Baseline Factors Associated with Mortality in Patients Who Engaged in Buprenorphine Treatment for Opioid Use Disorder: a Cohort Study

Considerations and limitations of buprenorphine prescribing for opioid use disorder in the intensive care unit setting: A narrative review

PURPOSE

The purpose of this review is to discuss important considerations when prescribing buprenorphine for opioid use disorder (OUD) in the intensive care unit (ICU) setting, recognizing the challenges of providing detailed recommendations in the setting of limited available evidence.

SUMMARY

Buprenorphine is a partial mu-opioid receptor agonist that is likely to be increasingly prescribed for OUD in the ICU setting due to the relaxation of prescribing regulations. The pharmacology and pharmacokinetics of buprenorphine are complicated by the availability of several formulations that can be given by different administration routes. There is no single optimal dosing strategy for buprenorphine induction, with regimens ranging from very low-dose to high dose regimens. Faster induction with higher doses of buprenorphine has been studied and is frequently utilized in the emergency department. In patients admitted to the ICU who were receiving opioids either medically or illicitly, analgesia will not occur until their baseline opioid requirements are covered when their preadmission opioid is either reversed or interrupted. For patients in the ICU who are not on buprenorphine at the time of admission but have possible OUD, there are no validated tools to diagnose OUD or the severity of opioid withdrawal in critically ill patients unable to provide the subjective components of instruments validated in outpatient settings. When prescribing buprenorphine in the ICU, important issues to consider include dosing, monitoring, pain management, use of adjunctive medications, and considerations to transition to outpatient therapy. Ideally, addiction and pain management specialists would be available when buprenorphine is prescribed for critically ill patients.

CONCLUSION

There are unique challenges when prescribing buprenorphine for OUD in critically ill patients, regardless of whether they were receiving buprenorphine when admitted to the ICU setting for OUD or are under consideration for buprenorphine initiation. There is a critical need for more research in this area.

Evaluation of opioid use disorder treatment outcomes in patients receiving split daily versus once daily dosing of buprenorphine-naloxone

INTRODUCTION

In clinical practice, sublingual (SL) buprenorphine-naloxone is prescribed as once daily or split daily dosing for the management of opioid use disorder (OUD). Evidence is lacking that assesses how split daily buprenorphine-naloxone affects OUD outcomes. This study aims to evaluate how the dosing frequency of SL buprenorphine-naloxone impacts therapy effectiveness when treating patients with OUD.

METHODS

This retrospective analysis included adult outpatients prescribed treatment with SL buprenorphine-naloxone for OUD between July 1, 2016, and March 1, 2020. The study excluded patients with sickle cell disease, recent methadone treatment, or pregnancy. We characterized study groups by dosing frequency, either once daily or split dosing. The study compared retention in treatment, medication adherence, adherence to treatment program, and hospital encounters between groups.

RESULTS

The study screened eight-hundred and seven patients, and included 250 patients newly prescribed SL buprenorphine-naloxone. Fifty-seven patients (22.8 %) were prescribed once daily dosing and 193 patients (77.2 %) were prescribed split daily dosing. The study found no significant differences noted in 12-month rates of treatment retention (52.6 % vs. 45.6 %, p = .35). These outcomes remained similar when assessed at three and six months. Within a year of buprenorphine-naloxone initiation, the study found no differences in the percentage of patients with hospitalizations (26.3 % vs. 38.3 %, p = .10), median number of hospitalizations (2 vs. 2), or proportion of days covered by a prescription ≥80 % (93.3 % vs. 92.0 %, p = .82).

CONCLUSIONS

In this study, patients receiving once daily buprenorphine-naloxone had similar treatment outcomes to patients receiving split dosing. Further controlled studies are necessary to evaluate which patients are more likely to benefit from split dosing.

Mobile service delivery in response to the opioid epidemic in Philadelphia

BACKGROUND

The harms of opioid use disorder (OUD) and HIV infection disproportionately impact marginalized populations, especially people experiencing homelessness and people who inject drugs (PWID). Mobile OUD service delivery models are emerging to increase access and reduce barriers to OUD care. While there is growing interest in these models, there is limited research about the services they provide, how they operate, and what barriers they face. We characterize the capacity, barriers, and sustainment of mobile OUD care services in a large city with a high incidence of OUD and HIV.

METHODS

From May to August 2022, we conducted semi-structured interviews with leadership from all seven mobile OUD care units (MOCU) providing a medication for OUD or other substance use disorder services in Philadelphia. We surveyed leaders about their unit's services, staffing, operating location, funding sources, and linkages to care. Leaders were asked to describe their clinical approach, treatment process, and the barriers and facilitators to their operations. Interview recordings were coded using rapid qualitative analysis.

RESULTS

MOCUs are run by small, multidisciplinary teams, typically composed of a clinician, one or two case managers, and a peer recovery specialist or outreach worker. MOCUs provide a range of services, including medications for OUD, wound care, medical services, case management, and screening for infectious diseases. No units provide methadone, but all units provide naloxone, six write prescriptions for buprenorphine, and one unit dispenses buprenorphine. The most frequently reported barriers include practical challenges of working on a MOCU (e.g. lack of space, safety), lack of community support, and patients with substantial medical and psychosocial needs. Interviewees reported concerns about funding and specifically as it relates to providing their staff with adequate pay. The most frequently reported facilitators include positive relationships with the community, collaboration with other entities (e.g. local nonprofits, the police department, universities), and having non-clinical staff (e.g. outreach workers, peer recovery specialists) on the unit.

CONCLUSIONS

MOCUs provide life-saving services and engage marginalized individuals with OUD. These findings highlight the challenges and complexities of caring for PWID and demonstrate a need to strengthen collaborations between MOCU providers and the treatment system. Policymakers should consider programmatic funding for permanent mobile OUD care services.

Comparing the diagnostic performance of ordinary, mixed, and lasso logistic regression models at identifying opioid and cannabinoid poisoning in U.S. dogs using pet demographic and clinical data reported to an animal poison control center (2005-2014)

Researchers have begun studying the impact of human opioid and cannabinoid use on dog populations. These studies have used data from an animal poison control center (APCC) and there are concerns that due to the illicit nature and social stigma concerning the use of these drugs, owners may not always be forthcoming with veterinarians or APCC staff regarding pet exposures to these toxicants. As a result, models derived from APCC data that examine the predictability of opioid and cannabinoid dog poisonings using pet demographic and health disorder information may help veterinarians or APCC staff more reliably identify these toxicants when examining or responding to a call concerning a dog poisoned by an unknown toxicant. The fitting of epidemiologically informed statistical models has been useful for identifying factors associated with various health conditions and as predictive tools. However, machine learning, including lasso regression, has many useful features as predictive tools, including the ability to incorporate large numbers of independent variables. Consequently, the objectives of our study were: 1) identify pet demographic and health disorders associated with opioid and cannabinoid dog poisonings using ordinary and mixed logistic regression models; and 2) compare the predictive performance of these models to analogous lasso logistic regression models. Data were obtained from reports of dog poisoning events collected by the American Society for the Prevention of Cruelty to Animals' (ASPCA) Animal Poisoning Control Center, from 2005-2014. We used ordinary and mixed logistic regression models as well as lasso logistic regression models with and without controlling for autocorrelation at the state level to train our models on half the dataset and test their predictive performance on the remainder. Although epidemiologically informed logistic regression models may require substantial knowledge of the disease systems being investigated, they had the same predictive abilities as lasso logistic regression models. All models had relatively high predictive parameters except for positive predictive values, due to the rare nature of calls concerning opioid and cannabinoid poisonings. Ordinary and mixed logistic regression models were also substantially more parsimonious than their lasso equivalents while still allowing for the epidemiological interpretation of model coefficients. Controlling for autocorrelation had little effect on the predictive performance of all models, but it did reduce the number of variables included in lasso models. Several disorder variables were associated with opioid and cannabinoid calls that were consistent with the acute effects of these toxicants. These models may help build diagnostic evidence concerning dog exposure to opioids and cannabinoids, saving time and resources when investigating these cases.

Predictors of Death From Physical Illness or Accidental/Intentional Causes Among Patients With Substance-Related Disorders

OBJECTIVE

This study identified patient clinical and sociodemographic characteristics, and, more originally, service use patterns as predictors of death from physical illness or accidental/intentional causes.

METHODS

A cohort of 19,015 patients with substance-related disorders (SRD) from 14 addiction treatment centers was investigated using Quebec (Canada) health administrative databases. Death was studied over a 3-year period (April 1, 2013, to March 31, 2016), and most predictors from 4 years to 12 months prior to the time of death, using multinomial logistic regression.

RESULTS

Frequent emergency department (ED) use strongly predicted both causes of death, suggesting that outpatient care responded inadequately to patient needs. Only receipt of specialized SRD and psychiatric care significantly decreased the risk of death from physical illness, with trends toward significance for accidental/intentional death. Hospitalization, greater material deprivation and having SRD-chronic physical illnesses or alcohol-related disorders most strongly predicted risk of death from physical illness. Sociodemographic characteristics, mainly social deprivation, were more likely to predict accidental/intentional death.

CONCLUSIONS

Outpatient services could be improved by increasing outreach and motivational interventions and, for ED and hospital units, better screening, brief intervention, and referral to treatment, particularly for men and socially deprived patients at high risk of accidental/intentional death. Patients with more severe health conditions, notably older or materially deprived men at higher risk of death from physical illness, could benefit from programs like assertive community treatment or intensive case management that respond well to diverse and continuous patient needs. Collaborative care between SRD and health services could also be improved.

Gaps in naloxone ownership among people who inject drugs during the fentanyl wave of the opioid overdose epidemic in New York City, 2018

Background: Community distribution of naloxone, a medication that reverses opioid overdose, is an effective public health strategy to prevent overdose deaths. However, data are limited on who has naloxone during the current fentanyl wave of the opioid overdose epidemic in the United States. We aim to determine correlates of naloxone ownership among a community sample of people who inject drugs (PWID) from New York City (NYC). Methods: Data were drawn from the National HIV Behavioral Surveillance Study among PWID. Participants were recruited via respondent-driven sampling. Eligible participants completed an interviewer-administered survey. Log-linked Poisson regression was used to determine adjusted prevalence ratios (aPR) and 95% confidence intervals (CIs) current naloxone ownership. Results: Of 503 PWID, 60% currently owned naloxone. In the past 12 months, 74% witnessed an opioid overdose and 25% experienced one. Those who experienced current homelessness were less likely to own naloxone (aPR: 0.79; 95% CI: 0.68, 0.91), as were those who had been recently incarcerated (aPR: 0.83; 95% CI: 0.71, 0.97). Respondents who reported recent known or possible fentanyl use were more likely to own naloxone (aPR: 1.23; 95% CI: 1.07, 1.43) as were those who experienced an opioid overdose in the past 12 months (aPR: 1.33; 95% CI: 1.15, 1.53). Conclusions: The prevalence of naloxone ownership among PWID in NYC was high, potentially due to widespread community naloxone distribution programs; however, gaps in naloxone ownership existed. Interventions that further ease access to naloxone, such as reclassifying naloxone as an over-the-counter medication and making it available "off the shelf," should be considered. More research is needed to identify barriers to access, uptake, and sustained possession within this group to maximize the impact of naloxone distribution during the ongoing fentanyl wave of the opioid overdose epidemic.

Associations of housing stress with later substance use outcomes: A systematic review

A synthesis of existing evidence regarding the association of housing stress with later substance use outcomes can help support and inform housing interventions as a potential strategy to address problematic substance use. We conducted a comprehensive search of PubMed, Web of Science, PsycInfo, CINAHL, Social Work Abstracts, and Sociological Abstracts and systematically screened for articles examining housing stress and later substance use outcomes among U.S. adults. Across 38 relevant articles published from 1991 to 2020, results demonstrated an association of homelessness with an increased likelihood of substance use, substance use disorders (SUD), and overdose death. Results regarding the association of homelessness with receipt and completion of SUD treatment were mixed, and one study indicated no association of homelessness with motivation to change substance use behaviors. Several studies did not find an association of unstable housing with substance use or receipt of SUD treatment, while others found an association of unstable housing with intensified SUD symptoms and a decreased likelihood of completing SUD treatment. Overall, while there is evidence of an association of homelessness with later substance use, SUD, and overdose death, results for other forms of housing stress and some substance use outcomes are less consistent. There are several methodological considerations specific to selected measures of housing stress and substance use, study populations, and analytic approaches that have implications for results and directions for future research. Despite these considerations, results collectively suggest that innovative interventions to address housing stress, namely homelessness, may help mitigate some substance use outcomes.

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

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

Opioid use disorder treatment for people experiencing homelessness: A scoping review

BACKGROUND

The opioid-related overdose epidemic remains a persistent public health problem in the United States and has been accelerated by the 2019 coronavirus disease pandemic. Existing, evidence-based treatment options for opioid use disorder (OUD) are broadly underutilized, particularly by people experiencing homelessness (PEH). PEH are also more likely to misuse and overdose on opioids. To better understand current gaps and disparities in OUD treatment experienced by PEH and efforts to address them, we synthesized the literature reporting on the intersection of housing status and OUD treatment.

METHODS

We conducted a scoping review of the literature from the electronic databases MEDLINE, Embase, PsycINFO, and Web of Science Core Collection. We included studies describing treatment-related outcomes specific to PEH and articles assessing OUD treatment interventions tailored to this population. Relevant findings were compiled via thematic analysis and narratively synthesized.

RESULTS

60 articles met our inclusion criteria, including 43 descriptive and 17 intervention-focused studies. These studies demonstrated that PEH experience more barriers to OUD treatment than their housed counterparts and access inpatient and detoxification treatment more commonly than pharmacotherapy. However, the reviewed literature indicated that PEH have similar outcomes once engaged in pharmacotherapy. Efficacious interventions for PEH were low-barrier and targeted, with housing interventions also demonstrating benefit.

CONCLUSIONS

PEH have diminished access to evidence-based OUD treatment, particularly medications, and require targeted approaches to improve engagement and retention. To mitigate the disproportionate opioid-related morbidity and mortality PEH experience, innovative, flexible, and interdisciplinary OUD treatment models are necessary, with housing support playing an important role.

Office-Based Addiction Treatment Retention and Mortality Among People Experiencing Homelessness

Importance

People experiencing homelessness have been disproportionately affected by the opioid overdose crisis. To mitigate morbidity and mortality, several office-based addiction treatment (OBAT) programs designed for this population have been established across the US, but studies have not yet evaluated their outcomes.

Objective

To evaluate treatment retention and mortality in an OBAT program designed specifically for individuals experiencing homelessness with opioid use disorder (OUD).

Design, Setting, and Participants

A retrospective cohort study was conducted in the Boston Health Care for the Homeless Program (BHCHP). Participants included all adult patients (N = 1467) who had 1 or more OBAT program encounter at BHCHP from January 1 through December 31, 2018. Data analysis was conducted from January 13 to December 14, 2020.

Exposures

Sociodemographic, clinical, and addiction treatment-related characteristics were abstracted from the BHCHP electronic health record.

Main Outcomes and Measures

The primary outcome was all-cause mortality, identified by linkage to the Massachusetts Department of Public Health vital records. Multivariable Cox proportional hazards regression analyses were performed to evaluate baseline and time-varying variables associated with all-cause mortality. Secondary addiction treatment-related outcomes were abstracted from the electronic health record and included (1) BHCHP OBAT program retention, (2) buprenorphine continuation and adherence verified by toxicology testing, and (3) opioid abstinence verified by toxicology testing.

Results

Of 1467 patients in the cohort, 1046 were men (71.3%) and 731 (49.8%) were non-Hispanic White; mean (SD) age was 42.2 (10.6) years. Continuous retention in the OBAT program was 45.2% at 1 month, 21.7% at 6 months, and 11.3% at 12 months. Continuous buprenorphine adherence was 41.5% at 1 month, 17.6% at 6 months, and 10.2% at 12 months, and continuous opioid abstinence was 28.3% at 1 month, 6.1% at 6 months, and 2.9% at 12 months. The all-cause mortality rate was 29.0 deaths per 1000 person-years, with 51.8% dying from drug overdose. Past-month OBAT program attendance was associated with lower mortality risk (adjusted hazard ratio, 0.34; 95% CI, 0.21-0.55).

Conclusions and Relevance

Mortality rates were high in this cohort of addiction treatment-seeking homeless and unstably housed individuals with OUD. Although continuous OBAT program retention was low, past-month attendance in care was associated with reduced mortality risk. Future work should examine interventions to promote increased OBAT attendance to mitigate morbidity and mortality in this vulnerable population.