among reachable patients, the effect of time on change in MEDD from baseline to 4 months to 2 to 3 years was significant. Since baseline, 20 (95%) of the current sample reduced MEDD, and 15 (71%) further reduced MEDD at 2- to 3-year follow-up. There was no effect of time on change in pain intensity from baseline to 4 months to 2 to 3 years. Since baseline, 11 (52%) of the current sample reported pain reduction, and 12 (57%) reported reduced pain from the 4-month follow-up to the 2- to 3-year follow-up. Five (24%) reported increased pain intensity.

Conclusion

Study findings reveal continued MEDD reduction and enduring pain stability 2 to 3 years after a patient-centered voluntary opioid tapering program for a substantial fraction of patients. Notably, we were not able to verify current opioid use through medical records and were limited by self-report.

The Association between Opioid Discontinuation and Heroin Use: A Nested Case-Control Study

BACKGROUND

Opioid prescribing guidelines recommend reducing or discontinuing opioids for chronic pain if harms of opioid treatment outweigh benefits. As opioid discontinuation becomes more prevalent, it is important to understand whether opioid discontinuation is associated with heroin use. In this study, we sought to assess the association between opioid discontinuation and heroin use documented in the medical record.

METHODS

A matched nested case-control study was conducted in an integrated health plan and delivery system in Colorado. Patients receiving opioid therapy in the study period (January 2006-June 2018) were included. Opioid discontinuation was defined as ≥45 days with no opioids dispensed after initiating opioid therapy. The heroin use onset date represented the index date. Case patients were matched to up to 20 randomly selected patients without heroin use (control patients) by age, sex, calendar time, and time between initiating opioid therapy and the index date. Conditional logistic regression models estimated matched odds ratios (mOR) for the association between an opioid discontinuation prior to the index date and heroin use.

RESULTS

Among 22,962 patients prescribed opioid therapy, 125 patients (0.54%) used heroin after initiating opioid therapy, of which 74 met criteria for inclusion in the analysis. The odds of opioid discontinuation were approximately two times higher in case patients (n = 74) than control patients (n = 1045; mOR = 2.19; 95% CI 1.27-3.78).

CONCLUSIONS

Among patients prescribed chronic opioid therapy, the observed increased risk for heroin use associated with opioid discontinuation should be balanced with potential benefits.

All-cause mortality among males living with and without HIV initiating long-term opioid therapy, and its association with opioid dose, opioid interruption and other factors

BACKGROUND

While the relationship between long-term opioid therapy (LTOT) dose and overdose is well-established, LTOT's association with all-cause mortality is less understood, especially among people living with HIV (PLWH). There is also limited information regarding the association of LTOT cessation or interruption with mortality.

METHODS

Among PLWH and matched uninfected male veterans in care, we identified those who initiated LTOT. Using time-updated cox regression, we examined the association between all-cause mortality, unnatural death, and overdose, and opioid use categorized as 1-20 (reference group), 21-50, 51-90, and ≥ 91 mg morphine equivalent daily dose (MEDD).

RESULTS

There were 22,996 patients on LTOT, 6,578 (29 %) PLWH and 16,418 (71 %) uninfected. Among 5,222 (23 %) deaths, 12 % were unnatural deaths and 6 % overdoses. MEDD was associated with risk of all 3 outcomes; compared to patients on 1-20 mg MEDD, adjusted risk for all-cause mortality monotonically increased (Hazard Ratios (HR) [95 % CI] for 21-50 mg MEDD = 1.36 [1.21, 1.52], 51-90 mg MEDD = 2.06 [1.82, 2.35], and ≥ 91 mg MEDD = 3.03 [2.71, 3.39]). Similar results were seen in models stratified by HIV. LTOT interruption was also associated with all-cause, unnatural, and overdose mortality (HR [95 % CI] 2.30 [2.09, 2.53], 1.47 [1.13, 1.91] and 1.52 [1.04, 2.23], respectively).

CONCLUSIONS

Among PLWH and uninfected patients on LTOT we observed a strong dose-response relationship with all 3 mortality outcomes. Opioid risk mitigation approaches should be expanded to address the potential effects of higher dose on all-cause mortality in addition to unnatural and overdose fatalities.

Prescription Opioid Dispensing Patterns Prior to Heroin Overdose in a State Medicaid Program: a Case-Control Study

BACKGROUND

A large proportion of individuals who use heroin report initiating opioid use with prescription opioids. However, patterns of prescription opioid use preceding heroin-related overdose have not been described.

OBJECTIVE

To describe prescription opioid use in the year preceding heroin overdose.

DESIGN

Case-control study comparing prescription opioid use with a heroin-involved overdose, non-heroin-involved opioid overdose, and non-overdose controls from 2015 to 2017.

PARTICIPANTS

Oregon Medicaid beneficiaries with linked administrative claims, vital statistics, and prescription drug monitoring program data.

MAIN MEASURES

Opioid, benzodiazepine, and other central nervous system depressant prescriptions preceding overdose; among individuals with one or more opioid prescription, we assessed morphine milligram equivalents per day, overlapping prescriptions, prescriptions from multiple prescribers, long-term use, and discontinuation of long-term use.

KEY RESULTS

We identified 1458 heroin-involved overdoses (191 fatal) and 2050 non-heroin-involved opioid overdoses (266 fatal). In the 365 days prior to their overdose, 45% of individuals with a heroin-involved overdose received at least one prescribed opioid compared with 78% of individuals who experienced a non-heroin-involved opioid overdose (p < 0.001). For both heroin- and non-heroin-involved overdose cases, the likelihood of receiving an opioid increased with age. Among heroin overdose cases with an opioid dispensed, the rate of multiple pharmacy use was the only high-risk opioid pattern that was greater than non-overdose controls (adjusted odds ratio 3.2; 95% confidence interval 1.48 to 6.95). Discontinuation of long-term opioid use was not common prior to heroin overdose and not higher than discontinuation rates among non-overdose controls.

CONCLUSIONS

Although individuals with a heroin-involved overdose were less likely to receive prescribed opioids in the year preceding their overdose relative to non-heroin opioid overdose cases, prescription opioid use was relatively common and increased with age. Discontinuation of long-term prescription opioid use was not associated with heroin-involved overdose.