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IntroductionMore than 30 million adults are released from incarceration globally each year. Many experience complex physical and mental health problems, and are at markedly increased risk of preventable mortality. Despite this, evidence regarding the global epidemiology of mortality following release from incarceration is insufficient to inform the development of targeted, evidence-based responses. Many previous studies have suffered from inadequate power and poor precision, and even large studies have limited capacity to disaggregate data by specific causes of death, sub-populations or time since release to answer questions of clinical and public health relevance.ObjectivesTo comprehensively document the incidence, timing, causes and risk factors for mortality in adults released from prison.MethodsWe created the Mortality After Release from Incarceration Consortium (MARIC), a multi-disciplinary collaboration representing 29 cohorts of adults who have experienced incarceration from 11 countries. Findings across cohorts will be analysed using a two-step, individual participant data meta-analysis methodology.ResultsThe combined sample includes 1,337,993 individuals (89% male), with 75,795 deaths recorded over 9,191,393 person-years of follow-up.ConclusionsThe consortium represents an important advancement in the field, bringing international attention to this problem. It will provide internationally relevant evidence to guide policymakers and clinicians in reducing preventable deaths in this marginalized population.Key wordsMortality; incarceration; prison; release; individual participant data meta-analysis; consortium; cohort.

BACKGROUND: High mortality rates after release from prison have been well-documented, particularly from overdose. However, little is known about the risk factors for death after release from prison. Therefore, the objective of this study was to determine the demographic and incarceration-related risk factors for all-cause, overdose and early mortality after release from prison. METHODS: We conducted a retrospective cohort study of inmates released from a state prison system from 1999 through 2003. The cohort included 30,237 who had a total of 38,809 releases from prison. Potential risk factors included gender, race/ethnicity, age, length of incarceration, and community supervision. Cox proportional hazards regression was used to determine risk factors for all-cause, overdose and early (within 30 days of release) death after release from prison. RESULTS: Age over 50 was associated with an increased risk for all-cause mortality (hazard ratio [HR] 2.67 for each decade increase, 95% confidence interval [CI] 2.23, 3.20) but not for overdose deaths or early deaths. Latinos were at decreased risk of death compared to Whites only for all-cause mortality (HR 0.61, 95% CI 0.42, 0.87). Increasing years of incarceration were associated with a decreased risk of all-cause mortality (HR 0.95, 95% CI 0.91, 0.99) and overdose deaths (HR 0.80, 95% CI 0.68, 0.95), but not early deaths. Gender and type of release were not significantly associated with all-cause, overdose or early deaths. CONCLUSIONS: Age, ethnicity and length of incarceration were associated with mortality after release from prison. Interventions to reduce mortality among former inmates are needed. [ABSTRACT FROM AUTHOR]

Objective: Although soft tissue infections are common among injection drug users (IDUs), little is known about the health outcomes among those who seek care for these infections. Emergency department visits are an important point-of-health-care contact for IDUs. In this prospective cohort study, we aimed to determine the hospitalization and mortality rates and factors associated with hospitalization or death among IDUs seeking emergency care for soft tissue infection.Method: Participants were English-speaking IDUs, 18 years of age and older, who sought initial care for soft tissue infection in an urban emergency department. We conducted semistructured interviews, identified hospitalizations from hospital records, and identified deaths using the National Death Index. Cox proportional hazards regression was used to investigate associations between baseline characteristics and hospitalizations or death.Results: Of 211 eligible patients, 156 (74%) participated (mean age = 42 years). There were 255 subsequent hospitalizations over a mean of 3.9 years follow-up. The hospitalization rate was 42 hospitalizations per 100 person-years (95% confidence interval [CI]: 38-48). The mortality rate was 2.0 per 100 person-years (95% CI: 1.1-3.7). Factors associated with increased risk for hospitalization or death included living on the street or in a shelter (adjusted odds ratio [AOR] = 1.75, 95% CI: 1.10-2.79), being recently incarcerated (AOR = 1.90, 95% CI: 1.05-3.44), and having insurance (AOR: 1.98, 95% CI: 1.22-3.23).Conclusions: IDUs who sought care in the emergency department for soft tissue infections were at high risk for subsequent hospitalization and death. Visits for soft tissue infections represent missed opportunities for preventive care. [ABSTRACT FROM AUTHOR]

Background: The U.S. population of former prison inmates is large and growing. The period immediately after release may be challenging for former inmates and may involve substantial health risks. We studied the risk of death among former inmates soon after their release from Washington State prisons.Methods: We conducted a retrospective cohort study of all inmates released from the Washington State Department of Corrections from July 1999 through December 2003. Prison records were linked to the National Death Index. Data for comparison with Washington State residents were obtained from the Wide-ranging OnLine Data for Epidemiologic Research system of the Centers for Disease Control and Prevention. Mortality rates among former inmates were compared with those among other state residents with the use of indirect standardization and adjustment for age, sex, and race.Results: Of 30,237 released inmates, 443 died during a mean follow-up period of 1.9 years. The overall mortality rate was 777 deaths per 100,000 person-years. The adjusted risk of death among former inmates was 3.5 times that among other state residents (95% confidence interval [CI], 3.2 to 3.8). During the first 2 weeks after release, the risk of death among former inmates was 12.7 (95% CI, 9.2 to 17.4) times that among other state residents, with a markedly elevated relative risk of death from drug overdose (129; 95% CI, 89 to 186). The leading causes of death among former inmates were drug overdose, cardiovascular disease, homicide, and suicide.Conclusions: Former prison inmates were at high risk for death after release from prison, particularly during the first 2 weeks. Interventions are necessary to reduce the risk of death after release from prison. [ABSTRACT FROM AUTHOR]

Objective: Chronic opioid use can lead to detrimental effects on the immune and various organ systems that put individuals prescribed chronic opioid therapy (COT) for pain and those with an opioid use disorder (OUD) at risk for severe COVID-19 disease. We assessed the association of COT and OUD with COVID-19-related hospitalization and death to inform targeted interventions to improve clinical outcomes in COVID-19 patients who use opioids., Methods: We conducted a retrospective cohort study of adults ages ≥ 18 with laboratory-confirmed SARS-CoV-2 infection in 2020 and 2021 from three US health systems. We used Cox proportional hazards regression to estimate the 30-day risk of COVID-19-related hospitalization and death associated with two opioid exposures (COT and OUD) following an infection., Results: The study cohort included 53,123 patients with SARS-CoV-2 infection and a mean (SD) age of 45.1 (16.5), of whom 1,059 (2.0 %) were exposed to COT and 269 (0.5 %) had an OUD diagnosis in the year prior to infection. There were 2,270 observed COVID-19-related hospitalizations or deaths (1.6 per 1,000 person-days, 95 % CI 1.5-1.7). In the fully adjusted model, COT was not associated with increased risk (HR 1.19; 95 % CI, 0.98-1.43), while past-year OUD was independently associated with severe COVID-19 disease (HR 1.82; 95 % CI, 1.18-2.80). Past-year OUD remained associated with increased risk in post-hoc analysis with COVID-19-related hospitalization alone as the outcome (HR 2.00; 95 % CI, 1.30-3.08)., Conclusions: Past-year OUD is a potential independent risk factor for severe COVID-19 disease that warrants monitoring to improve the prognosis of patients with COVID-19., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Binswanger receives royalties for educational content on the health of incarcerated persons from UpToDate. Authors have disclosed no other conflicts of interest., (© 2024 The Author(s).)

Importance: Transitions in insurance coverage may be associated with worse health care outcomes. Little is known about insurance stability for individuals with opioid use disorder (OUD)., Objective: To examine insurance transitions among adults with newly diagnosed OUD in the 12 months after diagnosis., Design, Setting, and Participants: Longitudinal cohort study using data from the Massachusetts Public Health Data Warehouse. The cohort includes adults aged 18 to 63 years diagnosed with incident OUD between July 1, 2014, and December 31, 2014, who were enrolled in commercial insurance or Medicaid at diagnosis; individuals diagnosed after 2014 were excluded from the main analyses due to changes in the reporting of insurance claims. Data were analyzed from November 10, 2022, to May 6, 2024., Exposure: Insurance type at time of diagnosis (commercial and Medicaid)., Main Outcomes and Measures: The primary outcome was the cumulative incidence of insurance transitions in the 12 months after diagnosis. Logistic regression models were used to generate estimated probabilities of insurance transitions by insurance type and diagnosis for several characteristics including age, race and ethnicity, and whether an individual started medication for OUD (MOUD) within 30 days after diagnosis., Results: There were 20 768 individuals with newly diagnosed OUD between July 1, 2014, and December 31, 2014. Most individuals with newly diagnosed OUD were covered by Medicaid (75.4%). Those with newly diagnosed OUD were primarily male (67% in commercial insurance, 61.8% in Medicaid). In the 12 months following OUD diagnosis, 30.4% of individuals experienced an insurance transition, with adjusted models demonstrating higher transition rates among those starting with Medicaid (31.3%; 95% CI, 30.5%-32.0%) compared with commercial insurance (27.9%; 95% CI, 26.6%-29.1%). The probability of insurance transitions was generally higher for younger individuals than older individuals irrespective of insurance type, although there were notable differences by race and ethnicity., Conclusions and Relevance: This study found that nearly 1 in 3 individuals experience insurance transitions in the 12 months after OUD diagnosis. Insurance transitions may represent an important yet underrecognized factor in OUD treatment outcomes.

The association between SARS-CoV-2 humoral immunity and post-acute sequelae of COVID-19 (long COVID) remains uncertain. The objective of this population-based cohort study was to assess the association between SARS-CoV-2 seropositivity and symptoms consistent with long COVID. English and Spanish-speaking members ≥ 18 years old with SARS-CoV-2 serologic testing conducted prior to August 2021 were recruited from Kaiser Permanente Southern California and Kaiser Permanente Colorado. Between November 2021 and April 2022, participants completed a survey assessing symptoms, physical health, mental health, and cognitive function consistent with long COVID. Survey results were linked to SARS-CoV-2 antibody (Ab) and viral (RNA) lab results in electronic health records. Weighted descriptive analyses were generated for five mutually exclusive patient groups: (1) +Ab/+RNA; (2) +Ab/- or missing RNA; (3) -Ab/+RNA; (4a) -Ab/-RNA reporting no prior infection; and (4b) -Ab/-RNA reporting prior infection. The proportions reporting symptoms between the +Ab/+RNA and -Ab/+RNA groups were compared, adjusted for covariates. Among 3,946 participants, the mean age was 52.1 years old (SD 15.6), 68.3% were female, 28.4% were Hispanic, and the serologic testing occurred a median of 15 months prior (IQR = 12-18). Three quarters (74.5%) reported having had COVID-19. Among people with laboratory-confirmed COVID-19, there was no association between antibody positivity (+Ab/+RNA vs. -Ab/+RNA) and any symptoms, physical health, mental health, or cognitive function. As expected, physical health, cognitive function, and fatigue were worse, and palpitations and headaches limiting the ability to work were more prevalent among people with laboratory-confirmed prior infection and positive serology (+Ab/+RNA) compared to those without reported or confirmed prior infection and negative serology (-Ab/-RNA/no reported COVID-19). Among people with laboratory-confirmed COVID-19, SARS-CoV-2 serology from practice settings were not associated with long COVID symptoms and health status suggesting limited utility of serology testing for long COVID., Competing Interests: “I have read the journal’s policy and the authors of this manuscript have the following competing interests: Dr. Binswanger received royalties from UpToDate (Wolters Kluwer) for unrelated educational content on the health of incarcerated persons. Dr. Bruxvoort has received funding from Moderna, Pfizer, Dynavax, Gilead, and GlaxoSmithKline for unrelated research. This commercial funding does not alter our adherence to PLOS ONE policies on sharing data and materials. All other authors have declared that no competing interests exist.”, (Copyright: © 2024 Binswanger et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objective: The Centers for Disease Control and Prevention's 2022 Clinical Practice Guideline for Prescribing Opioids for Pain cautioned that inflexible opioid prescription duration limits may harm patients. Information about the relationship between initial opioid prescription duration and a subsequent refill could inform prescribing policies and practices to optimize patient outcomes. We assessed the association between initial opioid duration and an opioid refill prescription., Methods: We conducted a retrospective cohort study of adults ≥19 years of age in 10 US health systems between 2013 and 2018 from outpatient care with a diagnosis for back pain without radiculopathy, back pain with radiculopathy, neck pain, joint pain, tendonitis/bursitis, mild musculoskeletal pain, severe musculoskeletal pain, urinary calculus, or headache. Generalized additive models were used to estimate the association between opioid days' supply and a refill prescription., Results: Overall, 220,797 patients were prescribed opioid analgesics upon an outpatient visit for pain. Nearly a quarter (23.5%) of the cohort received an opioid refill prescription during follow-up. The likelihood of a refill generally increased with initial duration for most pain diagnoses. About 1 to 3 fewer patients would receive a refill within 3 months for every 100 patients initially prescribed 3 vs. 7 days of opioids for most pain diagnoses. The lowest likelihood of refill was for a 1-day supply for all pain diagnoses, except for severe musculoskeletal pain (9 days' supply) and headache (3-4 days' supply)., Conclusions: Long-term prescription opioid use increased modestly with initial opioid prescription duration for most but not all pain diagnoses examined., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: together to conduct postmarketing studies required by the Food and Drug Administration that assess risks related to opioid analgesic use. Dr. Andrade has received research support on grants to the University of Massachusetts Chan Medical School from Pfizer, Inc., GlaxoSmithKline, and the Reagan-Udall Foundation, and consulting fees from Corevitas LLC. Dr. Binswanger receives royalties for educational content on the health of incarcerated persons from UpToDate. Ms. Rosa was substantially involved in the study, consistent with her role as Scientific Officer. She had no substantial involvement in the other cited grants., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Medical cannabis is commonly used for chronic pain, but little is known about differences in characteristics, cannabis use patterns, and perceived helpfulness among primary care patients who use cannabis for pain versus nonpain reasons., Methods: Among 1688 patients who completed a 2019 cannabis survey administered in a health system in Washington state, where recreational use is legal, participants who used cannabis for pain (n = 375) were compared with those who used cannabis for other reasons (n = 558) using survey and electronic health record data. We described group differences in participant characteristics, use patterns, and perceptions and applied adjusted multinomial logistic and modified Poisson regression., Results: Participants who used cannabis for pain were significantly more likely to report using applied (50.7% vs 10.6%) and beverage cannabis products (19.2% vs 11.6%), more frequent use (47.1% vs 33.1% for use ≥2 times per day; 81.6% vs 69.7% for use 4 to 7 days per week), and smoking tobacco cigarettes (19.2% vs 12.2%) than those who used cannabis for other reasons. They were also significantly more likely to perceive cannabis as very/extremely helpful (80.5% vs 72.7%), and significantly less likely to use cannabis for nonmedical reasons (4.8% vs 58.8%) or report cannabis use disorder symptoms (51.7% vs 61.1%)., Discussion: Primary care patients who use cannabis for pain use it more frequently, often in applied and ingested forms, and have more co-use of tobacco, which may differentially impact safety and effectiveness. These findings suggest the need for different approaches to counseling in clinical care., Competing Interests: Conflict of interest: Ms. Ford, Dr. Lapham, Dr. Matson, Ms. Luce, and Ms. Oliver have no conflicts of interest to declare. Dr. Binswanger received royalties from UptoDate (Wolters Kluwer) and is employed by the Colorado Permanente Medical Group, which provides primary care and specialty care. She has no other conflicts of interest to declare., (© Copyright by the American Board of Family Medicine.)

Purpose: The aim of this study is to use electronic opioid dispensing data to develop an individual segmented trajectory approach for identifying opioid use patterns. The resulting opioid use patterns can be used for examining the association between opioid use and drug overdose., Methods: We retrospectively assembled a cohort of members on long-term opioid therapy (LTOT) between January 1, 2006 and June 30, 2019 who were 18 years and older and enrolled in one of three health care systems in the US. We have developed an individual segmented trajectory analysis for identifying various opioid use patterns by scanning over the follow-up and finding distinct opioid use patterns based on variability measured with coefficient of variation and trends of milligram morphine equivalents levels., Results: Among 31, 865 members who were on LTOT between January 1, 2006 and June 30, 2019, 58.3% were female, and the average age was 55.4 years (STD = 15.4). The study population had 152 557 person-years of follow-up, with an average follow-up of 4.4 years per enrollment per person (STD = 3.4). This novel approach identified up to 13 distinct patterns including 88 756 episodes of "stable" pattern (42.1%) with an average follow-up of 11.2 months, 29 140 episodes of "increasing" pattern (13.8%) with an average follow-up of 6.0 months, 13 201 episodes of ≤10% dose reduction (6.3%) with an average follow-up of 10.4 months, 7286 episodes of 11%-20% dose reduction (3.5%) with an average follow-up of 5.3 months, 4457 episodes of 21%-30% dose reduction (2.1%) with an average follow-up of 4.0 months, and 9903 episodes of >30% dose reduction (4.7%) with an average follow-up of 2.6 months., Conclusions: A novel approach was developed to identify 13 distinct opioid use patterns using each individual's longitudinal dispensing data and these patterns can be used in examining overdose risk during the time that these patterns are ongoing., (© 2023 John Wiley & Sons Ltd.)

The association between the presence of detectable antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and SARS-CoV-2 reinfection is not well established. The objective of this study was to determine the association between antibody seronegativity and reinfection., Methods: Participants in Colorado, USA, were recruited between June 15, 2020, and March 28, 2021, and encouraged to complete SARS-CoV-2 molecular ribonucleic acid (RNA) and serology testing for antibodies every 28 days for 10 months. Participants with reinfections (positive SARS-CoV-2 RNA test ≥ 90 days after the first positive RNA test) were matched to controls without reinfections by age, sex, date of the first positive RNA test, date of the last serology test, and serology test type. Using conditional logistic regression, case patients were compared to control patients on the last serologic test result, with adjustment for demographic and clinical confounders., Results: The cohort (n = 4,235) included 2,033 participants with ≥ 1 positive RNA test, of whom 120 had reinfection. Among the 80 case patients who could be matched, the last serologic test was negative in 12 of the cases (15.0 %) whereas the last serologic test was negative in 77 of 1,034 (7.5 %) controls. Seronegativity (adjusted OR [aOR] 2.24; 95 % CI 1.07, 4.68), Hispanic ethnicity (aOR 1.87; 95 % 1.10, 3.18), and larger household size (aOR 1.15; 95 % 1.01, 1.30 for each additional household member) were associated with reinfection., Conclusions: Seronegative status, Hispanic ethnicity, and increasing household size were associated with reinfection. Serologic testing could be considered to reduce vaccine hesitancy in higher risk populations., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Bechtel was employed at Kaiser Permanente Colorado at the time this study was conducted through November 2022 and is currently employed by Siemens Healthineers, USA, which had no role in the study design, analysis, manuscript preparation or review, or decision to submit for publication. All other authors declare that they do not have a conflict of interest., (© 2023 The Authors.)

Objective: Spinal cord injury (SCI) is a life-altering neurological condition affecting physical and psycho-social functioning and associated high rates of pain. Thus, individuals with SCI may be more likely to be exposed to prescription opioids. A scoping review was conducted to synthesize published research findings on post-acute SCI and prescription opioid use for pain, identify literature gaps, and propose recommendations for future research., Methods: We searched 6 electronic bibliographic databases (PubMed [MEDLINE], Ovid [MEDLINE], EMBASE, Cochrane Library, CINAHL, PsychNET) for articles published from 2014 through 2021. Terms for "spinal cord injury" and "prescription opioid use" were used. Included articles were in English and peer reviewed. Data were extracted using an electronic database by 2 independent reviewers. Opioid use risk factors for chronic SCI were identified and a gap analysis was performed., Results: Of the 16 articles included in the scoping review, a majority were conducted in the United States (n = 9). Most articles lacked information on income (87.5%), ethnicity (87.5%), and race (75%). Prescription opioid use ranged from 35% to 64% in articles reporting this information (n = 7 articles, n = 3675 participants). Identified risk factors for opioid use included middle age, lower income, osteoarthritis diagnosis, prior opioid use, and lower-level spinal injury. Limited reporting of diversity in study populations, absence of risk of polypharmacy, and limited high quality methodology were identified gaps., Conclusions: Future research should report data on prescription opioid use in SCI populations, with additional demographics such as race, ethnicity, and income, given their importance to risk outcomes., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Clinical opioid overdose risk prediction models can be useful tools to reduce the risk of overdose in patients prescribed long-term opioid therapy (LTOT). However, evolving overdose risk environments and clinical practices in addition to potential harmful model misapplications require careful assessment prior to widespread implementation into clinical care. Models may need to be tailored to meet local clinical operational needs and intended applications in practice., Objective: To update and validate an existing opioid overdose risk model, the Kaiser Permanente Colorado Opioid Overdose (KPCOOR) Model, in patients prescribed LTOT for implementation in clinical care., Design, Setting, and Participants: The retrospective cohort study consisted of 33, 625 patients prescribed LTOT between January 2015 and June 2019 at Kaiser Permanente Colorado, with follow-up through June 2021., Main Measures: The outcome consisted of fatal opioid overdoses identified from vital records and non-fatal opioid overdoses from emergency department and inpatient settings. Predictors included demographics, medication dispensings, substance use disorder history, mental health history, and medical diagnoses. Cox proportional hazards regressions were used to model 2-year overdose risk., Key Results: During follow-up, 65 incident opioid overdoses were observed (111.4 overdoses per 100,000 person-years) in the study cohort, of which 11 were fatal. The optimal risk model needed to risk-stratify patients and to be easily interpreted by clinicians. The original 5-variable model re-validated on the new study cohort had a bootstrap-corrected C-statistic of 0.73 (95% CI, 0.64-0.85) compared to a C-statistic of 0.80 (95% CI, 0.70-0.88) in the updated model and 0.77 (95% CI, 0.66-0.87) in the final adapted 7-variable model, which was also well-calibrated., Conclusions: Updating and adapting predictors for opioid overdose in the KPCOOR Model with input from clinical partners resulted in a parsimonious and clinically relevant model that was poised for integration in clinical care., (© 2023. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Background: Individuals prescribed long-term opioid therapy (LTOT) have increased risk of readmission and death after hospital discharge. The risk of opioid overdose during the immediate post-discharge time period is unknown., Objective: To examine the association between time since hospital discharge and opioid overdose among individuals prescribed LTOT., Design: Self-controlled risk interval analysis., Participants: Adults prescribed LTOT with at least one hospital discharge at a safety-net health system and a non-profit healthcare organization in Colorado., Main Measures: We identified individuals prescribed LTOT who were discharged from January 2006 through June 2019. The outcome was a composite of fatal and non-fatal opioid overdoses during a 90-day post-discharge observation period, identified using electronic health record (EHR) and vital statistics data. Risk intervals included days 0-6 after index and subsequent hospital discharges. Control intervals ranged from days 7 to 89 after index discharge and included all other time during the observation period that did not fall within a risk interval or time readmitted during a subsequent hospitalization, which was excluded. Poisson regression was used to estimate incidence rate ratios (IRR) and 95% confidence intervals (CI) for overdose events during risk in comparison to control intervals., Key Results: We identified 7695 adults (63.3% over 55 years, 59.4% female, 20.3% Hispanic) who experienced 9499 total discharges during the study period. Twenty-one overdoses occurred during their observation periods (1174 per 100,000 person-years [9 in risk, 12 in control]). Overdose risk was significantly higher during the risk interval in comparison to the control interval (IRR 6.92; 95% CI 2.92-16.43)., Conclusion: During the first 7 days after hospital discharge, individuals prescribed LTOT appear to be at elevated risk for opioid overdose. Clarifying mechanisms of overdose risk may help inform in-hospital and post-discharge prevention strategies., (© 2023. The Author(s), under exclusive licence to Society of General Internal Medicine.)

Background: Tapering long-term opioid therapy is an increasingly common practice, yet rapid opioid dose reductions may increase the risk of overdose. The objective of this study was to compare overdose risk following opioid dose reduction rates of ≤10%, 11% to 20%, 21% to 30%, and >30% per month to stable dosing., Methods: We conducted a retrospective cohort study in three health systems in Colorado and Wisconsin. Participants were patients ≥18 years of age prescribed long-term opioid therapy between January 1, 2006, and June 30, 2019. Five opioid dosing patterns and drug overdoses (fatal and nonfatal) were identified using electronic health records, pharmacy records, and the National Death Index. Cox proportional hazard regression was conducted on a propensity score-weighted cohort to estimate adjusted hazard ratios (aHRs) for follow-up periods of 1, 3, 6, 9, and 12 months after a dose reduction., Results: In a cohort of 17 540 patients receiving long-term opioid therapy, 42.7% of patients experienced a dose reduction. Relative to stable dosing, a dose reduction rate of >30% was associated with an increased risk of overdose and the aHR estimates decreased as the follow-up increased; the aHRs for the 1-, 6- and 12-month follow-ups were 5.33 (95% CI, 1.98-14.34), 1.81 (95% CI,1.08-3.03), and 1.49 (95% CI, 0.97-2.27), respectively. The slower tapering rates were not associated with overdose risk., Conclusions: Patients receiving long-term opioid therapy exposed to dose reduction rates of >30% per month had increased overdose risk relative to patients exposed to stable dosing. Results support the use of slow dose reductions to minimize the risk of overdose., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Dr. Binswanger receives royalties for educational content on the health of incarcerated persons from UpToDate. The authors have disclosed no other conflicts of interest.

Background and Aims: Buprenorphine is an effective medication for opioid use disorder that reduces mortality; however, many patients are not retained in buprenorphine treatment, and an optimal length of treatment after which patients can safely discontinue treatment has not been identified. This study measured the association between buprenorphine treatment duration and all-cause mortality among patients who discontinued treatment. Secondary objectives were to measure the association between treatment duration and drug overdose and opioid-related overdoses., Design: Multi-site cohort study., Setting: Eight US health systems., Participants: Patients who initiated and discontinued buprenorphine treatment between 1 January 2012 and 31 December 2018 (n = 6550). Outcomes occurring after patients discontinued buprenorphine treatment were compared between patients who initiated and discontinued treatment after 8-30, 31-90, 91-180, 181-365 and > 365 days., Measurements: Covariate data were obtained from electronic health records (EHRs). Mortality outcomes were derived from EHRs and state vital statistics. Non-fatal opioid and drug overdoses were obtained from diagnostic codes. Four sites provided cause-of-death data to identify fatal drug and opioid-related overdoses. Adjusted frailty regression was conducted on a propensity-weighted cohort to assess associations between duration of the final treatment episode and outcomes., Findings: The mortality rate after buprenorphine treatment was 1.82 per 100 person-years (n = 191 deaths). In regression analyses with > 365 days as the reference group, treatment duration was not associated with all-cause mortality and drug overdose (P > 0.05 for both). However, compared with > 365 days of treatment, 91-180 days of treatment was associated with increased opioid overdose risk (hazard ratio = 2.94, 95% confidence interval = 1.11-7.79)., Conclusions: Among patients who discontinue buprenorphine treatment, there appears to be no treatment duration period associated with a reduced risk for all-cause mortality. Patients who discontinue buprenorphine treatment after 91-180 days appear to be at heightened risk for opioid overdose compared with patients who discontinue after > 365 days of treatment., (© 2022 The Authors. Addiction published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.)

Objective: The authors sought to characterize the 3-year prevalence of mental disorders and nonnicotine substance use disorders among male and female primary care patients with documented opioid use disorder across large U.S. health systems., Methods: This retrospective study used 2014-2016 data from patients ages ≥16 years in six health systems. Diagnoses were obtained from electronic health records or claims data; opioid use disorder treatment with buprenorphine or injectable extended-release naltrexone was determined through prescription and procedure data. Adjusted prevalence of comorbid conditions among patients with opioid use disorder (with or without treatment), stratified by sex, was estimated by fitting logistic regression models for each condition and applying marginal standardization., Results: Females (53.2%, N=7,431) and males (46.8%, N=6,548) had a similar prevalence of opioid use disorder. Comorbid mental disorders among those with opioid use disorder were more prevalent among females (86.4% vs. 74.3%, respectively), whereas comorbid other substance use disorders (excluding nicotine) were more common among males (51.9% vs. 60.9%, respectively). These differences held for those receiving medication treatment for opioid use disorder, with mental disorders being more common among treated females (83% vs. 71%) and other substance use disorders more common among treated males (68% vs. 63%). Among patients with a single mental health condition comorbid with opioid use disorder, females were less likely than males to receive medication treatment for opioid use disorder (15% vs. 20%, respectively)., Conclusions: The high rate of comorbid conditions among patients with opioid use disorder indicates a strong need to supply primary care providers with adequate resources for integrated opioid use disorder treatment.

Importance: Uncertainty remains about the longer-term benefits and harms of different opioid management strategies, such as tapering and dose escalation. For instance, opioid tapering could help patients reduce opioid exposure to prevent opioid use disorder, but patients may also seek care elsewhere and engage in nonprescribed opioid use., Objective: To evaluate the association between opioid dose trajectories observed in practice and patient outcomes., Design, Setting, and Participants: This retrospective cohort study was conducted in 3 health systems in Colorado and Wisconsin. The study population included patients receiving long-term opioid therapy between 50 and 200 morphine milligram equivalents between August 1, 2014, and July 31, 2017. Follow-up ended on December 31, 2019. Data were analyzed from January 2020 to August 2022., Exposures: Group-based trajectory modeling identified 5 dosing trajectories over 1 year: 1 decreasing, 1 high-dose increasing, and 3 stable., Main Outcomes and Measures: Primary outcomes assessed after the trajectory period were 1-year all-cause mortality, incident opioid use disorder, continued opioid therapy at 1 year, and health plan disenrollment. Associations were tested using Cox proportional hazards regression and log-binomial models, adjusting for baseline covariates., Results: A total of 3913 patients (mean [SD] age, 59.2 [14.4] years; 2767 White non-Hispanic [70.7%]; 2237 female patients [57.2%]) were included in the study. Compared with stable trajectories, the decreasing dose trajectory was negatively associated with opioid use disorder (adjusted hazard ratio [aHR], 0.40; 95% CI, 0.29-0.55) and continued opioid therapy (site 1: adjusted relative risk [aRR], 0.39; 95% CI, 0.34-0.44), but was positively associated with health plan disenrollment (aHR, 1.66; 95% CI, 1.24-2.22). The decreasing trajectory was not associated with mortality (aHR, 1.28; 95% CI, 0.87-1.86). In contrast, the high-dose increasing trajectory was positively associated with mortality (aHR, 2.19; 95% CI, 1.44-3.32) and opioid use disorder (aHR, 1.81; 95% CI, 1.39-2.37) but was not associated with disenrollment (aHR, 0.90; 95% CI, 0.56-1.42) or continued opioid therapy (site 1: aRR, 0.98; 95% CI, 0.94-1.03)., Conclusions and Relevance: In this cohort study, decreasing opioid dose was associated with reduced risk of opioid use disorder and continued opioid therapy but increased risk of disenrollment compared with stable dosing, whereas the high-dose increasing trajectory was associated with an increased risk of mortality and opioid use disorder. These findings can inform opioid management decision-making.

Background: Hospitalizations related to opioid use disorder (OUD) are rising. Addiction consultation services (ACS) increasingly provide OUD treatment to hospitalized patients, but barriers to initiating and continuing medications for OUD remain. We examined facilitators and barriers to hospital-based OUD treatment initiation and continuation from the perspective of patients and healthcare workers in the context of an ACS., Methods: In this qualitative study, we sought input using key informant interviews and focus groups from patients who received care from an ACS during their hospitalization and from hospitalists, pharmacists, social workers, and nurses who work in the hospital setting. A multidisciplinary team coded and analyzed transcripts using a directed content analysis., Findings: We conducted 20 key informant interviews with patients, nine of whom were interviewed following hospital discharge and 12 of whom were interviewed during a rehospitalization. We completed six focus groups and eight key informant interviews with hospitalists and hospital-based medical staff (n = 62). Emergent themes related to hospital-based OUD treatment included the following: the benefit of an ACS to facilitate OUD treatment engagement; expanded use of methadone or buprenorphine to treat opioid withdrawal; the triad of hospitalization, self-efficacy, and easily accessible, patient-centered treatment motivates change in opioid use; adequate pain control and stabilization of mental health conditions among patients with OUD contributed to opioid agonist therapy (OAT) continuation; and stable housing and social support are prerequisites for OAT uptake and continuation., Conclusion: Modifiable factors which facilitate hospital-based OUD treatment initiation and continuation include availability of in-hospital addiction expertise to offer easily accessible, patient-centered treatment and the use of methadone or buprenorphine to manage opioid withdrawal. Further research and public policy efforts are urgently needed to address reported barriers to hospital-based OUD treatment initiation and continuation which include unstable housing, poorly controlled chronic medical and mental illness, and lack of social support., (© 2021. The Author(s) under exclusive licence to Society of General Internal Medicine.)

Background: Although naloxone prevents opioid overdose deaths, few patients prescribed opioids receive naloxone, limiting its effectiveness in real-world settings. Barriers to naloxone prescribing include concerns that naloxone could increase risk behavior and limited time to provide necessary patient education., Objective: To determine whether pharmacy-based naloxone co-dispensing affected opioid risk behavior. Secondary objectives were to assess if co-dispensing increased naloxone acquisition, increased patient knowledge about naloxone administration, and affected opioid dose and other substance use., Design: Cluster randomized pragmatic trial of naloxone co-dispensing., Setting: Safety-net health system in Denver, Colorado, between 2017 and 2020., Participants: Seven pharmacies were randomized. Pharmacy patients (N=768) receiving opioids were followed using automated data for 10 months. Pharmacy patients were also invited to complete surveys at baseline, 4 months, and 8 months; 325 survey participants were enrolled from November 15, 2017, to January 8, 2019., Intervention: Intervention pharmacies implemented workflows to co-dispense naloxone while usual care pharmacies provided usual services., Main Measures: Survey instruments assessed opioid risk behavior; hazardous drinking; tobacco, cannabis, and other drug use; and knowledge. Naloxone dispensings and opioid dose were evaluated using pharmacy data among pharmacy patients and survey participants. Intention-to-treat analyses were conducted using generalized linear mixed models accounting for clustering at the pharmacy level., Key Results: Opioid risk behavior did not differ by trial group (P=0.52; 8-month vs. baseline adjusted risk ratio [ARR] 1.07; 95% CI 0.78, 1.47). Compared with usual care pharmacies, naloxone dispensings were higher in intervention pharmacies (ARR 3.38; 95% CI 2.21, 5.15) and participant knowledge increased (P=0.02; 8-month vs. baseline adjusted mean difference 1.05; 95% CI 0.06, 2.04). There was no difference in other substance use by the trial group., Conclusion: Co-dispensing naloxone with opioids effectively increased naloxone receipt and knowledge but did not increase self-reported risk behavior., Trial Registration: Registered at ClinicalTrials.gov ; Identifier: NCT03337100., (© 2022. The Author(s) under exclusive licence to Society of General Internal Medicine.)

Importance: Patients who use cannabis for medical reasons may benefit from discussions with clinicians about health risks of cannabis and evidence-based treatment alternatives. However, little is known about the prevalence of medical cannabis use in primary care and how often it is documented in patient electronic health records (EHR)., Objective: To estimate the primary care prevalence of medical cannabis use according to confidential patient survey and to compare the prevalence of medical cannabis use documented in the EHR with patient report., Design, Setting, and Participants: This study is a cross-sectional survey performed in a large health system that conducts routine cannabis screening in Washington state where medical and nonmedical cannabis use are legal. Among 108 950 patients who completed routine cannabis screening (between March 28, 2019, and September 12, 2019), 5000 were randomly selected for a confidential survey about cannabis use, using stratified random sampling for frequency of past-year use and patient race and ethnicity. Data were analyzed from November 2020 to December 2021., Exposures: Survey measures of patient-reported past-year cannabis use, medical cannabis use (ie, explicit medical use), and any health reason(s) for use (ie, implicit medical use)., Main Outcomes and Measures: Survey data were linked to EHR data in the year before screening. EHR measures included documentation of explicit and/or implicit medical cannabis use. Analyses estimated the primary care prevalence of cannabis use and compared EHR-documented with patient-reported medical cannabis use, accounting for stratified sampling and nonresponse., Results: Overall, 1688 patients responded to the survey (34% response rate; mean [SD] age, 50.7 [17.5] years; 861 female [56%], 1184 White [74%], 1514 non-Hispanic [97%], and 1059 commercially insured [65%]). The primary care prevalence of any past-year patient-reported cannabis use on the survey was 38.8% (95% CI, 31.9%-46.1%), whereas the prevalence of explicit and implicit medical use were 26.5% (95% CI, 21.6%-31.3%) and 35.1% (95% CI, 29.3%-40.8%), respectively. The prevalence of EHR-documented medical cannabis use was 4.8% (95% CI, 3.45%-6.2%). Compared with patient-reported explicit medical use, the sensitivity and specificity of EHR-documented medical cannabis use were 10.0% (95% CI, 4.4%-15.6%) and 97.1% (95% CI, 94.4%-99.8%), respectively., Conclusions and Relevance: These findings suggest that medical cannabis use is common among primary care patients in a state with legal use, and most use is not documented in the EHR. Patient report of health reasons for cannabis use identifies more medical use compared with explicit questions about medical use.

Background: Hospitalizations for complications related to opioid use disorder (OUD) are increasing. Hospitalists care for most hospitalized patients in the United States, yet little is known about their attitudes, beliefs, and clinical practices regarding OUD-related care., Methods: We distributed an online survey to hospitalists in the United States to measure how access to addiction specialists affected attitudes and beliefs regarding hospital-based OUD care, OUD screening practices, naloxone prescribing, and buprenorphine initiation., Results: Among 262 respondents, 67.9% ( n  = 178) reported having access to addiction specialists. While 84.5% ( n  = 221) reported often or always caring for patients with OUD, 48.2% ( n  = 126) rarely or never screened for OUD, 57.1% ( n  = 149) rarely or never prescribed or recommended naloxone as harm reduction, and 88.9% ( n  = 233) rarely or never initiated buprenorphine. In multivariable analyses, compared to hospitalists without access to addiction specialists, hospitalist with access to addiction specialists were more likely to feel supported to screen and refer patients to treatment (aOR = 4.4, 95% CI 2.1 - 9.1; ρ  < 0.001), to be aware of local treatment resources (aOR = 3.4, 95% CI 1.8 - 6.3; ρ  < 0.001), and refer patients to treatment (aOR = 3.0, 95% CI 1.7 - 5.6; ρ  < 0.001)., Conclusions: Many hospitalists do not provide life-saving treatment to patients with OUD. Access to addiction specialists may increase provision of OUD-related care by hospitalists.

Background: Most states have legalized medical cannabis, yet little is known about how medical cannabis use is documented in patients' electronic health records (EHRs). We used natural language processing (NLP) to calculate the prevalence of clinician-documented medical cannabis use among adults in an integrated health system in Washington State where medical and recreational use are legal. Methods: We analyzed EHRs of patients ≥18 years old screened for past-year cannabis use (November 1, 2017-October 31, 2018), to identify clinician-documented medical cannabis use. We defined medical use as any documentation of cannabis that was recommended by a clinician or described by the clinician or patient as intended to manage health conditions or symptoms. We developed and applied an NLP system that included NLP-assisted manual review to identify such documentation in encounter notes. Results: Medical cannabis use was documented for 16,684 (5.6%) of 299,597 outpatient encounters with routine screening for cannabis use among 203,489 patients seeing 1,274 clinicians. The validated NLP system identified 54% of documentation and NLP-assisted manual review the remainder. Language documenting reasons for cannabis use included 125 terms indicating medical use, 28 terms indicating non-medical use and 41 ambiguous terms. Implicit documentation of medical use (e.g., "edible THC nightly for lumbar pain ") was more common than explicit (e.g., "continues medical cannabis use"). Conclusions: Clinicians use diverse and often ambiguous language to document patients' reasons for cannabis use. Automating extraction of documentation about patients' cannabis use could facilitate clinical decision support and epidemiological investigation but will require large amounts of gold standard training data.

Background and Aims: To estimate during pregnancy correlations between frequency of self-reported use of marijuana and quantified marijuana metabolite in biospecimens including urine, sera and umbilical cord homogenate., Design: Prospective cohort., Setting: Two urban hospitals in Colorado with legal recreational and medicinal marijuana., Participants: Pregnant women (<16 weeks gestation) self-reporting marijuana use., Measurements: Participants completed a written self-report survey and provided biospecimens at <16 weeks gestation (n = 46), 18 to 22 weeks gestation (n = 43), 32 to 36 weeks gestation (n = 39), and delivery (n = 37). Self-reported marijuana use frequency was calculated based on past-month days of use multiplied by number of daily uses. Maternal urine and sera were tested for presence (>5 ng/mL) of 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH). Liquid chromatography tandem mass spectrometry quantified THC-COOH in umbilical cord homogenate (ng/g). Last marijuana use by any measure was recorded to evaluate the time frame over which THC-COOH remains detectable (>0.10 ng/g) in cord., Findings: From December 2017 through May 2019, 51 pregnant women enrolled, and 46 were included in analyses (2 withdrew and 3 had a spontaneous abortion). The majority were normal weight, White or Black race, and insured by Medicaid. At the time of enrollment between 7 to 15 weeks' gestation, 87% had ongoing use by self-report, or positive urine or serum. The majority (33 [66%]) stopped using before delivery. Sera and urine results were strongly correlated with self-reported use frequency (Spearman correlation coefficient [r] range 0.70-0.87 across visits, P < 0.001), and with each other. There was only one positive cord result when use stopped before 22 weeks. Frequency of self-reported marijuana use at delivery had strong correlation with quantified cord THC-COOH (r = 0.80, 95% CI = 0.62-0.89)., Conclusions: Quantified umbilical cord THC-COOH appears to strongly correlate with frequency of maternal marijuana use in the last month of pregnancy. Earlier use can be measured by either quantitative urine or serum assay., (© 2021 Society for the Study of Addiction.)

Background: Medications for opioid use disorder (MOUD) are clinically effective at treating OUD among legal-involved populations. However, research shows that legal-involved veterans who receive care through the VHA have lower rates of MOUD use compared to non-legal-involved veterans. Education may be a key factor in intervention strategies to improve MOUD access. This study was a national survey of VHA staff to identify barriers to and facilitators of MOUD, as well as MOUD-related education needs for VHA staff, community partners, criminal justice partners, and legal-involved veterans. Method : A 98-item online survey was conducted to examine VHA staff perspectives ( N  = 218) around needed education, barriers to, and facilitators of MOUD for legal-involved veterans. Descriptive statistics were conducted and linear regression analyses were used to evaluate differences in perceptions by respondents' current position at the VHA and their VHA facility's rate of provision of MOUD among legal-involved veterans. Results : Respondents endorsed a need for education in all areas of MOUD (e.g., existing medications for the treatment of OUD) for VHA staff and providers, community partners, criminal justice partners, and legal-involved veterans. VHA staff perceived barriers to MOUD for legal-involved veterans to include stigma and complicated guidelines around MOUD and OUD treatment. Facilities with low rates of MOUD use highlighted barriers including MOUD conflicting with the philosophy of the local VHA facility and provider stigma toward patients with OUD. Perceptions of efficacy of MOUD differed by respondents' current position at the VHA such that substance use disorder treatment providers perceived buprenorphine and methadone as more effective compared to Veterans Justice Specialists. Conclusion : The results of this study suggest a need for an educational intervention emphasizing the evidence supporting use of MOUD as a lack of knowledge about these medications was considered a barrier to access, whereas gaining education about MOUD was a facilitator to access. Education strategies specifically tailored to address VHA facility-level differences may help address barriers to MOUD experienced by legal-involved veterans.

Background: Youth are vulnerable to opioid use initiation and its complications. With growing rates of opioid overdose, strategies to identify youth at risk of opioid use disorder (OUD) to efficiently focus prevention interventions are needed. This study developed and validated a prediction model of OUD in youth aged 14-18 years., Methods: The model was developed in a Colorado healthcare system (derivation site) using Cox proportional hazards regression analysis. Model predictors and outcomes were identified using electronic health record data. The model was externally validated in a separate Denver safety net health system (validation site). Youth were followed for up to 3.5 years. We evaluated internal and external validity using discrimination and calibration., Results: The derivation cohort included 76,603 youth, of whom 108 developed an OUD diagnosis. The model contained 3 predictors (smoking status, mental health diagnosis, and non-opioid substance use or disorder) and demonstrated good calibration (p = 0.90) and discrimination (bootstrap-corrected C-statistic = 0.76: 95 % CI = 0.70, 0.82). Sensitivity and specificity were 57 % and 84 % respectively with a positive predictive value (PPV) of 0.49 %. The validation cohort included 45,790 youth of whom, 74 developed an OUD diagnoses. The model demonstrated poorer calibration (p < 0.001) but good discrimination (C-statistic = 0.89; 95 % CI = 0.84, 0.95), sensitivity of 87.8 % specificity of 68.6 %, and PPV of 0.45 %., Conclusions: In two Colorado healthcare systems, the prediction model identified 57-88 % of subsequent OUD diagnoses in youth. However, PPV < 1% suggests universal prevention strategies for opioid use in youth may be the best health system approach., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Veterans involved in the legal system have a high risk of overdose mortality but limited utilization of medications for opioid use disorder (MOUD). To increase the use of MOUD in Veterans Health Administration (VHA) facilities and reduce overdose mortality, the VHA should incorporate strategies identified by legal-involved veterans to improve quality of care and ensure that their patients' experiences are integrated into care delivery. This study aims to determine strategies to increase use of MOUD from the perspective of legal-involved veterans with a history of opioid use or opioid use disorder (OUD)., Methods: Between February 2018 and March 2019, we conducted semistructured interviews with 18 veterans with a history of opioid use or OUD and legal involvement (15 men and 3 women; mean age 41, standard deviation 13, range 28-61). Veterans were from 9 geographically dispersed United States VHA facilities. The study analyzed verbatim transcripts using the framework method. The primary focus was themes that represented legal-involved veteran-identified strategies to improve the use of MOUD., Results: The 18 veterans interviewed had legal involvement directly related to their opioid use and most (n = 15; 83%) had previously used MOUD. Veteran-identified strategies to improve access to and use of MOUD included: (1) VHA should provide transportation or telehealth services; (2) legal agencies should increase access to MOUD during incarceration; (3) the VHA should reduce physician turnover; (4) the VHA should improve physician education to deliver compassionate, patient-centered treatment; (5) the VHA should improve veteran education about MOUD; and (6) the VHA should provide social support opportunities to veterans., Conclusions: Legal-involved veterans provided strategies that can inform and expand MOUD to better meet their needs and the treatment needs of all patients with OUD. The VHA should consider incorporating these strategies into care, and should evaluate their impact on patients' experience, initiation of and retention on medications, and overdose rates., (Published by Elsevier Inc.)

Purpose: Little is known about prevalence and treatment of OUD among youth engaged in primary care (PC). Medications are the recommended treatment of opioid use disorder (OUD) for adolescents and young adults (youth). This study describes the prevalence of OUD, the prevalence of medication treatment for OUD, and patient characteristics associated with OUD treatment among youth engaged in PC., Methods: This cross-sectional study includes youth aged 16-25 years engaged in PC. Eligible patients had ≥ 1 PC visit during fiscal years (FY) 2014-2016 in one of 6 health systems across 6 states. Data from electronic health records and insurance claims were used to identify OUD diagnoses, office-based OUD medication treatment, and patient demographic and clinical characteristics in the FY of the first PC visit during the study period. Descriptive analyses were conducted in all youth, and stratified by age (16-17, 18-21, 22-25 years)., Results: Among 303,262 eligible youth, 2131 (0.7%) had a documented OUD diagnosis. The prevalence of OUD increased by ascending age groups. About half of youth with OUD had documented depression or anxiety and one third had co-occurring substance use disorders. Receipt of medication for OUD was lowest among youth 16-17 years old (14%) and highest among those aged 22-25 (39%)., Conclusions: In this study of youth engaged in 6 health systems across 6 states, there was low receipt of medication treatment, and high prevalence of other substance use disorders and mental health disorders. These findings indicate an urgent need to increase medication treatment for OUD and to integrate treatment for other substance use and mental health disorders.

Background: Despite policy efforts to prevent overdose, accidental overdoses among individuals prescribed opioids continue to occur. Guided by Rhodes' Risk Environment Framework, we examined the unintended consequences of restrictive policies by identifying macro policy and micro-level contextual factors that patients prescribed opioids for pain identified as contributing to overdose events., Methods: Semi-structured interviews were conducted with 31 patients prescribed opioids who experienced an accidental opioid overdose between April 2017 and June 2019 in two health systems., Results: We identified three interrelated factors that emerged within an evolving risk environment and may have increased patients' vulnerability for an accidental opioid overdose: desperation from persistent pain and comorbidities; limited knowledge about opioid medication safety and effectiveness; and restrictive opioid prescribing policies that exacerbated stigma, fear and mistrust and prevented open patient-clinician communication. When experiencing persistent pain, patients took matters into their own hands by taking more medications or in different intervals than prescribed, mixing them with other substances, or using illicitly obtained opioids., Conclusion: For some patients, macro-level policies and guidelines designed to reduce opioid overdoses by restricting opioid supply may have paradoxically created a micro-level risk environment that contributed to overdose events in a subset of patients., Competing Interests: Declarations of Interest Dr. Ingrid Binswanger receives royalties from UpToDate but does not have any additional conflict of interest. All remaining authors declare that they do not have a conflict of interest., (Copyright © 2020. Published by Elsevier B.V.)

Importance: Many people use cannabis for medical reasons despite limited evidence of therapeutic benefit and potential risks. Little is known about medical practitioners' documentation of medical cannabis use or clinical characteristics of patients with documented medical cannabis use., Objectives: To estimate the prevalence of past-year medical cannabis use documented in electronic health records (EHRs) and to describe patients with EHR-documented medical cannabis use, EHR-documented cannabis use without evidence of medical use (other cannabis use), and no EHR-documented cannabis use., Design, Setting, and Participants: This cross-sectional study assessed adult primary care patients who completed a cannabis screen during a visit between November 1, 2017, and October 31, 2018, at a large health system that conducts routine cannabis screening in a US state with legal medical and recreational cannabis use., Exposures: Three mutually exclusive categories of EHR-documented cannabis use (medical, other, and no use) based on practitioner documentation of medical cannabis use in the EHR and patient report of past-year cannabis use at screening., Main Outcomes and Measures: Health conditions for which cannabis use has potential benefits or risks were defined based on National Academies of Sciences, Engineering, and Medicine's review. The adjusted prevalence of conditions diagnosed in the prior year were estimated across 3 categories of EHR-documented cannabis use with logistic regression., Results: A total of 185 565 patients (mean [SD] age, 52.0 [18.1] years; 59% female, 73% White, 94% non-Hispanic, and 61% commercially insured) were screened for cannabis use in a primary care visit during the study period. Among these patients, 3551 (2%) had EHR-documented medical cannabis use, 36 599 (20%) had EHR-documented other cannabis use, and 145 415 (78%) had no documented cannabis use. Patients with medical cannabis use had a higher prevalence of health conditions for which cannabis has potential benefits (49.8%; 95% CI, 48.3%-51.3%) compared with patients with other cannabis use (39.9%; 95% CI, 39.4%-40.3%) or no cannabis use (40.0%; 95% CI, 39.8%-40.2%). In addition, patients with medical cannabis use had a higher prevalence of health conditions for which cannabis has potential risks (60.7%; 95% CI, 59.0%-62.3%) compared with patients with other cannabis use (50.5%; 95% CI, 50.0%-51.0%) or no cannabis use (42.7%; 95% CI, 42.4%-42.9%)., Conclusions and Relevance: In this cross-sectional study, primary care patients with documented medical cannabis use had a high prevalence of health conditions for which cannabis use has potential benefits, yet a higher prevalence of conditions with potential risks from cannabis use. These findings suggest that practitioners should be prepared to discuss potential risks and benefits of cannabis use with patients.

Objectives: A variety of patients - including women, older, racial/ethnic minority, rural, homeless, and justice-involved patients - are vulnerable to experiencing poor healthcare access and quality, such as lower quality substance use disorder treatment, than other populations. The current study examined receipt of medications for opioid use disorder by vulnerable populations within Veterans Health Administration (VHA) facilities to determine whether there are patient and facility factors that are associated with disparities in care., Methods: Using national VHA clinical/administrative data from Fiscal Year 2017, we calculated receipt of medications for opioid use disorder using the American Society for Addiction Medicine quality measure specifications. A mixed-effects logistic regression model tested whether patient vulnerability (ie, women, older age, racial/ethnic minority, rural residence, homeless, and justice-involved) and facility (eg, regional location, availability of a methadone clinic) characteristics were associated with medication receipt., Results: Among the 53,568 veterans at VHA facilities diagnosed with opioid use disorder in Fiscal Year 2017, vulnerable populations - including women, older, Black, rural, homeless, and justice-involved veterans - had lower odds of receiving medications for opioid use disorder than their nonvulnerable counterparts. Veterans had higher odds of receiving medications at facilities with a higher proportion of patients with opioid use disorder, but lower odds of receiving medications at facilities in the Southern region compared to the Northeast region of the United States., Conclusions: Quality improvement efforts targeted at vulnerable populations are needed at the VHA to ensure these groups receive the same quality of substance use disorder treatment as other veterans., Competing Interests: The authors have no conflicts of interests to disclose.

Background: Hepatitis C and HIV are associated with opioid use disorders (OUD) and injection drug use. Medications for OUD can prevent the spread of HCV and HIV., Objective: To describe the prevalence of documented OUD, as well as receipt of office-based medication treatment, among primary care patients with HCV or HIV., Design: Retrospective observational cohort study using electronic health record and insurance data., Participants: Adults ≥ 18 years with ≥ 2 visits to primary care during the study (2014-2016) at 6 healthcare systems across five states (CO, CA, OR, WA, and MN)., Main Measures: The primary outcome was the diagnosis of OUD; the secondary outcome was OUD treatment with buprenorphine or oral/injectable naltrexone. Prevalence of OUD and OUD treatment was calculated across four groups: HCV only; HIV only; HCV and HIV; and neither HCV nor HIV. In addition, adjusted odds ratios (AOR) of OUD treatment associated with HCV and HIV (separately) were estimated, adjusting for age, gender, race/ethnicity, and site., Key Results: The sample included 1,368,604 persons, of whom 10,042 had HCV, 5821 HIV, and 422 both. The prevalence of diagnosed OUD varied across groups: 11.9% (95% CI: 11.3%, 12.5%) for those with HCV; 1.6% (1.3%, 2.0%) for those with HIV; 8.8% (6.2%, 11.9%) for those with both; and 0.92% (0.91%, 0.94%) among those with neither. Among those with diagnosed OUD, the prevalence of OUD medication treatment was 20.9%, 16.0%, 10.8%, and 22.3%, for those with HCV, HIV, both, and neither, respectively. HCV was not associated with OUD treatment (AOR = 1.03; 0.88, 1.21), whereas patients with HIV had a lower probability of OUD treatment (AOR = 0.43; 0.26, 0.72)., Conclusions: Among patients receiving primary care, those diagnosed with HCV and HIV were more likely to have documented OUD than those without. Patients with HIV were less likely to have documented medication treatment for OUD.

Background: Effective and efficient methods are needed to identify naloxone administrations within electronic health record (EHR) data to conduct overdose surveillance and research. The objective of this study was to develop and validate a text-mining tool to identify naloxone administrations in EHR data. Methods: Clinical notes stored in databases between January 2017 and March 2018 were used to iteratively develop a text-mining tool to identify naloxone administrations. The first iteration of the tool used broad search terms. Then, after reviewing clinical notes of overdose encounters, we developed a list of phrases that described naloxone administrations to inform iteration two. While validating iteration two, additional phrases were found, which were then added to inform the final iteration. The comparator was an administrative code query extracted from the EHR. Medical record review was used to identify true positives. The primary outcome was the positive predictive values (PPV) of the second iteration, final iteration, and administrative code query. Results: Iteration two, the final iteration, and the administrative code had PPVs of 84.3% (95% confidence interval [CI] 78.6-89.0%), 83.8% (95% CI 78.6-88.2%), and 57.1% (95% CI 47.1-66.8%), respectively. Both iterations of the tool had a significantly higher PPV than the administrative code ( p  < 0.001). Conclusions: A text-mining tool improved the identification of naloxone administrations in EHR data from less than 60% with the administrative code to greater than 80% with both versions of the tool. Text-mining tools can inform the use of more sophisticated informatics methods, which often require significant time, resource, and expertise investment.

Background and Aims: Despite the high prevalence of substance use among people in the US criminal justice system, little is known about the incidence of overdose mortality by use patterns, drug convictions and supervision setting. We examined the associations between these characteristics and overdose mortality., Design: Retrospective cohort study., Setting and Participants: Individuals sentenced to prison, jail, probation or jail plus probation for a felony conviction in Michigan, USA from 2003 to 2006., Measurements: Using the National Death Index, we assessed overdose mortality to December 2012. We calculated overdose mortality rates by pre-sentence opioid use, drug convictions and supervision setting. Multivariable analyses were conducted using competing risks regression with time-varying covariates., Findings: Among 140 266 individuals followed over a mean of 7.84 years [standard deviation (SD) = 1.52], 14.9% of the 1131 deaths were due to overdose (102.8 per 100 000 person-years). Over the follow-up, more than half of overdose deaths occurred in the community (57.7%), nearly a third (28.8%) on probation and 12.8% on parole. The adjusted risk of overdose death was lower on probation [hazard ratio (HR) = 0.71, 95% confidence interval (CI) = 0.60, 0.85] than in the community without probation or parole (HR = 1.00) but not significantly different on parole (HR = 1.13, 95% CI = 0.87, 1.47). Pre-sentence daily opioid use (HR = 3.54, 95% CI = 3.24, 3.87) was associated with an increased risk. Drug possession (HR = 1.11, 95% CI = 0.93, 1.31) and delivery convictions (HR = 0.92, 95% CI = 0.77, 1.09) were not significantly associated with overdose mortality., Conclusions: Based on the absolute or relative risk, parole, probation and community settings are appropriate settings for enhanced overdose prevention interventions. Ensuring that individuals with pre-sentence opioid use have access to harm reduction and drug treatment services may help to prevent overdose among people involved with the criminal justice system., (© 2020 Society for the Study of Addiction.)

Background: Opioid prescribing guidelines recommend reducing or discontinuing opioids for chronic pain if harms of opioid treatment outweigh benefits. As opioid discontinuation becomes more prevalent, it is important to understand whether opioid discontinuation is associated with heroin use. In this study, we sought to assess the association between opioid discontinuation and heroin use documented in the medical record., Methods: A matched nested case-control study was conducted in an integrated health plan and delivery system in Colorado. Patients receiving opioid therapy in the study period (January 2006-June 2018) were included. Opioid discontinuation was defined as ≥45 days with no opioids dispensed after initiating opioid therapy. The heroin use onset date represented the index date. Case patients were matched to up to 20 randomly selected patients without heroin use (control patients) by age, sex, calendar time, and time between initiating opioid therapy and the index date. Conditional logistic regression models estimated matched odds ratios (mOR) for the association between an opioid discontinuation prior to the index date and heroin use., Results: Among 22,962 patients prescribed opioid therapy, 125 patients (0.54%) used heroin after initiating opioid therapy, of which 74 met criteria for inclusion in the analysis. The odds of opioid discontinuation were approximately two times higher in case patients (n = 74) than control patients (n = 1045; mOR = 2.19; 95% CI 1.27-3.78)., Conclusions: Among patients prescribed chronic opioid therapy, the observed increased risk for heroin use associated with opioid discontinuation should be balanced with potential benefits., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Objective: To develop a validated instrument that measures knowledge about prescription opioid overdose., Methods: Within an integrated health care system, we adapted, piloted, and tested the reliability and predictive validity of a modified Opioid Overdose Knowledge Scale (OOKS) instrument specific to prescription opioids (Rx-OOKS) with a patient population prescribed long-term opioid therapy and potentially at risk of opioid overdose. We used an interdisciplinary team approach and patient interviews to adapt the instrument. We then piloted the survey on a patient sample and assessed it using Cronbach's alpha and logistic regression., Results: Rx-OOKS (N = 56) resulted in a three-construct, 25-item instrument. Internal consistency was acceptable for the following constructs: "signs of an overdose" (10 items) at α = 0.851, "action to take with opioid overdose" (seven items) at α = 0.692, and "naloxone use knowledge" (eight items) at α = 0.729. One construct, "risks of an overdose" (three items), had an α of 0.365 and was subsequently eliminated from analysis due to poor performance. We conducted logistic regression to determine if any of the constructs was strongly associated with future naloxone receipt. Higher scores on "actions to take in an overdose" had nine times the odds of receiving naloxone (odds ratio [OR] = 9.00, 95% confidence interval [CI] = 1.42-57.12); higher "naloxone use knowledge" scores were 15.8 times more likely to receive naloxone than those with lower scores (OR = 15.83, 95% CI = 1.68-149.17)., Conclusions: The Rx-OOKS survey instrument can reliably measure knowledge about prescription opioid overdose recognition and naloxone use. Further, knowledge about actions to take during an opioid overdose and naloxone use were associated with future receipt of naloxone., (© The Author(s) 2020. Published by Oxford University Press on behalf of the American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

In the United States, we are experiencing linked epidemics (a syndemic) of substance use disorders (SUDs) and infections associated with drug use, including unsafe injecting and unsafe sex in exchange for drugs or money. Current drug laws, together with risk-taking behavior among persons with SUDs, contribute to disproportionately high prevalences of these conditions in correctional settings. Detection and treatment of diseases with a high impact on public health are best addressed in the settings where such conditions are most prevalent (ie, jails and prisons for SUDs and chronic infections). The effectiveness, safety, cost of care. and public health impact of these conditions can be improved by means of broader screening and expanded access to specialty consultations through telemedicine/telehealth, along with broader use of long-acting medications for the treatment of human immunodeficiency virus and SUDs. Expanding telemedicine/telehealth, first for specialties which do not require advanced technology (eg, infectious diseases, addictions), can eventually lead to further advancements in correctional healthcare., (© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Background: Veterans involved in the legal system are at high risk for overdose but have lower receipt of medications for opioid use disorder than other veterans., Objective: The study aimed to understand barriers to medication access from the perspective of legally involved veterans with opioid use disorder and people who work with these veterans in the Veterans Health Administration (VHA) and the legal system., Design: This national qualitative study interviewed veterans and stakeholders from 14 geographically diverse VHA facilities to explore perceptions of barriers to medications for opioid use disorder., Participants: Participants included veterans with a history of opioid use disorder and legal involvement (n = 18), VHA Veterans Justice Programs Specialists (n = 15), VHA and community substance use disorder treatment providers (n = 5), and criminal justice staff (n = 12)., Approach: We conducted interviews based on the Consolidated Framework for Implementation Research. Interview transcripts were analyzed using a team-based approach., Key Results: Four key barriers, noted by group, were identified: (1) a preference for counseling along with or instead of medications (veterans, Specialists, treatment providers, criminal justice staff); (2) concerns about veterans using medications without a prescription, selling them, or providing them to others (veterans, Specialists, treatment providers, criminal justice staff); (3) concerns about perceived stigma towards medication use (veterans, Specialists, treatment providers, criminal justice staff); and (4) concerns about medication discontinuation after recurrent opioid use (veterans, criminal justice staff). A fifth theme, education, was noted by all stakeholders except providers as important to facilitating use of medications for opioid use disorder. All five themes mapped to the framework construct of knowledge and beliefs about the intervention., Conclusions: Based on identified barriers, interventions focused on enhancing medication knowledge, reducing stigma towards use of medications, and increasing knowledge that opioid use may recur during treatment may help increase access to medication for veterans with legal involvement.

Importance: Family members are cited as a common source of prescription opioids used for nonmedical reasons. However, the overdose risk associated with exposure to opioids prescribed to family members among adolescents and young adults is not well established., Objective: To assess the association of opioids prescribed to family members with pharmaceutical opioid overdose among youth., Design, Setting, and Participants: This cohort study included 45 145 family units with a total of 72 040 adolescents and young adults aged 11 to 26 years enrolled in a Kaiser Permanente Colorado health plan in 2006 and observed through June 2018., Exposures: Opioid prescriptions and dosage dispensed to family members and youth in the past month., Main Outcomes and Measures: Fatal pharmaceutical opioid overdoses identified in vital records and nonfatal pharmaceutical opioid overdoses identified in emergency department and inpatient settings. Time to first overdose was modeled using Cox regression., Results: The study population consisted of 72 040 adolescents and young adults (mean [SD] age across follow-up, 19.3 [3.7] years; 36 646 [50.9%] girls and women) nested in 45 145 family units. Youth were more commonly exposed to prescription opioids dispensed to a family member than through their own prescriptions. During follow-up, 26 284 youth (36.5%) filled at least 1 opioid prescription, and 47 461 youth (65.9%) had at least 1 family member with a prescription. Exposure to family members with opioid prescriptions in the past month was associated with increased risk of pharmaceutical opioid overdose (adjusted hazard ratio [aHR], 2.17; 95% CI, 1.24-3.79) independent of opioids prescribed to youth (aHR, 6.62; 95% CI, 3.39-12.91). Concurrent exposure to opioid prescriptions from youth and family members was associated with substantially increased overdose risk (aHR, 12.99; 95% CI, 5.08-33.25). High dosage of total morphine milligram equivalents (MME) prescribed to family members in the past month was associated with youth overdose (0 MME vs >0 to <200 MME: aHR, 1.39; 95% CI, 0.51-3.81; 0 MME vs 200 to <600 MME: aHR, 1.49; 95% CI, 0.59-3.77; 0 MME vs ≥600 MME: aHR, 2.93; 95% CI, 1.55-5.56)., Conclusions and Relevance: In this study of youth linked to family members, exposure to family members' prescribed opioids was associated with increased risk of pharmaceutical opioid overdose, independent of opioids prescribed to youth. Further interventions targeting youth and families are needed, including counseling patients about the risks of opioids to youth in their families.

Background: The United States is in the middle of an opioid overdose epidemic, and experts are calling for improved detection of opioid use disorders (OUDs) and treatment with buprenorphine or extended release (XR) injectable naltrexone, which can be prescribed in general medical settings. To better understand the magnitude of opportunities for treatment among primary care (PC) patients, we estimated the prevalence of documented OUD and medication treatment of OUD among PC patients., Methods: This cross-sectional study included patients with ≥2 visits to PC clinics across 6 healthcare delivery systems who were ≥16 years of age during the study period (fiscal years 2014-2016). Diagnoses, prescriptions, and healthcare utilization were ascertained from electronic health records and insurance claims (5 systems that also offer health insurance). Documented OUDs were defined as ≥1 International Classification of Diseases code for OUDs (active or remission), and OUD treatment was defined as ≥1 prescription(s) for buprenorphine formulations indicated for OUD or naltrexone XR, during the 3-year study period. The prevalence of documented OUD and treatment (95% confidence intervals) across health systems were estimated, and characteristics of patients by treatment status were compared. Prevalence of OUD and OUD treatment were adjusted for age, gender, and race/ethnicity. Combined results were also adjusted for site., Result: Among 1,403,327 eligible PC patients, 54-62% were female and mean age ranged from 46 to 51 years across health systems. The 3-year prevalence of documented OUD ranged from 0.7-1.4% across the health systems. Among patients with documented OUD, the prevalence of medication treatment (primarily buprenorphine) varied across health systems: 3%, 12%, 16%, 20%, 22%, and 36%., Conclusion: The prevalence of documented OUD and OUD treatment among PC patients varied widely across health systems. The majority of PC patients with OUD did not have evidence of treatment with buprenorphine or naltrexone XR, highlighting opportunities for improved identification and treatment in medical settings. These results can inform initiatives aimed at improving treatment of OUD in PC. Future research should focus on why there is such variation and how much of the variation can be addressed by improving access to medication treatment., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: The U.S. experienced nearly 48,000 opioid overdose deaths in 2017. Treatment of opioid use disorder (OUD) with buprenorphine is a recommended part of primary care, yet little is known about current U.S. practices in this setting. This observational study reports the prevalence of documented OUD and OUD treatment with buprenorphine among primary care patients in six large health systems., Methods: Adults with ≥2 primary care visits during a three-year period (10/1/2013-9/30/2016) in six health systems were included. Data were obtained from electronic health record and claims data, with measures, assessed over the three-year period, including indicators for documented OUD from ICD 9 and 10 codes and OUD treatment with buprenorphine. The prevalence of OUD treatment was adjusted for age, gender, race/ethnicity, and health system., Results: Among 1,368,604 primary care patients, 13,942 (1.0 %) had documented OUD, and among these, 21.0 % had OUD treatment with buprenorphine. For those with documented OUD, the adjusted prevalence of OUD treatment with buprenorphine varied across demographic and clinical subgroups. OUD treatment was lower among patients who were older, women, Black/African American and Hispanic (compared to white), non-commercially insured, and those with non-cancer pain, mental health disorders, greater comorbidity, and more opioid prescriptions, emergency department visits or hospitalizations., Conclusions: Among primary care patients in six health systems, one in five with an OUD were treated with buprenorphine, with disparities across demographic and clinical characteristics. Less buprenorphine treatment among those with greater acute care utilization highlights an opportunity for systems-level changes to increase OUD treatment., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: Patients with mental illness are frequently treated in primary care, where Primary Care Providers (PCPs) report feeling ill-equipped to manage their care. Team-based models of care improve outcomes for patients with mental illness, but multiple barriers limit adoption. Barriers include practical issues and psychosocial factors associated with the reorganization of care. Practice facilitation can improve implementation, but does not directly address the psychosocial factors or gaps in PCP skills in managing mental illness. To address these gaps, we developed Relational Team Development (RELATED)., Methods: RELATED is an implementation strategy combining practice facilitation and psychology clinical supervision methodologies to improve implementation of team-based care. It includes PCP-level clinical coaching and a team-level practice change activity. We performed a preliminary assessment of RELATED with a convergent parallel mixed method study in 2 primary care clinics in an urban Federally Qualified Health Center in Southwest, USA, 2017-2018. Study participants included PCPs, clinic staff, and patient representatives. Clinic staff and patients were recruited for the practice change activity only. Primary outcomes were feasibility and acceptability. Feasibility was assessed as ease of recruitment and implementation. Acceptability was measured in surveys of PCPs and staff and focus groups. We conducted semi-structured focus groups with 3 participant groups in each clinic: PCPs; staff and patients; and leadership. Secondary outcomes were change in pre- post- intervention PCP self-efficacy in mental illness management and team-based care. We conducted qualitative observations to better understand clinic climate., Results: We recruited 18 PCPs, 17 staff members, and 3 patient representatives. We ended recruitment early due to over recruitment. Both clinics developed and implemented practice change activities. The mean acceptability score was 3.7 (SD=0.3) on a 4-point Likert scale. PCPs had a statistically significant increase in their mental illness management self-efficacy [change = 0.9, p-value= <.01]. Focus group comments were largely positive, with PCPs requesting additional coaching., Conclusions: RELATED was feasible and highly acceptable. It led to positive changes in PCP self-efficacy in Mental Illness Management. If confirmed as an effective implementation strategy, RELATED has the potential to significantly impact implementation of evidence-based interventions for patients with mental illness in primary care.

People leaving incarceration are at high risk of opioid-related overdose. Overdose fatalities are preventable with administration of naloxone. In response to this risk, overdose education and naloxone distribution (OEND) programs have been implemented in a handful of jails and prisons in the United States. We document the history, structure, and data from the San Francisco County Jail OEND program. During 4 years of operation, 637 people participated; 67% received naloxone upon release, of whom only 3.5% had been previously trained in community-based OEND programs. Of those who received naloxone, 32% reported reversing an overdose and 44% received refills from community-based programs after reentry. This confirms that implementation of OEND in criminal justice settings is feasible and reaches people who have not previously been trained as well as those willing to act as overdose responders.