Long-term Prescription Opioid Use Research Articles

Pharmacokinetics-Informed Neural Network for Predicting Opioid Administration Moments with Wearable Sensors.

Long-term and high-dose prescription opioid use places individuals at risk for opioid misuse, opioid use disorder (OUD), and overdose. Existing methods for monitoring opioid use and detecting misuse rely on self-reports, which are prone to reporting bias, and toxicology testing, which may be infeasible in outpatient settings. Although wearable technologies for monitoring day-to-day health metrics have gained significant traction in recent years due to their ease of use, flexibility, and advancements in sensor technology, their application within the opioid use space remains underexplored. In the current work, we demonstrate that oral opioid administrations can be detected using physiological signals collected from a wrist sensor. More importantly, we show that models informed by opioid pharmacokinetics increase reliability in predicting the timing of opioid administrations. Forty-two individuals who were prescribed opioids as a part of their medical treatment in-hospital and after discharge were enrolled. Participants wore a wrist sensor throughout the study, while opioid administrations were tracked using electronic medical records and self-reports. We collected 1,983 hours of sensor data containing 187 opioid administrations from the inpatient setting and 927 hours of sensor data containing 40 opioid administrations from the outpatient setting. We demonstrate that a self-supervised pre-trained model, capable of learning the canonical time series of plasma concentration of the drug derived from opioid pharmacokinetics, can reliably detect opioid administration in both settings. Our work suggests the potential of pharmacokinetic-informed, data-driven models to objectively detect opioid use in daily life.

Patient perspectives on primary care providers role in long-term opioid therapy.

Over the past decade, long-term use of prescription opioids for chronic non-cancer pain (CNCP) has risen globally despite the associated risks. The majority of opioid users receive their first prescription in primary care. To investigate the perspective of long-term opioid users in primary care regarding the role of healthcare providers (HCP) in their prolonged opioid use. Semi-structured interviews in Dutch primary care Methods: We recruited long-term opioid users for CNCP from seven community pharmacies in the Netherlands. In-depth, semi-structured interviews focussed on experiences with long term opioid use, access to opioids, and the guidance of their HCPs. A directed content analysis was conducted on the transcribed interviews using NVivo. Participants (n=25) mentioned ways HCPs impacted their long-term use of opioids. These encompassed: 1) the initiation of treatment, 2) chronic use of opioids, 3) discontinuation of treatment. Participants stressed the need for risk counselling during initial prescriptions, ongoing medication evaluations including tapering conversations, and more support from their HCP during a tapering attempt. Patients' perspective illustrates the important role of HCPs across the spectrum of opioid usage - from initiation to tapering. It underscores the importance of clear risk counselling starting at the initial prescription, continuous medication assessments throughout treatment, addressing tapering at regular intervals and strong support during tapering. These insights carry significant implications for clinical practice, emphasising the importance of informed and patient-centred care when it comes to opioid use for chronic non-cancer pain management.

Analysis of physical activity and prescription opioid use among US adults: a cross-sectional study

BackgroundOpioid crisis has become a global concern, but whether physical activity (PA) can effectively reduce prescription opioid use remains unclear. The study aimed to examine the relationship of different domains of PA (e.g., occupation-related PA [OPA], transportation-related PA [TPA], leisure-time PA [LTPA]) with prescription opioid use and duration of prescription opioid use.MethodsThis cross-sectional study was conducted on 27,943 participants aged ≥ 18 years from National Health and Nutrition Examination Survey (NHANES, 2007– March 2020). We examined the relationship of different domains of PA with prescription opioid use and duration of prescription opioid use using multivariable logistic regression. Stratified analysis and a series of sensitivity analysis were used to elevate robustness. All analyses were conducted using appropriate sampling weights.ResultsOf the 27,943 participants, the mean age was 45.10 years, with 14,018 [weighted, 50.0%] females and 11,045 [weighted, 66.0%] non-Hispanic White. After multivariable adjustment, inverse associations between PA and prescription opioid use were observed for sufficient (≥ 150 min/week) total PA (OR,0.68 95%CI [0.56–0.81]), TPA (OR,0.73 95%CI [0.58–0.92]), and LTPA (OR,0.60 95%CI [0.48–0.75]) compared with insufficient PA(< 150 min/week), but not for sufficient OPA (OR,0.93 95%CI [0.79–1.10]). In addition, the associations were dose-responsive, participants had 22–40%, 27–36%, and 26–47% lower odds of using prescription opioids depending on the duration of total PA, TPA, and LTPA, respectively. Nevertheless, the impact of PA on prescription opioid use varied by duration of opioid use. Sufficient total PA was associated with elevated odds of short-term use of prescription opioids (< 90 days). Comparatively, sufficient total PA, TPA, and LTPA had different beneficial effects on reducing long-term use of prescription opioids (≥ 90 days) depending on the strength of opioids.ConclusionsThis study demonstrated sufficient total PA, TPA, and LTPA were inversely associated with prescription opioid use and varied depending on the duration and strength of prescription opioid use. These findings highlight PA can provide policy guidance to address opioid crisis.

Relationships of Self-reported Opioid Use and Misuse and Pain Severity With Probable Major Depression Among Participants With Spinal Cord Injury

ObjectivesTo examine the relations of pain intensity, opioid use, and opioid misuse with depressive symptom severity and probable major depression (PMD) among participants with spinal cord injuries (SCI), controlling for demographic, injury, and socioeconomic characteristics. Study DesignCohort study. SettingMedical University in the Southeastern United States (US). ParticipantsParticipants (N=918) were identified from 1 of 2 sources including a specialty hospital and a state-based surveillance system in the Southeastern US. Participants were a minimum of 18 years old at enrollment and had SCI with non-complete recovery. Participants were on average 57.5 years old at the time of the study and an average of 24.4 years post SCI onset. InterventionsNot applicable. Main Outcome MeasuresParticipants completed a self-report assessment that included frequency of prescription opioid use and misuse, based on the National Survey on Drug Use and Health (NSDUH), and the PHQ – 9 to measure depressive symptom severity and PMD. ResultsOpioid use, opioid misuse, and pain intensity were related to elevated depressive symptom severity and higher odds of PMD. Non-Hispanic Blacks had fewer depressive symptoms and lower odds of PMD, as did those with higher incomes. Veterans had lower risk of PMD, whereas ambulatory participants had a higher risk of PMD. Age at SCI onset had a mixed pattern of significance, whereas years of education and years since injury were not significant. ConclusionsThe relation between pain intensity with depressive symptom severity and PMD was profound, consistent with the biopsychosocial model of pain. The greater risk of PMD and higher depressive symptom severity among those using opioids and misusing opioids raises further concern about long-term prescription opioid use. Alternative treatments are needed.

Characteristics of patients with non-cancer pain and long-term prescription opioid use who have used medical versus recreational marijuana

ObjectiveMarijuana use is increasingly common among patients with chronic non-cancer pain (CNCP) and long-term opioid therapy (LTOT). We determined if lifetime recreational and medical marijuana use were associated with more frequent and higher dose prescription opioid use.DesignCross-sectionalSubjectsEligible patients (n=1,037), who had a new period of prescription opioid use lasting 30-90 days, were recruited from two midwestern health care systems to a study of long-term prescription opioid use and mental health outcomes. The present cross-sectional analyses uses baseline data from this on-going cohort study.MethodsPrimary exposures were participant reported lifetime recreational and medical marijuana use versus no lifetime marijuana use. Prescription opioid characteristics included daily versus non-daily opioid use and ≥50 morphine milligram equivalent (MME) dose per day vs. <50 MME. Multivariate, logistic regression models estimated the association between lifetime recreational and medical marijuana use vs. no use and odds of daily and higher dose prescription opioid use, before and after adjusting for confounding.ResultsThe sample was an average of 54.9 (SD±11.3) years of age, 57.3% identified as female gender, 75.2% identified as White, and 22.5% identified as Black race. Among all participants, 44.4% were never marijuana users, 21.3% were recreational only, 7.7% medical only and 26.6% were both recreational and medical marijuana users. After controlling for all confounders, lifetime recreational marijuana use, as compared to no use, was significantly associated with increased odds of daily prescription opioid use (OR=1.61; 95%CI:1.02-2.54). There was no association between lifetime recreational or medical marijuana use and daily opioid dose.ConclusionLifetime medical marijuana use is not linked to current opioid dose, but lifetime recreational use is associated with more than a 60% odds of being a daily prescription opioid user. Screening for lifetime recreational marijuana use may identify patients with chronic pain who are vulnerable to daily opioid use which increases risk for adverse opioid outcomes. Prospective data is needed to determine how marijuana use influences the course of LTOT and vice versa.

A patient activation intervention in primary care for patients with chronic pain on long term opioid therapy: results from a randomized control trial

BackgroundGiven significant risks associated with long-term prescription opioid use, there is a need for non-pharmacological interventions for treating chronic pain. Activating patients to manage chronic pain has the potential to improve health outcomes. The ACTIVATE study was designed to evaluate the effectiveness of a 4-session patient activation intervention in primary care for patients on long-term opioid therapy.MethodsThe two-arm, pragmatic, randomized trial was conducted in two primary care clinics in an integrated health system from June 2015—August 2018. Consenting participants were randomized to the intervention (n = 189) or usual care (n = 187). Participants completed online and interviewer-administered surveys at baseline, 6- and 12- months follow-up. Prescription opioid use was extracted from the EHR. The primary outcome was patient activation assessed by the Patient Activation Measure (PAM). Secondary outcomes included mood, function, overall health, non-pharmacologic pain management strategies, and patient portal use. We conducted a repeated measure analysis and reported between-group differences at 12 months.ResultsAt 12 months, the intervention and usual care arms had similar PAM scores. However, compared to usual care at 12 months, the intervention arm demonstrated: less moderate/severe depression (odds ratio [OR] = 0.40, 95%CI 0.18–0.87); higher overall health (OR = 3.14, 95%CI 1.64–6.01); greater use of the patient portal’s health/wellness resources (OR = 2.50, 95%CI 1.42–4.40) and lab/immunization history (OR = 2.70, 95%CI 1.29–5.65); and greater use of meditation (OR = 2.72; 95%CI 1.61–4.58) and exercise/physical therapy (OR = 2.24, 95%CI 1.29–3.88). At 12 months, the intervention arm had a higher physical health measure (mean difference 1.63; 95%CI: 0.27–2.98).ConclusionThis trial evaluated the effectiveness of a primary care intervention in improving patient activation and patient-reported outcomes among adults with chronic pain on long-term opioid therapy. Despite a lack of improvement in patient activation, a brief intervention in primary care can improve outcomes such as depression, overall health, non-pharmacologic pain management, and engagement with the health system.Trial RegistrationThe study was registered on 10/27/14 on ClinicalTrials.gov (NCT02290223).

Baseline Characteristics From a New Longitudinal Cohort of Patients With Noncancer Pain and Chronic Opioid Use in the United States

Retrospective cohort studies have consistently observed that long-term prescription opioid use is a risk factor for new major depressive episodes. However, prospective studies are needed to confirm these findings and establish evidence for causation. The Prescription Opioids and Depression Pathways cohort study is designed for this purpose. The present report describes the baseline sample and associations between participant characteristics and odds of daily versus nondaily opioid use. Second, we report associations between participant characteristics and odds of depression, dysthymia, anhedonia, and vital exhaustion. Patients with noncancer pain were eligible if they started a new period of prescription opioid use lasting 30 to 90 days. Participants were 54.8 (standard deviation ± 11.3) years of age, 57.3% female and 73% White race. Less than college education was more common among daily versus nondaily opioid users (32.4% vs 27.3%; P = .0008), as was back pain (64.2% vs 51.3%; P < .0001), any nonopioid substance use disorder (12.8% vs 4.8%; P < .0001), and current smoking (30.7% vs 18.4% P < .0001). High pain interference (50.9% vs 28.4%; P < .0001) was significantly associated with depression, as was having more pain sites (6.9 ± 3.6 vs 5.7 ± 3.6; P < .0001), and benzodiazepine comedication (38.2% vs 23.4%; P < .0001). High pain interference was significantly more common among those with anhedonia (46.8% vs 27.4%; P < .0001), and more pain sites (7.0 ± 3.7 vs 5.6 ± 3.6; P < .0001) were associated with anhedonia. Having more pain sites (7.9 ± 3.6 vs 5.5 ± 3.50; P < .0001) was associated with vital exhaustion, as was back pain (71.9% vs 56.8%; P = .0001) and benzodiazepine comedication (42.8% vs 22.8%; P < .0001). Patients using prescription opioids for noncancer pain have complex pain, psychiatric, and substance use disorder comorbidities. Longitudinal data will reveal whether long-term opioid therapy leads to depression or other mood disturbances such as anhedonia and vital exhaustion. PerspectiveThis study reports baseline characteristics of a new prospective, noncancer pain cohort study. Risk factors for adverse opioid outcomes were most common in those with depression and vital exhaustion and less common in dysthymia and anhedonia. Baseline data highlight the complexity of patients receiving long-term opioid therapy for noncancer pain.

Persistent long-term opioid use after trauma: Incidence and risk factors.

The opioid epidemic in the United States continues to lead to a substantial number of preventable deaths and disability. The development of opioid dependence has been strongly linked to previous opioid exposure. Trauma patients are at particular risk since opioids are frequently required to control pain after injury. The purpose to this study was to examine the prevalence of opioid use before and after injury and to identify risk factors for persistent long-term opioid use after trauma. Records for all patients admitted to a Level 1 trauma center over a 1-year period were analyzed. Demographics, injury characteristics, and hospital course were recorded. A multistate Prescription Drug Monitoring Program database was queried to obtain records of all controlled substances prescribed from 6 months before the date of injury to 12 months after hospital discharge. Patients still receiving narcotics at 1 year were defined as persistent long-term users and were compared against those who were not. A total of 2,992 patients were analyzed. Of all patients, 20.4% had filled a narcotic prescription within the 6 months before injury, 53.5% received opioids at hospital discharge, and 12.5% had persistent long-term use after trauma with the majority demonstrating preinjury use. Univariate risk factors for long-term use included female sex, longer length of stay, higher Injury Severity Score, anxiety, depression, orthopedic surgeries, spine injuries, multiple surgical locations, discharge to acute inpatient rehab, and preinjury opioid use. On multivariate analysis, the only significant predictors of persistent long-term prescription opioid use were preinjury use and a much smaller effect associated with use at discharge. During a sustained opioid epidemic, concerns and caution are warranted in the use of prescription narcotics for trauma patients. However, persistent long-term opioid use among opioid-naive patients is rare and difficult to predict after trauma. Prognostic and Epidemiological; Level III.

478-P: Brain Volume Changes after Long-Term Opioid Treatment in Painful Diabetic Peripheral Neuropathy

Aim: Opioid medications are commonly used to treat Painful-Diabetic Peripheral Neuropathy (Painful-DPN). However, opioids are associated with significant adverse effects, including prescription opioid use disorder which has reached epidemic proportions in the United States. There is an urgent need to determine the effect of long-term opioid treatment (&amp;gt;6-months) on cerebral structure in Painful-DPN. Methods: A total of 56 participants with Painful-DPN were recruited (17 on long-term opioid treatment [O+] and 39 not on opioid treatment [O-]). Participants underwent detailed clinical and neurophysiological assessments and cerebral imaging (3T, Phillips Medical Systems, Holland). Brain morphometric analysis was performed using Freesurfer. Results: O+ participants were prescribed: codeine (n=3, 18%), tramadol (n=5, 29%), morphine modified release (n=1, 6%), buprenorphine (n=1, 6%), and combination treatment (n=5, 29%). O+ participants had a longer duration of diabetes, greater HbA1c, higher pain severity and higher scores on Hospital Anxiety and Depression scales compared to the O- group. Participants in the O+ group had a greater mean caudate volume (O+ 3.5mL ± 0.4; O- 3.2 ± 0.4mL, p=0.034); mean insula volume (O+ 6.3 ± 0.8; O- 5.9 ± 0.6, p=0.049) and mean insular vertices (O+ 3,286 ± 411; O- 3055 ± 282, p=0.018). Conclusion: This is the first study to examine the impact of long-term opioid use on cerebral structure in Painful-DPN. Our findings suggest that chronic opioid use may alter affective/attentional pain processing (insular cortex) and brain regions associated with binge/intoxication (caudate nucleus). These results may have important clinical implications for uncovering the effects of long-term prescription opioid use on brain structure in Painful-DPN. Clearer clinical utility will come from future longitudinal modelling of the prognostic characteristics of opioid use disorder from the neuroimaging features identified in this study. Disclosure G.P.Sloan: None. K.Teh: None. P.Shillo: None. S.Tesfaye: Advisory Panel; Bayer Inc., Wörwag Pharma GmbH &amp; Co. KG, Angelini, Speaker's Bureau; Viatris Inc., Nevro Corp., Procter &amp; Gamble, Novo Nordisk, Berlin-Chemie AG. D.Selvarajah: None. I.D.Wilkinson: None. Funding European Foundation for the Study of Diabetes; Novartis Knowledge Exchange Support Fund (X/162218); Efficacy and Mechanism Evaluation Programme (NIHR129921); Medical Research Council/National Institute for Health Research Partnership

Pathways into Opioid Dependence: Evidence from Practice Variation in Emergency Departments

We use practice variation across physicians to uncover the role of medical care in causing opioid dependence. Using health records of 2 million US veterans with emergency department visits, we find that quasi-random assignment to a top (versus bottom) decile prescribing provider significantly increases subsequent opioid use and misuse rates. Instrumental variable results show that opioid prescription receipt leads to a 20 percent increase in the probability of long-term prescription opioid use and sizable increases in the development of opioid use disorder and opioid overdose mortality. We find suggestive evidence of transition into illicit opioids due to prescription opioid exposure. (JEL I11, I12, I18)

Long-Term Prescription Opioid Use After Injury in Washington State 2015–2018

BackgroundPatients with injury may be at high risk of long-term opioid use due to the specific features of injury (e.g., injury severity), as well as patient, treatment, and provider characteristics that may influence their injury-related pain management. ObjectivesInform prescribing practices and identify high-risk populations through studying chronic prescription opioid use in the trauma population. MethodsUsing the Washington State All-Payer Claims Database (WA-APCD) data, we included adults aged 18–65 years with an incident injury from October 1, 2015–December 31, 2017. We compared patient, injury, treatment, and provider characteristics by whether or not the patients had long-term (≥ 90 days continuous prescription opioid use), or no opioid use after injury. ResultsWe identified 191,130 patients who met eligibility criteria and were included in our cohort; 5822 met criteria for long-term use. Most had minor injuries, with a median Injury Severity Score = 1, with no difference between groups. Almost all patients with long-term opioid use had filled an opioid prescription in the year prior to their injury (95.3%), vs. 31.3% in the no-use group (p < 0.001). Comorbidities associated with chronic pain, mental health, and substance use conditions were more common in the long-term than the no-use group. ConclusionAcross this large cohort of multiple, mostly minor, injury types, long-term opioid use was relatively uncommon, but almost all patients with chronic use post injury had preinjury opioid use. Long-term opioid use after injury may be more closely tied to preinjury chronic pain and pain management than acute care pain management.

CO56 Association of Long-Term Prescription Opioid Use with Advanced Stage Cancer at Diagnosis Among Older Cancer Survivors with Non-Cancer Chronic Pain Conditions (NCPCS)

Older adults have the highest prevalence of non-cancer chronic pain conditions (NCPCs) that are commonly treated with prescription opioids. Animal studies show that opioids may not only increase the risk of developing cancer but also stage of cancer. This study investigated the association of the long-term prescription opioid use (LTPOU) with stage of cancer diagnosis among older cancer survivors with any NCPC.

The impact of California wildfires on patient access to prescription opioids

BackgroundPatients on long-term opioid therapy are particularly vulnerable to disruptions in medication access, especially during traumatic and chaotic events such as wildfires and other natural disasters. ObjectivesTo determine whether past highly destructive California wildfires were associated with disrupted access to prescription opioids for patients receiving long-term, and therefore physically dependent on, opioid medications. MethodsUsing California prescription drug monitoring program data, this retrospective study selected patients with long-term prescription opioid use episodes residing in ZIP code tabulation areas impacted by either the Camp Fire or Tubbs Fire. Autoregressive integrated moving average time series models were fit to pre-fire data to forecast post-fire expected values and then compared with observed post-fire data, specifically for weekly proportions of long-term episodes with early fills, late fills, changes in patients’ prescriber and pharmacy, and fills within a different ZIP code tabulation area than the patient’s residence. ResultsAfter the Camp Fire, there were significant spikes in the proportions of early fills (peak at 56% of total, week 1 after fire), late fills (peak at 29%, week 6), and immediate significant increases in prescriber (peak at 37%, week 3) and pharmacy changes (peak at 71%, week 1) in high-impact ZIP code tabulation areas. Low-impact ZIP code tabulation areas experienced no similar disruptions. Disruptions due to the Tubbs Fire were far less severe. ConclusionAccess to prescription opioids was greatly disrupted for patients living in areas most impacted by the Camp Fire. Future research should explore effectiveness of current state and federal controlled substance prescribing policies to determine what improvements are needed to minimize disruptions in medication access due to wildfires and other natural disasters.

Depression and Long-Term Prescription Opioid Use and Opioid Use Disorder: Implications for Pain Management in Cancer.

Opinion statementPreventing depression in cancer patients on long-term opioid therapy should begin with depression screening before opioid initiation and repeated screening during treatment. In weighing the high morbidity of depression and opioid use disorder in patients with chronic cancer pain against a dearth of evidence-based therapies studied in this population, patients and clinicians are left to choose among imperfect but necessary treatment options. When possible, we advise engaging psychiatric and pain/palliative specialists through collaborative care models and recommending mindfulness and psychotherapy to all patients with significant depression alongside cancer pain. Medications for depression should be reserved for moderate to severe symptoms. We recommend escitalopram/citalopram or sertraline among selective serotonin reuptake inhibitors (SSRIs), or the serotonin and norepinephrine reuptake inhibitors (SNRIs) duloxetine, venlafaxine, or desvenlafaxine if patients have a significant component of neuropathic pain or fibromyalgia. Tricyclic antidepressants (TCAs) (consider nortriptyline or desipramine, which have better anticholinergic profiles) should be considered for patients who do not respond to or tolerate SSRI/SNRIs. Existing evidence is inadequate to definitively recommend methylphenidate or novel agents, such as ketamine or psilocybin, as adjunctive treatments for cancer-related depression and pain. Physicians who treat patients with cancer pain should utilize universal precautions to limit the risk of non-medical opioid use (non-medical opioid use). Patients should be screened for non-medical opioid use behaviors at initial consultation and at regular intervals during treatment using a non-judgmental approach that reduces stigma. Co-management with an addiction specialist may be indicated for patients at high risk of non-medical opioid use and opioid use disorder. Buprenorphine and methadone are indicated for the treatment of opioid use disorder, and while they have not been systematically studied for treatment of opioid use disorder in patients with cancer pain, they do provide analgesia for cancer pain. While an interdisciplinary team approach to manage psychological stress may be beneficial, this may not be possible for patients treated outside of comprehensive cancer centers.

Chronic Pain in Youth and Substance Misuse, Mental Illness, and Long-Term Prescription Opioid Use in Adulthood: A Retrospective Longitudinal Cohort Study

Chronic Pain in Youth and Substance Misuse, Mental Illness, and Long-Term Prescription Opioid Use in Adulthood: A Retrospective Longitudinal Cohort Study

A Risk Prediction Model for Long-term Prescription Opioid Use.

Tools are needed to aid clinicians in estimating their patients' risk of transitioning to long-term opioid use and to inform prescribing decisions. The objective of this study was to develop and validate a model that predicts previously opioid-naive patients' risk of transitioning to long-term use. This was a statewide population-based prognostic study. Opioid-naive (no prescriptions in previous 2 y) patients aged 12 years old and above who received a pill-form opioid analgesic in 2016-2018 and whose prescriptions were registered in the California Prescription Drug Monitoring Program (PDMP). A multiple logistic regression approach was used to construct a prediction model with long-term (ie, >90 d) opioid use as the outcome. Models were developed using 2016-2017 data and validated using 2018 data. Discrimination (c-statistic), calibration (calibration slope, intercept, and visual inspection of calibration plots), and clinical utility (decision curve analysis) were evaluated to assess performance. Development and validation cohorts included 7,175,885 and 2,788,837 opioid-naive patients with outcome rates of 5.0% and 4.7%, respectively. The model showed high discrimination (c-statistic: 0.904 for development, 0.913 for validation), was well-calibrated after intercept adjustment (intercept, -0.006; 95% confidence interval, -0.016 to 0.004; slope, 1.049; 95% confidence interval, 1.045-1.053), and had a net benefit over a wide range of probability thresholds. A model for the transition from opioid-naive status to long-term use had high discrimination and was well-calibrated. Given its high predictive performance, this model shows promise for future integration into PDMPs to aid clinicians in formulating opioid prescribing decisions at the point of care.

Long-term prescription opioid use among US military service members injured in combat.

During the Global War on Terrorism, many US Military service members sustained injuries with potentially long-lasting functional limitations and chronic pain. We sought to understand the patterns of prescription opioid use among service members injured in combat. We queried the Military Health System Data Repository to identify service members injured in combat between 2007 and 2011. Sociodemographics, injury characteristics, treatment information, and costs of care were abstracted for all eligible patients. We surveyed for prescription opioid utilization subsequent to hospital discharge and through 2018. Negative binomial regression was used to identify factors associated with cumulative prescription opioid use. We identified 3,981 service members with combat-related injuries presenting during the study period. The median age was 24 years (interquartile range [IQR], 22-29 years), 98.5% were male, and the median follow-up was 3.3 years. During the study period, 98% (n = 3,910) of patients were prescribed opioids at least once and were prescribed opioids for a median of 29 days (IQR, 9-85 days) per patient-year of follow-up. While nearly all patients (96%; n = 3,157) discontinued use within 6 months, 91% (n = 2,882) were prescribed opioids again after initially discontinuing opioids. Following regression analysis, patients with preinjury opioid exposure, more severe injuries, blast injuries, and enlisted rank had higher cumulative opioid use. Patients who discontinued opioids within 6 months had an unadjusted median total health care cost of US $97,800 (IQR, US $42,364-237,135) compared with US $230,524 (IQR, US $134,387-370,102) among those who did not discontinue opioids within 6 months (p < 0.001). Nearly all service members injured in combat were prescribed opioids during treatment, and the vast majority experienced multiple episodes of prescription opioid use. Only 4% of the population met the criteria for sustained prescription opioid use at 6 months following discharge. Early discontinuation may not translate to long-term opioid cessation in this population. Epidemiology study, level III.

Social vulnerability in persons with chronic hepatitis C virus infection is associated with a higher risk of prescription opioid use

Prescription opioid use (POU) is often a precursor to opioid use disorder (OUD) and subsequent consequences. Persons with chronic hepatitis C virus infection (CHC) may be at a higher risk of POU due to a higher comorbidity burden and social vulnerability factors. We sought to determine the burden of POU and associated risk factors among persons with CHC in the context of social vulnerability. We identified CHC persons and propensity-score matched HCV− controls in the electronically retrieved Cohort of HCV-Infected Veterans and determined the frequency of acute, episodic long-term and chronic long-term POU and the prevalence of social vulnerability factors among persons with POU. We used logistic regression analysis to determine factors associated with POU. Among 160,856 CHC and 160,856 propensity-score matched HCV-controls, acute POU was recorded in 38.4% and 38.0% (P = 0.01) respectively. Episodic long-term POU was recorded in 3.9% in each group (P = 0.5), while chronic long-term POU was recorded in 28.4% and 19.2% (P < 0.0001). CHC was associated with a higher risk of chronic long-term POU (OR 1.66, 95%CI 1.63, 1.69), but not with acute or episodic long-term POU. Black race, female sex and homelessness were associated with a higher risk of chronic long-term POU. Presence of ≥ 1 factor was associated with a higher risk of all POU patterns. Persons with CHC have more social vulnerability factors and a higher risk of chronic long-term POU. Presence of ≥ 1 social vulnerability factor is associated with a higher risk of POU. Downstream consequences of POU need further study.

Predictors of long-term use of prescription opioids in the community-dwelling population of adults without a cancer diagnosis: a retrospective cohort study

Background:Long-term opioid use is a known risk factor for opioid-related harms. We aimed to identify risk factors for and predictors of long-term use of prescription opioids in the community-dwelling population of adults without a diagnosis of cancer, to inform practice change at the point of care.Methods:Using Quebec administrative claims databases, we conducted a retrospective cohort study in a random sample of adult members (≥ 18 yr) of the public drug plan who did not have a cancer diagnosis and who initiated a prescription opioid in the outpatient setting between Jan. 1, 2012, and Dec. 31, 2016. The outcome of interest was long-term opioid use (≥ 90 consecutive days or ≥ 120 cumulative days over 12 mo). Potential predictors included sociodemographic factors, medical history, characteristics of the initial opioid prescription and prescriber’s specialty. We used multivariable logistic regression to assess the association between each characteristic and long-term use. We used the area under the receiver operating characteristic curve to determine the predictive performance of full and parsimonious models.Results:Of 124 664 eligible patients who initiated opioid therapy, 4172 (3.3%) progressed to long-term use of prescription opioids. The most important associated factors in the adjusted analysis were long-term prescription of acetaminophen–codeine (odds ratio [OR] 6.30, 95% confidence interval [CI] 4.99 to 7.96), prescription of a long-acting opioid at initiation (OR 6.02, 95% CI 5.31 to 6.84), initial supply of 30 days or more (OR 4.22, 95% CI 3.81 to 4.69), chronic pain (OR 2.41, 95% CI 2.16 to 2.69) and initial dose of at least 90 morphine milligram equivalents (MME) per day (OR 1.24, 95% CI 1.04 to 1.47). Our predictive model, including only the initial days’ supply and chronic pain diagnosis, had area under the curve of 0.7618.Interpretation:This study identified factors associated with long-term prescription opioid use. Limiting the initial supply to no more than 7 days and limiting doses to 90 MME/day or less are actions that could be undertaken at the point of care.

Patterns of Long-Term Prescription Opioid Use Among Older Adults in the United States: A Study of Medicare Administrative Claims Data

BACKGROUND: Long-term opioid therapy was prescribed with increasing frequency over the past decade. However, factors surrounding long-term use of opioids in older adults remains poorly understood, probably because older people are not at the center stage of the national opioid crisis. OBJECTIVES: To estimate the annual utilization and trends in long-term opioid use among older adults in the United States. STUDY DESIGN: Retrospective cohort study. SETTING: Data from Medicare-enrolled older adults. METHODS: This study utilized a nationally representative sample of Medicare administrative claims data from the years 2012 to 2016 containing records of health care services for more than 2.3 million Medicare beneficiaries each year. Medicare beneficiaries who were 65 years of age or older and who were enrolled in Medicare Parts A, B, and D, but not Part C, for at least 10 months in a year were included in the study. We measured annual utilization and trends in new long-term opioid use episodes over 4 years (2013–2016). We examined claims records for the demographic characteristics of the eligible individuals and for the presence of chronic non-cancer pain (CNCP), cancer, and other comorbidities. RESULTS: From 2013 to 2016, administrative claims of approximately 2.3 million elderly Medicare beneficiaries were analyzed in each year with a majority of them being women (~56%) and white (~82%) with a mean age of approximately 75 years. The proportion of all eligible beneficiaries with at least one new opioid prescription increased from 6.64% in 2013, peaked at 10.32% in 2015, and then decreased to 8.14% in 2016. The proportion of individuals with long-term opioid use among those with a new opioid prescription was 12.40% in 2013 and 10.20% in 2016. Among new long-term opioid users, the proportion of beneficiaries with a cancer diagnosis during the study years increased from 13.30% in 2013 to 15.67% in 2016, and the proportion with CNCP decreased from 30.25% in 2013 to 27.36% in 2016. Across all years, long-term opioid use was consistently high in the Southern states followed by the Midwest region. LIMITATIONS: This study used Medicare fee-for-service administrative claims data to capture prescription fill patterns, which do not allow for the capture of individuals enrolled in Medicare Advantage plans, cash prescriptions, or for the evaluation of appropriateness of prescribing, or the actual use of medication. This study only examined long-term use episodes among patients who were defined as opioid-naive. Finally, estimates captured for 2016 could only utilize data from 9 months of the year to capture 90-day long-term-use episodes. CONCLUSIONS: Using a national sample of elderly Medicare beneficiaries, we observed that from 2013 to 2016 the use of new prescription opioids increased from 2013 to 2014 and peaked in 2015. The use of new long-term prescription opioids peaked in 2014 and started to decrease from 2015 and 2016. Future research needs to evaluate the impact of the changes in new and long-term prescription opioid use on population health outcomes. KEY WORDS: Long-term, opioids, older adults, trends, Medicare, chronic non-cancer pain, cancer, cohort study