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BACKGROUND: The association between cost-sharing and receipt of medication for opioid use disorder (MOUD) is unknown. METHODS: We constructed a cohort of 10,513 commercially insured individuals with a new diagnosis of opioid use disorder (OUD) and information on insurance cost-sharing in a large national de-identified claims database. We examined four cost-sharing measures: 1) pharmacy deductible; 2) medical service deductible; 3) pharmacy medication co-pay; and 4) medical office co-pay. We measured MOUD (naltrexone, buprenorphine, or methadone) initiation (within 14 days of diagnosis), engagement (second receipt within 34 days of first), and 6-month retention (continuous receipt without 14-day gap). We used multivariable logistic regression to assess the association between cost-sharing and MOUD initiation, engagement, and retention. We calculated total out-of-pocket costs in the 30 days following MOUD initiation for each type of MOUD. RESULTS: Of 10,513 individuals with incident OUD, 1,202 (11%) initiated MOUD, 742 (7%) engaged, and 253 (2%) were retained in MOUD at six months. A high ($1,000+) medical deductible was associated with a lower odds of initiation compared to no deductible (odds ratio: 0.85, 95% CI: 0.74-0.98). We found no significant associations between other cost-sharing measures for initiation, engagement, or retention. Median initial 30-day out-of-pocket costs ranged from $100 for methadone to $710 for extended-release naltrexone. CONCLUSION: Among insurance plan cost-sharing measures, only medical services deductible showed an association with decreased MOUD initiation. Policy and benefit design should consider ways to reduce cost barriers to initiation and retention in MOUD.

Objectives. To examine trends in opioid overdose deaths by race/ethnicity from 2018 to 2019 across 67 HEALing Communities Study (HCS) communities in Kentucky, New York, Massachusetts, and Ohio. Methods. We used state death certificate records to calculate opioid overdose death rates per 100 000 adult residents of the 67 HCS communities for 2018 and 2019. We used Poisson regression to calculate the ratio of 2019 to 2018 rates. We compared changes by race/ethnicity by calculating a ratio of rate ratios (RRR) for each racial/ethnic group compared with non-Hispanic White individuals. Results. Opioid overdose death rates were 38.3 and 39.5 per 100 000 for 2018 and 2019, respectively, without a significant change from 2018 to 2019 (rate ratio = 1.03; 95% confidence interval [CI] = 0.98, 1.08). We estimated a 40% increase in opioid overdose death rate for non-Hispanic Black individuals (RRR = 1.40; 95% CI = 1.22, 1.62) relative to non-Hispanic White individuals but no change among other race/ethnicities. Conclusions. Overall opioid overdose death rates have leveled off but have increased among non-Hispanic Black individuals. Public Health Implications. An antiracist public health approach is needed to address the crisis of opioid-related harms. (Am J Public Health. 2021;111(10):1851–1854. https://doi.org/10.2105/AJPH.2021.306431 )

Urine drug testing (UDT) is a recommended risk mitigation strategy for patients prescribed opioids for chronic pain, but evidence that UDT supports identification of substance misuse is limited. Identify the prevalence of UDT results that may identify substance misuse, including diversion, among patients prescribed opioids for chronic pain. Retrospective cohort study. Patients (n=638) receiving opioids for chronic pain who had one or more UDTs, examining up to eight substances per sample, during a one 1-year period. Experts adjudicated the clinical concern that UDT results suggest substance misuse or diversion as not concerning, uncertain, or concerning. Of 638 patients, 48% were female and 49% were over age 55 years. Patients had a median of three UDTs during the intervention year. We identified 37% of patients (235/638) with ≥1 concerning UDT and a further 35% (222/638) having ≥1 uncertain UDT. We found concerning UDTs due to non-detection of a prescribed substance in 24% (156/638) of patients and detection of a non-prescribed substance in 23% (147/638). Compared to patients over 65 years, those aged 18–34 years were more likely to have concerning UDT results with an adjusted odds ratio (AOR) of 4.8 (95% confidence interval [CI] 1.9–12.5). Patients with mental health diagnoses (AOR 1.6 [95% CI 1.1–2.3]) and substance use diagnoses (AOR 2.3 [95% CI 1.5–3.7]) were more likely to have a concerning UDT result. Expert adjudication of UDT results identified clinical concern for substance misuse in 37% of patients receiving opioids for chronic pain. Further research is needed to determine if UDTs impact clinical practice or patient-related outcomes.

People with mental illnesses and people living in poverty have higher rates of incarceration than others, but relatively little is known about the long-term impact that incarceration has on an individual's mental health later in life.To evaluate prior incarceration's association with mental health at midlife.Retrospective cohort study PARTICIPANTS: Participants from the National Longitudinal Survey of Youth 1979 (NLSY79)-a nationally representative age cohort of individuals 15 to 22 years of age in 1979-who remained in follow-up through age 50.Midlife mental health outcomes were measured as part of a health module administered once participants reached 50 years of age (2008-2019): any mental health history, any depression history, past-year depression, severity of depression symptoms in the past 7 days (Center for Epidemiologic Studies Depression [CES-D] scale), and mental health-related quality of life in the past 4 weeks (SF-12 Mental Component Score [MCS]). The main exposure was any incarceration prior to age 50.Among 7889 participants included in our sample, 577 (5.4%) experienced at least one incarceration prior to age 50. Prior incarceration was associated with a greater likelihood of having any mental health history (predicted probability 27.0% vs. 16.6%; adjusted odds ratio [aOR] 1.9 [95%CI: 1.4, 2.5]), any history of depression (22.0% vs. 13.3%; aOR 1.8 [95%CI: 1.3, 2.5]), past-year depression (16.9% vs. 8.6%; aOR 2.2 [95%CI: 1.5, 3.0]), and high CES-D score (21.1% vs. 15.4%; aOR 1.5 [95%CI: 1.1, 2.0]) and with a lower (worse) SF-12 MCS (-2.1 points [95%CI: -3.3, -0.9]; standardized mean difference -0.24 [95%CI: -0.37, -0.10]) at age 50, when adjusting for early-life demographic, socioeconomic, and behavioral factors.Prior incarceration was associated with worse mental health at age 50 across five measured outcomes. Incarceration is a key social-structural driver of poor mental health.

Background Opioid-related overdose mortality has remained at crisis levels across the United States, increasing 5-fold and worsened during the COVID-19 pandemic. The ability to provide forecasts of opioid-related mortality at granular geographical and temporal scales may help guide preemptive public health responses. Current forecasting models focus on prediction on a large geographical scale, such as states or counties, lacking the spatial granularity that local public health officials desire to guide policy decisions and resource allocation. Objective The overarching objective of our study was to develop Bayesian spatiotemporal dynamic models to predict opioid-related mortality counts and rates at temporally and geographically granular scales (ie, ZIP Code Tabulation Areas [ZCTAs]) for Massachusetts. Methods We obtained decedent data from the Massachusetts Registry of Vital Records and Statistics for 2005 through 2019. We developed Bayesian spatiotemporal dynamic models to predict opioid-related mortality across Massachusetts’ 537 ZCTAs. We evaluated the prediction performance of our models using the one-year ahead approach. We investigated the potential improvement of prediction accuracy by incorporating ZCTA-level demographic and socioeconomic determinants. We identified ZCTAs with the highest predicted opioid-related mortality in terms of rates and counts and stratified them by rural and urban areas. Results Bayesian dynamic models with the full spatial and temporal dependency performed best. Inclusion of the ZCTA-level demographic and socioeconomic variables as predictors improved the prediction accuracy, but only in the model that did not account for the neighborhood-level spatial dependency of the ZCTAs. Predictions were better for urban areas than for rural areas, which were more sparsely populated. Using the best performing model and the Massachusetts opioid-related mortality data from 2005 through 2019, our models suggested a stabilizing pattern in opioid-related overdose mortality in 2020 and 2021 if there were no disruptive changes to the trends observed for 2005-2019. Conclusions Our Bayesian spatiotemporal models focused on opioid-related overdose mortality data facilitated prediction approaches that can inform preemptive public health decision-making and resource allocation. While sparse data from rural and less populated locales typically pose special challenges in small area predictions, our dynamic Bayesian models, which maximized information borrowing across geographic areas and time points, were used to provide more accurate predictions for small areas. Such approaches can be replicated in other jurisdictions and at varying temporal and geographical levels. We encourage the formation of a modeling consortium for fatal opioid-related overdose predictions, where different modeling techniques could be ensembled to inform public health policy.

Understanding the factors associated with where people who use opioids live, where their fatal overdoses occur, and where deaths are recorded can improve our knowledge of local risk environments and inform intervention planning. Through geospatial analyses of death certificate data between 2015 and 2017, we found that a majority of opioid-involved fatal overdoses in Massachusetts occurred at home. Age (adjusted odds ratio [AOR], 1.03; 95% confidence interval [CI], 1.02-1.04), living in a census tract with a higher percentage of crowded households (AOR, 1.04; 95% CI, 1.01-1.08), households without vehicles (AOR, 1.01; 95% CI, 1.00-1.02), and Hispanic ethnicity (AOR, 0.56; 95% CI, 0.42-0.74) were independently associated with fatal overdose at home. Using geographically weighted regression, we identified locations where these associations were stronger and could benefit most from home-based and culturally sensitive overdose prevention efforts, including expanded overdose education and naloxone distribution.

BACKGROUND Relative costs of care among treatment options for opioid use disorder (OUD) are unknown. METHODS We identified a cohort of 40,885 individuals with a new diagnosis of OUD in a large national de-identified claims database covering commercially insured and Medicare Advantage enrollees. We assigned individuals to 1 of 6 mutually exclusive initial treatment pathways: (1) Inpatient Detox/Rehabilitation Treatment Center; (2) Behavioral Health Intensive, intensive outpatient or Partial Hospitalization Services; (3) Methadone or Buprenorphine; (4) Naltrexone; (5) Behavioral Health Outpatient Services, or; (6) No Treatment. We assessed total costs of care in the initial 90 day treatment period for each strategy using a differences in differences approach controlling for baseline costs. RESULTS Within 90 days of diagnosis, 94.8% of individuals received treatment, with the initial treatments being: 15.8% for Inpatient Detox/Rehabilitation Treatment Center, 4.8% for Behavioral Health Intensive, Intensive Outpatient or Partial Hospitalization Services, 12.5% for buprenorphine/methadone, 2.4% for naltrexone, and 59.3% for Behavioral Health Outpatient Services. Average unadjusted costs increased from $3250 per member per month (SD $7846) at baseline to $5047 per member per month (SD $11,856) in the 90 day follow-up period. Compared with no treatment, initial 90 day costs were lower for buprenorphine/methadone [Adjusted Difference in Differences Cost Ratio (ADIDCR) 0.65; 95% confidence interval (CI), 0.52-0.80], naltrexone (ADIDCR 0.53; 95% CI, 0.42-0.67), and behavioral health outpatient (ADIDCR 0.54; 95% CI, 0.44-0.66). Costs were higher for inpatient detox (ADIDCR 2.30; 95% CI, 1.88-2.83). CONCLUSION Improving health system capacity and insurance coverage and incentives for outpatient management of OUD may reduce health care costs.

OBJECTIVES: To determine how commonly medical inpatients with opioid use disorder (OUD) referred for post-acute medical care were rejected due to substance use or treatment with opioid agonist therapy (OAT). Additionally, to assess for changes in rejection rates following the United States Attorney’s May 2018 settlement with a Massachusetts nursing facility for violating anti-discrimination laws for such rejections. METHODS: We linked electronic referrals to private Massachusetts post-acute medical care facilities from Boston Medical Center in 2018 with clinical data. We included referrals with evidence of OUD using ICD-10 diagnosis codes or OAT receipt. We identified the frequency of referrals where the stated rejection reason was substance use or OAT and classified these as discriminatory. We used segmented regression to assess for changes in proportion of referrals with substance use and OAT-related rejections before and after the settlement. RESULTS: In 2018, 219 OUD-associated hospitalizations resulted in 1648 referrals to 285 facilities; 81.8% (1348) were rejected. Among hospitalizations, 37.4% (82) received at least one discriminatory rejection. Among rejections, 15.1% (203) were discriminatory (105 for OAT and 98 for substance use). Among facilities, 29.1% (83) had at least one discriminatory rejection. We found no differences in proportion of discriminatory rejections before and after the settlement. CONCLUSIONS: Individuals hospitalized with OUD frequently experience explicit discrimination when rejected from post-acute care despite federal and state protections. Efforts are needed to enhance enforcement of anti-discrimination laws, regulations, and policies to ensure access to post-acute medical care for people with OUD and ongoing medical needs.

IMPORTANCE: Vitamin D deficiency is associated with chronic pain syndromes and higher opioid use among cancer patients, but its association with opioid use among opioid-naïve subjects following a major surgical procedure with acute pain has not been explored. OBJECTIVE: To determine the association between serum 25-hydroxyvitamin D (25(OH)D) levels, opioid use, and opioid use disorder. METHODS: We identified commercially insured subjects aged 18–64 years with available perioperative serum 25-hydroxyvitamin D (25D) levels who underwent one of nine major surgical procedures in 2000–2014. Primary outcomes were dose and duration of opioid use measured using pharmacy claims. Secondary outcome was opioid use disorder captured using diagnosis codes. Multivariable negative binomial models with generalized estimating equations were performed examining the association between 25D levels and postoperative opioid use measures, adjusting for age, sex, race/ethnicity, Charlson score, education, income, latitude, and season of blood draw. Adjusted Cox regression was used to examine the association with opioid use disorder. RESULTS: Among 5446 subjects, serum 25(OH)D was sufficient (≥ 20 ng/mL) among 4349 (79.9%) subjects, whereas 837 (15.4%) had insufficient (12 to

Background and aim Medically managed opioid withdrawal (detox) can increase the risk of subsequent opioid overdose. We assessed the association between mortality following detox and receipt of medications for opioid use disorder (MOUD) and residential treatment after detox. Design Cohort study generated from individually linked public health data sets. Setting Massachusetts, USA. Participants A total of 30 681 opioid detox patients with 61 819 detox episodes between 2012 and 2014. Measurements Treatment categories included no post-detox treatment, MOUD, residential treatment or both MOUD and residential treatment identified at monthly intervals. We classified treatment exposures in two ways: (a) 'on-treatment' included any month where a treatment was received and (b) 'with-discontinuation' individuals were considered exposed through the month following treatment discontinuation. We conducted multivariable Cox proportional hazards analyses and extended Kaplan-Meier estimator cumulative incidence for all-cause and opioid-related mortality for the treatment categories as monthly time-varying exposure variables. Findings Twelve months after detox, 41% received MOUD for a median of 3 months, 35% received residential treatment for a median of 2 months and 13% received both for a median of 5 months. In on-treatment analyses for all-cause mortality compared with no treatment, adjusted hazard ratios (AHR) were 0.34 [95% confidence interval (CI) = 0.27-0.43] for MOUD, 0.63 (95% CI = 0.47-0.84) for residential treatment and 0.11 (95% CI = 0.03-0.43) for both. In with-discontinuation analyses for all-cause mortality, compared with no treatment, AHRs were 0.52 (95% CI = 0.42-0.63) for MOUD, 0.76 (95% CI = 0.59-0.96) for residential treatment and 0.21 (95% CI = 0.08-0.55) for both. Results were similar for opioid-related overdose mortality. Conclusions Among people who have undergone medically managed opioid withdrawal, receipt of medications for opioid use disorder, residential treatment or the combination of medications for opioid use disorder and residential treatment were associated with substantially reduced mortality compared with no treatment.

IMPORTANCE: Opioid-related mortality and national prescribing guidelines have led to tapering of doses among patients prescribed long-term opioid therapy for chronic pain. There is limited information about risks related to tapering, including overdose and mental health crisis. OBJECTIVE: To assess whether there are associations between opioid dose tapering and rates of overdose and mental health crisis among patients prescribed stable, long-term, higher-dose opioids. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study using deidentified medical and pharmacy claims and enrollment data from the OptumLabs Data Warehouse from 2008 to 2019. Adults in the US prescribed stable higher doses (mean ≥50 morphine milligram equivalents/d) of opioids for a 12-month baseline period with at least 2 months of follow-up were eligible for inclusion. EXPOSURES: Opioid tapering, defined as at least 15% relative reduction in mean daily dose during any of 6 overlapping 60-day windows within a 7-month follow-up period. Maximum monthly dose reduction velocity was computed during the same period. MAIN OUTCOMES AND MEASURES: Emergency or hospital encounters for (1) drug overdose or withdrawal and (2) mental health crisis (depression, anxiety, suicide attempt) during up to 12 months of follow-up. Discrete time negative binomial regression models estimated adjusted incidence rate ratios (aIRRs) of outcomes as a function of tapering (vs no tapering) and dose reduction velocity. RESULTS: The final cohort included 113 618 patients after 203 920 stable baseline periods. Among the patients who underwent dose tapering, 54.3% were women (vs 53.2% among those who did not undergo dose tapering), the mean age was 57.7 years (vs 58.3 years), and 38.8% were commercially insured (vs 41.9%). Posttapering patient periods were associated with an adjusted incidence rate of 9.3 overdose events per 100 person-years compared with 5.5 events per 100 person-years in nontapered periods (adjusted incidence rate difference, 3.8 per 100 person-years [95% CI, 3.0-4.6]; aIRR, 1.68 [95% CI, 1.53-1.85]). Tapering was associated with an adjusted incidence rate of 7.6 mental health crisis events per 100 person-years compared with 3.3 events per 100 person-years among nontapered periods (adjusted incidence rate difference, 4.3 per 100 person-years [95% CI, 3.2-5.3]; aIRR, 2.28 [95% CI, 1.96-2.65]). Increasing maximum monthly dose reduction velocity by 10% was associated with an aIRR of 1.09 for overdose (95% CI, 1.07-1.11) and of 1.18 for mental health crisis (95% CI, 1.14-1.21). CONCLUSIONS AND RELEVANCE: Among patients prescribed stable, long-term, higher-dose opioid therapy, tapering events were significantly associated with increased risk of overdose and mental health crisis. Although these findings raise questions about potential harms of tapering, interpretation is limited by the observational study design.

Opioid dosage tapering has emerged as a strategy to reduce harms associated with long-term opioid therapy; however, evidence supporting this approach is limited.To identify the association of opioid tapering or abrupt discontinuation with opioid overdose and suicide events among patients receiving stable long-term opioid therapy without evidence of opioid misuse.This comparative effectiveness study with a trial emulation approach used a large US claims data set of individuals with commercial insurance or Medicare Advantage who were aged 18 years or older and receiving stable long-term opioid therapy without evidence of opioid misuse between January 1, 2010, and December 31, 2018. Statistical analysis was performed from January 17, 2020, through November 12, 2021.Three opioid dosage strategies: stable dosage, tapering (dosage reduction ≥15%), or abrupt discontinuation.Time to opioid overdose or suicide event identified from International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis codes in medical claims over 11 months of follow-up. Inverse probability weighting was used to adjust for baseline confounders. The primary analysis used an intention-to-treat approach; follow-up after assignment regardless of changes in opioid dose was included. A per-protocol analysis was also conducted, in which episodes were censored for lack of adherence to assigned treatment.A cohort of 199 836 individuals (45.1% men; mean [SD] age, 56.9 [12.4] years; and 57.6% aged 45-64 years) had 415 123 qualifying, long-term opioid therapy episodes; 87.1% of episodes were considered stable, 11.1% were considered a taper, and 1.8% were considered abrupt discontinuation. The adjusted cumulative incidence of opioid overdose or suicide events 11 months after baseline was 0.96% (95% CI, 0.92%-0.99%) with a stable dosage strategy, 1.10% (95% CI, 0.99%-1.22%) with a tapered dosage strategy, and 1.28% (95% CI, 0.93%-1.38%) with an abrupt discontinuation strategy. The risk difference between a taper and a stable dosage was 0.15% (95% CI, 0.03%-0.26%), and the risk difference between abrupt discontinuation and a stable dosage was 0.33% (95% CI, -0.03% to 0.74%). Results were similar using the per-protocol approach.This study identified a small absolute increase in risk of harms associated with opioid tapering compared with a stable opioid dosage. These results do not suggest that policies of mandatory dosage tapering for individuals receiving a stable long-term opioid dosage without evidence of opioid misuse will reduce short-term harm via suicide and overdose.

OBJECTIVES Widespread use and misuse of prescription and illicit opioids have exposed millions to health risks including serious infectious complications. Little is known, however, about the association between opioid use and sepsis. DESIGN Retrospective cohort study. SETTING About 373 U.S. hospitals. PATIENTS Adults hospitalized between January 2009 and September 2015. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Sepsis was identified by clinical indicators of concurrent infection and organ dysfunction. Opioid-related hospitalizations were identified by the International Classification of Diseases, 9th Revision, Clinical Modification codes and/or inpatient orders for buprenorphine. Clinical characteristics and outcomes were compared by sepsis and opioid-related hospitalization status. The association between opioid-related hospitalization and all-cause, in-hospital mortality in patients with sepsis was assessed using mixed-effects logistic models to adjust for baseline characteristics and severity of illness.The cohort included 6,715,286 hospitalizations; 375,479 (5.6%) had sepsis, 130,399 (1.9%) had opioid-related hospitalizations, and 8,764 (0.1%) had both. Compared with sepsis patients without opioid-related hospitalizations (n = 366,715), sepsis patients with opioid-related hospitalizations (n = 8,764) were younger (mean 52.3 vs 66.9 yr) and healthier (mean Elixhauser score 5.4 vs 10.5), had more bloodstream infections from Gram-positive and fungal pathogens (68.9% vs 47.0% and 10.6% vs 6.4%, respectively), and had lower in-hospital mortality rates (10.6% vs 16.2%; adjusted odds ratio, 0.73; 95% CI, 0.60-0.79; p < 0.001 for all comparisons). Of 1,803 patients with opioid-related hospitalizations who died in-hospital, 928 (51.5%) had sepsis. Opioid-related hospitalizations accounted for 1.5% of all sepsis-associated deaths, including 5.7% of sepsis deaths among patients less than 50 years old. From 2009 to 2015, the proportion of sepsis hospitalizations that were opioid-related increased by 77% (95% CI, 40.7-123.5%). CONCLUSIONS Sepsis is an important cause of morbidity and mortality in patients with opioid-related hospitalizations, and opioid-related hospitalizations contribute disproportionately to sepsis-associated deaths among younger patients. In addition to ongoing efforts to combat the opioid crisis, public health agencies should focus on raising awareness about sepsis among patients who use opioids and their providers.

Objectives: Opioid-related overdoses are commonly attributed to prescription opioids. We examined data on opioid-related overdose decedents in Massachusetts. For each decedent, we determined which opioid medications had been prescribed and dispensed and which opioids were detected in postmortem medical examiner toxicology specimens. Methods: Among opioid-related overdose decedents in Massachusetts during 2013-2015, we analyzed individually linked postmortem opioid toxicology reports and prescription drug monitoring program records to determine instances of overdose in which a decedent had a prescription active on the date of death for the opioid(s) detected in the toxicology report. We also calculated the proportion of overdoses for which prescribed opioid medications were not detected in decedents’ toxicology reports. Results: Of 2916 decedents with complete toxicology reports, 1789 (61.4%) had heroin and 1322 (45.3%) had fentanyl detected in postmortem toxicology reports. Of the 491 (16.8%) decedents with ≥1 opioid prescription active on the date of death, prescribed opioids were commonly not detected in toxicology reports, specifically: buprenorphine (56 of 97; 57.7%), oxycodone (93 of 176; 52.8%), and methadone prescribed for opioid use disorder (36 of 112; 32.1%). Only 39 (1.3%) decedents had an active prescription for each opioid detected in toxicology reports on the date of death. Conclusion: Linking overdose toxicology reports to prescription drug monitoring program records can help attribute overdoses to prescribed opioids, diverted prescription opioids, heroin, and illicitly made fentanyl.

Background and aims While prescribed and illicit opioid use are primary drivers of the national surges in overdose deaths, opioid overdose deaths in which stimulants are also present are increasing in the U.S. We determined the social determinants and sociodemographic factors associated with opioid-only versus polysubstance opioid overdose deaths in Massachusetts. Particular attention was focused on the role of stimulants in opioid overdose deaths. Methods We analyzed all opioid-related overdose deaths from 2014 to 2015 in an individually-linked population database in Massachusetts. We used linked postmortem toxicology data to identify drugs present at the time of death. We constructed a multinomial logistic regression model to identify factors associated with three mutually exclusive overdose death groups based on toxicological results: opioid-related deaths with (1) opioids only present, (2) opioids and other substances not including stimulants, and (3) opioids and stimulants with or without other substances. Results Between 2014 and 2015, there were 2,244 opioid-related overdose deaths in Massachusetts that had accompanying toxicology results. Toxicology reports indicated that 17% had opioids only, 36% had opioids plus stimulants, and 46% had opioids plus another non-stimulant substance. Persons older than 24 years, non-rural residents, those with comorbid mental illness, non-Hispanic black residents, and persons with recent homelessness were more likely than their counterparts to die with opioids and stimulants than opioids alone. Conclusions Polysubstance opioid overdose is increasingly common in the US. Addressing modifiable social determinants of health, including barriers to mental health services and homelessness, is important to reduce polysubstance use and overdose deaths.

Although HIV preexposure prophylaxis (PrEP) implementation among persons who inject drugs has been inadequate, national HIV monitoring programs do not include data on PrEP, and specific trends in PrEP use are not well understood.To estimate HIV PrEP uptake among commercially insured persons with opioid or stimulant use disorder by injection drug use (IDU) status.This cross-sectional study used deidentified data from the MarketScan Commercial Claims and Encounters Database to identify a sample of 547 709 commercially insured persons without HIV but with opioid and/or stimulant use disorder, including 110 592 with evidence of IDU between January 1, 2010, and December 31, 2019. Data were analyzed from November 1, 2020, to July 1, 2021.Persons with opioid and/or stimulant use disorder and evidence of IDU were identified through claims data.The outcome was receipt of tenofovir disoproxil fumarate and emtricitabine for PrEP as identified from filled pharmacy claims. Multivariable logistic regression was used to assess the association of demographic and clinical characteristics with receipt of PrEP.The study cohort included 211 609 (28.6%) females and 336 100 (61.4%) males with a combined mean (SD) age of 34.8 (13.1) years, including 110 592 individuals with evidence of IDU. During the study period, 508 (0.09%) persons with opioid and/or stimulant use disorder, including 170 (0.15%) with evidence of IDU, received PrEP. Receipt of PrEP increased from 0.001 to 0.243 per 100 person-years from 2010 through 2019 among the entire cohort and from 0.000 to 0.295 per 100 person-years among those with IDU. In multivariable analysis, PrEP use was more likely among males (adjusted odds ratio [aOR] 8.72; 95% CI, 6.39-11.89), persons with evidence of IDU (aOR, 1.47; 95% CI, 1.21-1.79), and persons with evidence of sexual risk indications for PrEP (aOR, 23.68; 95% CI, 19.57-28.66).In this cross-sectional study of commercially insured persons with opioid and/or stimulant use disorder, HIV PrEP delivery remained low, including among those with evidence of IDU. PrEP should be consistently offered alongside substance use disorder treatment and other harm reduction and HIV prevention services.

Objectives. To estimate the annual prevalence of opioid use disorder (OUD) in Massachusetts from 2011 to 2015. Methods. We performed a multisample stratified capture–recapture analysis to estimate OUD prevalence in Massachusetts. Individuals identified from 6 administrative databases for 2011 to 2012 and 7 databases for 2013 to 2015 were linked at the individual level and included in the analysis. Individuals were stratified by age group, sex, and county of residence. Results. The OUD prevalence in Massachusetts among people aged 11 years or older was 2.72% in 2011 and 2.87% in 2012. Between 2013 and 2015, the prevalence increased from 3.87% to 4.60%. The greatest increase in prevalence was observed among those in the youngest age group (11–25 years), a 76% increase from 2011 to 2012 and a 42% increase from 2013 to 2015. Conclusions. In Massachusetts, the OUD prevalence was 4.6% among people 11 years or older in 2015. The number of individuals with OUD is likely increasing, particularly among young people.

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

Objective To determine HIV testing trends during emergency department (ED) visits among those with and without substance use disorder (SUD) and examine factors associated with test receipt. Methods We identified individuals age ≥ 15 with an ED visit between 2014 and 2018 in the National Hospital Ambulatory Medical Care Survey (NHAMCS), a representative sample of United States ED visits. We examined HIV testing trends by SUD status and used multivariable logistic regression accounting for NHAMCS's complex survey design to identify factors associated with HIV testing. Results We identified 6399 SUD and 75,498 non-SUD ED visits. Of SUD visits, 1.4% [95% Confidence Interval (95%CI 0.9–1.9)] resulted in HIV testing compared to 0.6% (95%CI 0.4–0.7) of non-SUD visits. During the second half of the study (Q3, 2016 - Q4, 2018), HIV testing increased from 1.1% (95%CI 0.6–1.6) to 1.7% (95%CI 1.0–2.5) among those with SUD and from 0.5% (95%CI 0.3–0.6) to 0.6% (95%CI 0.5–0.8) among those without SUD. In adjusted models, SUD status was associated with increased odds of HIV testing [Adjusted Odds Ratio (AOR) 1.6 (95%CI 1.1–2.2)]. Those receiving toxicology testing (AOR 2.2, 95%CI 1.6–3.2), Black (AOR 3.6, 95%CI 2.6–4.9) and Hispanic people (AOR 2.7, 95%CI 1.9–3.7), insured by Medicaid (AOR 1.6, 95%CI 1.2–2.2) or self-pay (AOR 1.7, 95%CI 1.1–2.8), and with venipuncture (AOR 3.0, 95%CI 2.2–4.1) also had greater odds of HIV testing. Conclusion HIV testing in the ED was rare, but slightly more common in individuals with SUD. Efforts to increase ED HIV testing among people with SUD are needed.

Background Efforts to address opioid-involved overdose fatalities have led to widespread implementation of various initiatives to taper (i.e., reduce or discontinue) opioid prescriptions despite a limited understanding of patients’ experience. Methods From 2019–2020, we recruited patients with chronic, non-cancer pain who had undergone a reduction in opioid daily dosage of ≥50 % in the past two years at Boston Medical Center or Michigan Medicine. Participants completed semi-structured interviews exploring health history, opioid use, and taper experiences. Inductive analysis, guided by theoretical conceptualizations of structural stigma, identified emergent themes. Results Among 41 participants, three elements of structural stigma were identified across participants’ lives. First, participants identified themselves as overlooked subjects of the U.S. opioid crisis, who experienced overprescribing, subsequent stigmatization and surveillance of opioid use (e.g., toxicology screening, “pill counts”), and various tapering initiatives. Second, during the course of pain treatment, participants felt stigmatized and invalidated by cultural norms linking chronic pain to stereotypes of acting disingenuously (e.g., “drug-seeking”). Finally, during and after tapers, institutional policies and programs further increased participants’ feelings of marginalization, producing multiple unintended consequences, including reduced access to medical care and feeling “orphaned by the system.” Conclusions Opioid tapers may exacerbate the social production and burden of stigma among patients with chronic pain, especially when processes are perceived to invalidate pain, endorse stereotypes, and label previously effective, acceptable treatment as inappropriate. Findings highlight how various tapering initiatives reinforce the devalued status of people living with chronic pain while also reducing patients’ wellbeing and confidence in medical systems.

This cohort study assess the association of receipt of medication for opioid use disorder and mortality after hospitalization for injection drug use–associated infective endocarditis in Massachusetts., Key Points Question Is there an association between receipt of medication for opioid use disorder (MOUD) and mortality after hospitalization for injection drug use–associated infective endocarditis? Findings In this cohort study 679 individuals hospitalized with injection drug use–associated endocarditis, 24% received MOUD within 3 months of discharge. MOUD receipt within 3 months of discharge was not associated with reduced mortality but was associated with a reduction in mortality in the month received. Meaning In this study, treatment with MOUD was uncommon and was associated with reduced mortality in the time-varying analysis but not the main analysis, possibly owing to poor treatment retention., Importance Although hospitalizations for injection drug use–associated infective endocarditis (IDU-IE) have increased during the opioid crisis, utilization of and mortality associated with receipt of medication for opioid use disorder (MOUD) after discharge from the hospital among patients with IDU-IE are unknown. Objective To assess the proportion of patients receiving MOUD after hospitalization for IDU-IE and the association of MOUD receipt with mortality. Design, Setting, and Participants This retrospective cohort study used a population registry with person-level medical claims, prescription monitoring program, mortality, and substance use treatment data from Massachusetts between January 1, 2011, and December 31, 2015; IDU-IE–related discharges between July 1, 2011, and June, 30, 2015, were analyzed. All Massachusetts residents aged 18 to 64 years with a first hospitalization for IDU-IE were included; IDU-IE was defined as any hospitalization with a diagnosis of endocarditis and at least 1 claim in the prior 6 months for OUD, drug use, or hepatitis C and with 2-month survival after hospital discharge. Data were analyzed from November 11, 2018, to June 23, 2020. Exposure Receipt of MOUD, defined as any treatment with methadone, buprenorphine, or naltrexone, within 3 months after hospital discharge excluding discharge month for IDU-IE. Main Outcomes and Measures The main outcome was all-cause mortality. The proportion of patients who received MOUD in the 3 months after hospital discharge was calculated. Multivariable Cox proportional hazard regression models were used to examine the association of MOUD receipt with mortality, adjusting for sex, age, medical and psychiatric comorbidities, and homelessness. In the secondary analysis, receipt of MOUD was considered as a monthly time-varying exposure. Results Of 679 individuals with IDU-IE, 413 (60.8%) were male, the mean (SD) age was 39.2 (12.1) years, 298 (43.9%) were aged 18 to 34 years, 419 (72.3) had mental illness, and 209 (30.8) experienced homelessness. A total of 134 individuals (19.7%) received MOUD in the 3 months before hospitalization and 165 (24.3%) in the 3 months after hospital discharge. Of those who received MOUD after discharge, 112 (67.9%) received buprenorphine. The crude mortality rate was 9.2 deaths per 100 person-years. MOUD receipt within 3 months after discharge was not associated with reduced mortality (adjusted hazard ratio, 1.29; 95% CI, 0.61-2.72); however, MOUD receipt was associated with reduced mortality in the month that MOUD was received (adjusted hazard ratio, 0.30; 95% CI, 0.10-0.89). Conclusions and Relevance In this cohort study, receipt of MOUD was associated with reduced mortality after hospitalization for injection drug use–associated endocarditis only in the month it was received. Efforts to improve MOUD initiation and retention after IDU-IE hospitalization may be beneficial.

Objectives Opioid overdose deaths in Massachusetts linked to illicitly-manufactured fentanyl have increased dramatically. In response, an urban safety-net hospital added urine fentanyl testing with reflex confirmation testing to its standard urine toxicology panel. The goals of this study were to describe fentanyl toxicology test results, identify the positive predictive value of presumptive fentanyl immunoassay, and describe co-substance use among those with unexpected fentanyl positive results. Methods We included urine toxicology tests from January through June 2016 analyzed at an urban safety-net hospital. We excluded tests from individuals prescribed or administered fentanyl within the preceding 72 hours. Positive fentanyl immunoassay tests underwent reflex chromatography confirmation testing. Samples that confirmed positive for acetyl fentanyl and/or fentanyl and/or norfentanyl were considered true positives. Results Of 11,873 urine samples, 10.4% of samples screened fentanyl positive and 8.8% were confirmed fentanyl positive. The positive predictive value of a positive urine fentanyl screen was 85.7%. Of 4398 unique patients, 13.2% had at least 1 test confirmed positive for nonprescription fentanyl. Patients with a confirmed fentanyl positive drug test were more likely to have positive urine drug test for barbiturates, benzodiazepines, cocaine, methadone, and opiates, and less likely to have oxycodone or buprenorphine. Conclusions At an urban safety-net hospital, nonprescription fentanyl use was common and was associated with greater use of other substances favoring routine fentanyl testing. Although the positive predictive value of the screening test was high, confirmation testing detected substantial numbers of false positives, especially in older patients. Therefore, fentanyl confirmation testing should be used when results will change treatment approach and patient education.

Highlights • HEALing Communities Study is a parallel-group cluster randomized controlled trial. • Communities That HEAL intervention’s goal is to reduce opioid overdose deaths. • Structured consensus decision-making strategy guided study measure development. • More than 80 study measure specifications and a common data model were developed. • The study will provide methodology and longitudinal community data for research., Background Opioid overdose deaths remain high in the U.S. Despite having effective interventions to prevent overdose deaths, there are numerous barriers that impede their adoption. The primary aim of the HEALing Communities Study (HCS) is to determine the impact of an intervention consisting of community-engaged, data-driven selection, and implementation of an integrated set of evidence-based practices (EBPs) on reducing opioid overdose deaths. Methods The HCS is a four year multi-site, parallel-group, cluster randomized wait-list controlled trial. Communities (n = 67) in Kentucky, Massachusetts, New York and Ohio are randomized to active intervention (Wave 1), which starts the intervention in Year 1 or the wait-list control (Wave 2), which starts the intervention in Year 3. The HCS will test a conceptually driven framework to assist communities in selecting and adopting EBPs with three components: 1) A community engagement strategy with local coalitions to guide and implement the intervention; 2) A compendium of EBPs coupled with technical assistance; and 3) A series of communication campaigns to increase awareness and demand for EBPs and reduce stigma. An implementation science framework guides the intervention and allows for examination of the multilevel contexts that promote or impede adoption and expansion of EBPs. The primary outcome, number of opioid overdose deaths, will be compared between Wave 1 and Wave 2 communities during Year 2 of the intervention for Wave 1. Numerous secondary outcomes will be examined. Discussion The HCS is the largest community-based implementation study in the field of addiction with an ambitious goal of significantly reducing fatal opioid overdoses.

Background Although national syndromic surveillance data reported declines in emergency department (ED) visits after the declaration of the national stay-at-home order for COVID-19, little is known whether these declines were observed for suspected opioid overdose. Methods This interrupted time series study used syndromic surveillance data from four states participating in the HEALing Communities Study: Kentucky, Massachusetts, New York, and Ohio. All ED encounters for suspected opioid overdose (n = 48,301) occurring during the first 31 weeks of 2020 were included. We examined the impact of the national public health emergency for COVID-19 (declared on March 14, 2020) on trends in ED encounters for suspected opioid overdose. Results Three of four states (Massachusetts, New York and Ohio) experienced a statistically significant immediate decline in the rate of ED encounters for suspected opioid overdose (per 100,000) after the nationwide public health emergency declaration (MA: -0.99; 95 % CI: -1.75, -0.24; NY: -0.10; 95 % CI, -0.20, 0.0; OH: -0.33, 95 % CI: -0.58, -0.07). After this date, Ohio and Kentucky experienced a sustained rate of increase for a 13-week period. New York experienced a decrease in the rate of ED encounters for a 10-week period, after which the rate began to increase. In Massachusetts after a significant immediate decline in the rate of ED encounters, there was no significant difference in the rate of change for a 6-week period, followed by an immediate increase in the ED rate to higher than pre-COVID levels. Conclusions The heterogeneity in the trends in ED encounters between the four sites show that the national stay-at-home order had a differential impact on opioid overdose ED presentation in each state.

Objective: A risk evaluation and mitigation strategy for extended-release and long-acting (ER/LA) opioid analgesics was approved by the Food and Drug Administration in 2012. Our objective was to assess frequency of opioid tolerance and urine drug testing for individuals initiating ER/LA opioid analgesics. Design: Retrospective cohort study. Setting: Sentinel, a distributed database with electronic healthcare data on >190 million predominantly commercially insured members. Patients, participants: Members under age 65 initiating ER/LA opioid analgesics between January 2009 and December 2013. Main outcome measure(s): We examined the proportion of opioid-tolerantonly ER/LA opioid analgesic initiates meeting tolerance criteria: receipt of ≥ 30 mg oxycodone equivalents per day in 7 days prior to the first opioid-tolerant-only dispensing. We separately examined the proportion of new users of extended-release oxycodone (ERO) and other ER/LA opioid analgesics with a claim for a urine drug test in the 30 days prior to, and separately for the 183 days after, dispensing. Results: We identified 79,824 ERO, 7,343 extended-release hydromorphone, and 91,778 transdermal fentanyl opioid-tolerant-only episodes. Tolerance criteria were met in 64 percent of ERO, 64 percent of extended-release hydromorphone and 40 percent of transdermal fentanyl episodes. We identified 210,581 incident ERO and 311,660 other ER/LA opioid analgesic episodes. Use of urine drug testing for ERO compared with other ER/LA opioid analgesics was: 4 percent vs 14 percent respectively in the 30 days prior to initiation and 9 percent vs 23 percent respectively in the 183 days following initiation. Conclusions: These results suggest potential areas for improving appropriate ER/LA opioid analgesic prescribing practices.

ObjectivesTo prospectively characterise: (1) postoperative opioid analgesic prescribing practices; (2) experience of patients undergoing elective ambulatory surgeries and (3) impact of patient risk for medication misuse on postoperative pain management.DesignLongitudinal survey of patients 7 days before and 7–14 days after surgery.SettingAcademic urban safety-net hospital.Participants181 participants recruited, 18 surgeons, follow-up data from 149 participants (82% retention); 54% women; mean age: 49 years.InterventionsNone.Primary and secondary outcome measuresTotal morphine equivalent dose (MED) prescribed and consumed, percentage of unused opioids.ResultsSurgeons postoperatively prescribed a mean of 242 total MED per patient, equivalent to 32 oxycodone (5 mg) pills. Participants used a mean of 116 MEDs (48%), equivalent to 18 oxycodone (5 mg) pills (~145 mg of oxycodone remaining per patient). A 10-year increase in patient age was associated with 12 (95% CI (−2.05 to –0.35)) total MED fewer prescribed opioids. Each one-point increase in the preoperative Graded Chronic Pain Scale was associated with an 18 (6.84 to 29.60) total MED increase in opioid consumption, and 5% (−0.09% to –0.005%) fewer unused opioids. Prior opioid prescription was associated with a 55 (5.38 to –104.82) total MED increase in opioid consumption, and 19% (−0.35% to –0.02%) fewer unused opioids. High-risk drug use was associated with 9% (−0.19% to 0.002%) fewer unused opioids. Pain severity in previous 3 months, high-risk alcohol, use and prior opioid prescription were not associated with postoperative prescribing practices.ConclusionsParticipants with a preoperative history of chronic pain, prior opioid prescription, and high-risk drug use were more likely to consume higher amounts of opioid medications postoperatively. Additionally, surgeons did not incorporate key patient-level factors (eg, substance use, preoperative pain) into opioid prescribing practices. Opportunities to improve postoperative opioid prescribing include system changes among surgical specialties, and patient education and monitoring.

Objective: A risk evaluation and mitigation strategy for extended-release and long-acting (ER/LA) opioid analgesics was approved by the Food and Drug Administration in 2012. Our objective was to assess frequency of opioid tolerance and urine drug testing for individuals initiating ER/LA opioid analgesics.Design: Retrospective cohort study.Setting: Sentinel, a distributed database with electronic healthcare data on >190 million predominantly commercially insured members.Patients, participants: Members under age 65 initiating ER/LA opioid analgesics between January 2009 and December 2013.Main outcome measure(s): We examined the proportion of opioid-tolerantonly ER/LA opioid analgesic initiates meeting tolerance criteria: receipt of ≥30 mg oxycodone equivalents per day in 7 days prior to the first opioid-tolerant-only dispensing. We separately examined the proportion of new users of extended-release oxycodone (ERO) and other ER/LA opioid analgesics with a claim for a urine drug test in the 30 days prior to, and separately for the 183 days after, dispensing.Results: We identified 79,824 ERO, 7,343 extended-release hydromorphone, and 91,778 transdermal fentanyl opioid-tolerant-only episodes. Tolerance criteria were met in 64 percent of ERO, 64 percent of extended-release hydromorphone and 40 percent of transdermal fentanyl episodes. We identified 210,581 incident ERO and 311,660 other ER/LA opioid analgesic episodes. Use of urine drug testing for ERO compared with other ER/LA opioid analgesics was: 4 percent vs 14 percent respectively in the 30 days prior to initiation and 9 percent vs 23 percent respectively in the 183 days following initiation.Conclusions: These results suggest potential areas for improving appropriate ER/LA opioid analgesic prescribing practices.

OBJECTIVE: Experts cautioned that patients affected by the November 2010 withdrawal of the opioid analgesic propoxyphene might receive riskier prescriptions. To explore this, we compared drug receipt and outcomes among propoxyphene users before and after market withdrawal. STUDY DESIGN: Using OptumLabs data, we studied three populations: commercial, Medicare Advantage aged (age 65+) and Medicare Advantage disabled (age

BACKGROUND: Patterns of inpatient opioid use and their associations with postdischarge opioid use are poorly understood. OBJECTIVE: To measure patterns in timing, duration, and setting of opioid administration in opioid-naive hospitalized patients and to examine associations with postdischarge use. DESIGN: Retrospective cohort study using electronic health record data from 2010 to 2014. SETTING: 12 community and academic hospitals in Pennsylvania. PATIENTS: 148 068 opioid-naive patients (191 249 admissions) with at least 1 outpatient encounter within 12 months before and after admission. MEASUREMENTS: Number of days and patterns of inpatient opioid use; any outpatient use (self-report and/or prescription orders) 90 and 365 days after discharge. RESULTS: Opioids were administered in 48% of admissions. Patients were given opioids for a mean of 67.9% (SD, 25.0%) of their stay. Location of administration of first opioid on admission, timing of last opioid before discharge, and receipt of nonopioid analgesics varied substantially. After adjustment for potential confounders, 5.9% of inpatients receiving opioids had outpatient use at 90 days compared with 3.0% of those without inpatient use (difference, 3.0 percentage points [95% CI, 2.8 to 3.2 percentage points]). Opioid use at 90 days was higher in inpatients receiving opioids less than 12 hours before discharge than in those with at least 24 opioid-free hours before discharge (7.5% vs. 3.9%; difference, 3.6 percentage points [CI, 3.3 to 3.9 percentage points]). Differences based on proportion of the stay with opioid use were modest (opioid use at 90 days was 6.4% and 5.4%, respectively, for patients with opioid use for ≥75% vs. ≤25% of their stay; difference, 1.0 percentage point [CI, 0.4 to 1.5 percentage points]). Associations were similar for opioid use 365 days after discharge. LIMITATION: Potential unmeasured confounders related to opioid use. CONCLUSION: This study found high rates of opioid administration to opioid-naive inpatients and associations between specific patterns of inpatient use and risk for long-term use after discharge. PRIMARY FUNDING SOURCE: UPMC Health System and University of Pittsburgh.

Summary Objective Tramadol has been widely used among patients with osteoarthritis (OA); however, there is paucity of information on its cardiovascular risk. We aimed to examine the association of tramadol with risk of myocardial infarction (MI) among patients with OA. Design Among OA patients aged 50–90 years without history of MI, cancer, or opioid use disorder in The Health Improvement Network database in the United Kingdom (2000–2016), three sequential propensity-score matched cohort studies were assembled, i.e., (1) patients who initiated tramadol or naproxen (negative comparator); (2) patients who initiated tramadol or diclofenac (positive comparator); and (3) patients who initiated tramadol or codeine (a commonly used weak opioid). The outcome was incident MI over six-months. Results Among tramadol and naproxen initiators (n = 33,024 in each cohort), 77 (4.8/1000 person-years) and 46 (2.8/1000 person-years) incident MI occurred, respectively. The rate difference (RD) and hazard ratios (HR) for incident MI with tramadol initiation were 1.9 (95% confidence interval [CI] 0.6 to 2.3)/1000 person-years and 1.68 (95% CI 1.16 to 2.41) relative to naproxen initiation, respectively. Among tramadol and diclofenac initiators (n = 18,662 in each cohort), 58 (6.4/1000 person-years) and 47 (5.1/1000 person-years) incident MIs occurred, respectively. The corresponding RD and HR for incident MI were 1.2 (95%CI -2.1 to 14.1)/1000 person-years and 1.24 (95%CI 0.84 to 1.82), respectively. Among tramadol and codeine initiators (n = 42,722 in each cohort), 127 (6.1/1000 person-years) and 103 (5.0/1000 person-years) incident MI occurred, respectively, and the corresponding RD and HR were 1.1 (95%CI:-0.3 to 2.5)/1000 person-years and 1.23 (95%CI:0.95 to 1.60), respectively. Conclusions In this population-based cohort of patients with OA, the six-month risk of MI among initiators of tramadol was higher than that of naproxen, but comparable to, if not lower than, those of diclofenac or codeine.

Background Medical care, public health, and criminal justice systems encounters could serve as touchpoints to identify and intervene with individuals at high-risk of opioid overdose death. The relative risk of opioid overdose death and proportion of deaths that could be averted at such touchpoints are unknown. Methods We used 8 individually linked data sets from Massachusetts government agencies to perform a retrospective cohort study of Massachusetts residents ages 11 and older. For each month in 2014, we identified past 12-month exposure to 4 opioid prescription touchpoints (high dosage, benzodiazepine co-prescribing, multiple prescribers, or multiple pharmacies) and 4 critical encounter touchpoints (opioid detoxification, nonfatal opioid overdose, injection-related infection, and release from incarceration). The outcome was opioid overdose death. We calculated Standardized Mortality Ratios (SMRs) and Population Attributable Fractions (PAFs) associated with touchpoint exposure. Results The cohort consisted of 6,717,390 person-years of follow-up with 1315 opioid overdose deaths. We identified past 12-month exposure to any touchpoint in 2.7% of person-months and for 51.8% of opioid overdose deaths. Opioid overdose SMRs were 12.6 (95% CI: 11.1, 14.1) for opioid prescription and 68.4 (95% CI: 62.4, 74.5) for critical encounter touchpoints. Fatal opioid overdose PAFs were 0.19 (95% CI: 0.17, 0.21) for opioid prescription and 0.37 (95% CI: 0.34, 0.39) for critical encounter touchpoints. Conclusions Using public health data, we found eight candidate touchpoints were associated with increased risk of fatal opioid overdose, and collectively identified more than half of opioid overdose decedents. These touchpoints are potential targets for development of overdose prevention interventions.

OBJECTIVE: Prescription Drug Monitoring Programs (PDMPs) are intended to help reduce prescription drug misuse and opioid overdose, yet little is known about the longitudinal patterns of opioid prescribing that may be associated with mortality. This study investigated longitudinal opioid prescribing patterns among patients with opioid use disorder (OUD) and without OUD in relation to mortality using PDMP data. METHODS: Growth modeling was used to examine opioid prescription data from the California PDMP over a 4-year period prior to death or a comparable period ending in 2014 for those remaining from a sample of 7,728 patients (2,576 with OUD, and 5,152 matched non-OUD controls) treated in a large healthcare system. RESULTS: Compared to controls, individuals with OUD (alive and deceased) had received significantly more opioid prescriptions, greater number of days’ supply, and steeper increases of opioid dosages over time. For morphine equivalents (ME, in grams), the interaction of OUD and mortality was significant at both intercept (β=10.4, SE=4.4, p

Background With opioid misuse, opioid use disorder (OUD), and opioid overdose deaths persisting at epidemic levels in the U.S., the largest implementation study in addiction research—the HEALing Communities Study (HCS)—is evaluating the impact of the Communities That Heal (CTH) intervention on reducing opioid overdose deaths in 67 disproportionately affected communities from four states (i.e., “sites”). Community-tailored dashboards are central to the CTH intervention’s mandate to implement a community-engaged and data-driven process. These dashboards support a participating community’s decision-making for selection and monitoring of evidence-based practices to reduce opioid overdose deaths. Methods/Design A community-tailored dashboard is a web-based set of interactive data visualizations of community-specific metrics. Metrics include opioid overdose deaths and other OUD-related measures, as well as drivers of change of these outcomes in a community. Each community-tailored dashboard is a product of a co-creation process between HCS researchers and stakeholders from each community. The four research sites used a varied set of technical approaches and solutions to support the scientific design and CTH intervention implementation. Ongoing evaluation of the dashboards involves quantitative and qualitative data on key aspects posited to shape dashboard use combined with website analytics. Discussion The HCS presents an opportunity to advance how community-tailored dashboards can foster community-driven solutions to address the opioid epidemic. Lessons learned can be applied to inform interventions for public health concerns and issues that have disproportionate impact across communities and populations (e.g., racial/ethnic and sexual/gender minorities and other marginalized individuals). Trial registration ClinicalTrials.gov (NCT04111939)

Background The Helping to End Addiction Long-termSM (HEALing) Communities Study (HCS) is a multisite, parallel-group, cluster randomized wait-list controlled trial evaluating the impact of the Communities That HEAL intervention to reduce opioid overdose deaths and associated adverse outcomes. This paper presents the approach used to define and align administrative data across the four research sites to measure key study outcomes. Methods Priority was given to using administrative data and established data collection infrastructure to ensure reliable, timely, and sustainable measures and to harmonize study outcomes across the HCS sites. Results The research teams established multiple data use agreements and developed technical specifications for more than 80 study measures. The primary outcome, number of opioid overdose deaths, will be measured from death certificate data. Three secondary outcome measures will support hypothesis testing for specific evidence-based practices known to decrease opioid overdose deaths: (1) number of naloxone units distributed in HCS communities; (2) number of unique HCS residents receiving Food and Drug Administration-approved buprenorphine products for treatment of opioid use disorder; and (3) number of HCS residents with new incidents of high-risk opioid prescribing. Conclusions The HCS has already made an impact on existing data capacity in the four states. In addition to providing data needed to measure study outcomes, the HCS will provide methodology and tools to facilitate data-driven responses to the opioid epidemic, and establish a central repository for community-level longitudinal data to help researchers and public health practitioners study and understand different aspects of the Communities That HEAL framework.

“Is It Safe for Me to Go to Work?” A strategy to protect at-risk workers requires a framework for counseling patients about the risks posed by continuing to work, policy changes to ensure financial...

BACKGROUND: Since 2010, heroin-related overdoses have risen sharply, coinciding with policies to restrict access to prescription opioids. It is unknown if patients tapered or discontinued off prescription opioids transitioned to riskier heroin use. This study examined opioid prescribing, including long-term opioid therapy (LTOT) and discontinuation, prior to heroin overdose. METHODS: We used retrospective longitudinal data from a national claims database to identify adults with an emergency or inpatient claim for heroin overdose between January 2010 and June 2017. Receipt of opioid prescription, LTOT episodes, and discontinuation of LTOT were measured for the period of one year prior to heroin overdose. RESULTS: We identified 3183 individuals (53.2% age 18–25; 70.0% male) with a heroin overdose (incidence rate 4.20 per 100k person years). Nearly half (42.3%) received an opioid prescription in the prior 12 months, and 10.9% had an active opioid prescription in the week prior to overdose. LTOT at any time in the 12 months prior to overdose was uncommon (12.8%) among those with heroin overdoses, especially among individuals 18–25 years old (3.5%, P < 0.001). LTOT discontinuation prior to overdose was also relatively uncommon, experienced by 6.7% of individuals aged 46 and over and 2.5% of individuals aged 18–25 years (P < 0.001). CONCLUSIONS: Prior to heroin overdose, prescription opioid use was common, but LTOT discontinuation was uncommon and observed primarily in older individuals with the lowest heroin overdose rates. Further study is needed to determine if these prescribing patterns are associated with increased heroin overdose.

Importance Nonfatal opioid overdose may be a critical touch point when youths who have never received a diagnosis of opioid use disorder can be engaged in treatment. However, the extent to which youths (adolescents and young adults) receive timely evidence-based treatment following opioid overdose is unknown. Objective To identify characteristics of youths who experience nonfatal overdose with heroin or other opioids and to assess the percentage of youths receiving timely evidence-based treatment. Design, Setting, and Participants This retrospective cohort study used the 2009-2015 Truven–IBM Watson Health MarketScan Medicaid claims database from 16 deidentified states representing all US census regions. Data from 4 039 216 Medicaid-enrolled youths aged 13 to 22 years were included and were analyzed from April 20, 2018, to March 21, 2019. Exposures Nonfatal incident and recurrent opioid overdoses involving heroin or other opioids. Main Outcomes and Measures Receipt of timely addiction treatment (defined as a claim for behavioral health services, for buprenorphine, methadone, or naltrexone prescription or administration, or for both behavioral health services and pharmacotherapy within 30 days of incident overdose). Sociodemographic and clinical characteristics associated with receipt of timely treatment as well as with incident and recurrent overdoses were also identified. Results Among 3791 youths with nonfatal opioid overdose, 2234 (58.9%) were female, and 2491 (65.7%) were non-Hispanic white. The median age was 18 years (interquartile range, 16-20 years). The crude incident opioid overdose rate was 44.1 per 100 000 person-years. Of these 3791 youths, 1001 (26.4%) experienced a heroin overdose; the 2790 (73.6%) remaining youths experienced an overdose involving other opioids. The risk of recurrent overdose among youths with incident heroin involvement was significantly higher than that among youths with other opioid overdose (adjusted hazard ratio, 2.62; 95% CI, 2.14-3.22), and youths with incident heroin overdose experienced recurrent overdose at a crude rate of 20 700 per 100 000 person-years. Of 3606 youths with opioid-related overdose and continuous enrollment for at least 30 days after overdose, 2483 (68.9%) received no addiction treatment within 30 days after incident opioid overdose, whereas only 1056 youths (29.3%) received behavioral health services alone, and 67 youths (1.9%) received pharmacotherapy. Youths with heroin overdose were significantly less likely than youths with other opioid overdose to receive any treatment after their overdose (adjusted odds ratio, 0.64; 95% CI, 0.49-0.83). Conclusions and Relevance After opioid overdose, less than one-third of youths received timely addiction treatment, and only 1 in 54 youths received recommended evidence-based pharmacotherapy. Interventions are urgently needed to link youths to treatment after overdose, with priority placed on improving access to pharmacotherapy.

Importance Although clinical trials demonstrate the superior effectiveness of medication for opioid use disorder (MOUD) compared with nonpharmacologic treatment, national data on the comparative effectiveness of real-world treatment pathways are lacking. Objective To examine associations between opioid use disorder (OUD) treatment pathways and overdose and opioid-related acute care use as proxies for OUD recurrence. Design, Setting, and Participants This retrospective comparative effectiveness research study assessed deidentified claims from the OptumLabs Data Warehouse from individuals aged 16 years or older with OUD and commercial or Medicare Advantage coverage. Opioid use disorder was identified based on 1 or more inpatient or 2 or more outpatient claims for OUD diagnosis codes within 3 months of each other; 1 or more claims for OUD plus diagnosis codes for opioid-related overdose, injection-related infection, or inpatient detoxification or residential services; or MOUD claims between January 1, 2015, and September 30, 2017. Data analysis was performed from April 1, 2018, to June 30, 2019. Exposures One of 6 mutually exclusive treatment pathways, including (1) no treatment, (2) inpatient detoxification or residential services, (3) intensive behavioral health, (4) buprenorphine or methadone, (5) naltrexone, and (6) nonintensive behavioral health. Main Outcomes and Measures Opioid-related overdose or serious acute care use during 3 and 12 months after initial treatment. Results A total of 40 885 individuals with OUD (mean [SD] age, 47.73 [17.25] years; 22 172 [54.2%] male; 30 332 [74.2%] white) were identified. For OUD treatment, 24 258 (59.3%) received nonintensive behavioral health, 6455 (15.8%) received inpatient detoxification or residential services, 5123 (12.5%) received MOUD treatment with buprenorphine or methadone, 1970 (4.8%) received intensive behavioral health, and 963 (2.4%) received MOUD treatment with naltrexone. During 3-month follow-up, 707 participants (1.7%) experienced an overdose, and 773 (1.9%) had serious opioid-related acute care use. Only treatment with buprenorphine or methadone was associated with a reduced risk of overdose during 3-month (adjusted hazard ratio [AHR], 0.24; 95% CI, 0.14-0.41) and 12-month (AHR, 0.41; 95% CI, 0.31-0.55) follow-up. Treatment with buprenorphine or methadone was also associated with reduction in serious opioid-related acute care use during 3-month (AHR, 0.68; 95% CI, 0.47-0.99) and 12-month (AHR, 0.74; 95% CI, 0.58-0.95) follow-up. Conclusions and Relevance Treatment with buprenorphine or methadone was associated with reductions in overdose and serious opioid-related acute care use compared with other treatments. Strategies to address the underuse of MOUD are needed.

BACKGROUND/OBJECTIVES: Potentially inappropriate opioid prescribing (PIP) may contribute to risk for fatal opioid overdose among older adults (age 50+). Our objective was to examine the effect of age on the likelihood of PIP exposure, as well as the effect of PIP exposure on adverse outcomes. DESIGN: Retrospective cohort study SETTING: Data from multiple state agencies in Massachusetts, 2011–2015 PARTICIPANTS: Over 3 million adult Massachusetts residents (3,078,163) who received at least one prescription opioid during the study period; approximately half (1,589,365) were older adults (age 50+). MEASUREMENTS: We measured exposure to five types of PIP: high-dose opioids, co-prescription with benzodiazepines, multiple opioid prescribers, multiple opioid pharmacies, and continuous opioid therapy without a pain diagnosis. We examined three adverse outcomes: non-fatal opioid overdose, fatal opioid overdose, and all-cause mortality. RESULTS: The rate of any PIP exposure increased with age, ranging from 2% among individuals age 18–29 to 14% among those age 50 and older. Older adults also had elevated rates of exposure to two or more different types of PIP, including 5% of adults age 50–69 and 4% of adults age 70 or older, in comparison to 2.5% of age 40–49 and lower percentages in younger age groups. Among covariates assessed, increasing age was the greatest positive predictor of PIP exposure. In analyses stratified by age, exposure to both any PIP and specific types of PIP were associated with non-fatal overdose, fatal overdose, and all-cause mortality among both younger and older adults. CONCLUSION: Older adults are more likely to be exposed to PIP, which elevates their risk for adverse events. Strategies to reduce exposure to PIP, and to improve outcomes among those already exposed, will be instrumental to addressing the opioid crisis as it manifests among older adults.

BACKGROUND: Opioid-related overdoses and deaths among adolescents in the United States continue to increase, but little is known about adolescents who experience opioid-related non-fatal overdose (NFOD). Our objective was to describe (1) the characteristics of adolescents aged 11-17 who experienced NFOD and (2) their receipt of medications for opioid use disorder (MOUD) in the 12 months following NFOD, compared with adults. METHODS: We created a retrospective cohort using six Massachusetts state agency datasets linked at the individual level, with information on 98% of state residents. Individuals entered the cohort if they experienced NFOD between January 1, 2012 and December 31, 2014. We compared adolescents to adults experiencing NFOD, examining individual characteristics and receipt of medications for opioid use disorder (MOUD)—methadone, buprenorphine, or naltrexone. RESULTS: Among 22,506 individuals who experienced NFOD during the study period, 195 (0.9%) were aged 11-17. Fifty-two percent (102/195) of adolescents were female, whereas only 38% of adults were female (P