Phillip O. Coffin

Income distribution and risk of fatal drug overdose in New York City neighborhoods

Accidental drug overdose is a substantial cause of mortality for drug users. Neighborhood-level factors, such as income distribution, may be important determinants of overdose death independent of individual-level factors. We used data from the Office of the Chief Medical Examiner to identify all cases of accidental deaths in New York City (NYC) in 1996 and individual-level covariates. We used 1990 US Census data to calculate the neighborhood-level income distribution. This multi-level case-control study included 725 accidental overdose deaths (cases) and 453 accidental deaths due to other causes (controls) in 59 neighborhoods in NYC. Overdose deaths were more likely in neighborhoods with higher levels of drug use and with more unequal income distribution. In multi-level models, income maldistribution was significantly associated with risk of overdose independent of individual-level variables (age, race, and sex) and neighborhood-level variables (income, drug use, and racial composition). The odds of death due to drug overdose were 1.63-1.88 in neighborhoods in the least equitable decile compared with neighborhoods in the most equitable decile. Disinvestment in social and economic resources in unequal neighborhoods may explain this association. Public health interventions related to overdose risk should pay particular attention to highly unequal neighborhoods.

Identifying Injection Drug Users at Risk of Nonfatal Overdose

OBJECTIVES Drug overdose is the second leading cause of accidental deaths among U.S. adults aged 15-64 years. Emergency physicians have a unique opportunity to provide overdose prevention interventions, because habitual drug users are in frequent need of medical care. The authors evaluated associations between individual-level risk factors and experiencing an overdose in the past six months to determine which characteristics and behaviors may be most predictive of overdose. METHODS The authors used data from a sample of street-recruited habitual drug users who participated in face-to-face interviews about overdose from November 2001 to February 2004. This analysis was restricted to 772 respondents who had been injecting for at least one year and who had injected heroin within the past two months. RESULTS A total of 16.6% of participants had overdosed in the past six months. Characteristics and behaviors that were independently associated with an increased risk of a recent overdose were having had a prior overdose (odds ratio [OR], 28.58; 95% confidence interval [CI] = 14.10 to 57.96), using cocaine/crack in the past six months (OR, 2.07; 95% CI = 1.25 to 3.45), using alcohol in the past six months (OR, 1.90; 95% CI = 1.01 to 3.57), experiencing serious withdrawal symptoms in the past two months (OR, 2.70; 95% CI = 1.58 to 4.61), and younger age. CONCLUSIONS Drug users who have previously experienced a nonfatal overdose are at very high risk of experiencing future overdoses. Further longitudinal studies are needed to identify robust predictors of overdose risk over time in habitual drug users, but these data suggest that drug users who have overdosed warrant aggressive prevention efforts such as agonist maintenance treatment or provision of take-home naloxone.

Cost-effectiveness and Population Outcomes of General Population Screening for Hepatitis C

BACKGROUND Current US guidelines recommend limiting hepatitis C virus (HCV) screening to high-risk individuals, and 50%-75% of infected persons remain unaware of their status. METHODS To estimate the cost-effectiveness and population-level impact of adding one-time HCV screening of US population aged 20-69 years to current guidelines, we developed a decision analytic model for the screening intervention and Markov model with annual transitions to estimate natural history. Subanalyses included protease inhibitor therapy and screening those at highest risk of infection (birth year 1945-1965). We relied on published literature and took a lifetime, societal perspective. RESULTS Compared to current guidelines, incremental cost per quality-adjusted life year gained (ICER) was

“Hooked on” Prescription-Type Opiates Prior to Using Heroin: Results from a Survey of Syringe Exchange Clients

7900 for general population screening and

Racial/ethnic disparities in overdose mortality trends in New York City, 1990–1998

4200 for screening by birth year, which dominated general population screening if cost, clinician uptake, and median age of diagnoses were assumed equivalent. General population screening remained cost-effective in all one-way sensitivity analyses, 30 000 Monte Carlo simulations, and scenarios in which background mortality was doubled, all genotype 1 patients were treated with protease inhibitors, and most parameters were set unfavorable to increased screening. ICER was lowest if screening was applied to a population with liver fibrosis similar to 2010 estimates. Approximately 1% of liver-related deaths would be averted per 15% of the general population screened; the impact would be greater with improved referral, treatment uptake, and cure. CONCLUSIONS Broader screening for HCV would likely be cost-effective, but significantly reducing HCV-related morbidity and mortality would also require improved rates of referral, treatment, and cure.

Risk Factors for Nonfatal Overdose at Seattle-Area Syringe Exchanges

Abstract The availability and diversion of prescription-type opioids increased dramatically in the first decade of the twenty-first century. One possible consequence of increased prescription opioid use and accessibility is the associated rise in opioid dependence, potentially resulting in heroin addiction. This study aimed to determine how common initial dependence on prescription-type opioids is among heroin injectors; associations with demographic and drug-using characteristics were also examined. Interview data were collected at syringe exchanges in King County, Washington in 2009. Among the respondents who had used heroin in the prior four months, 39% reported being “hooked on” prescription-type opioids first. Regression analysis indicated that younger age, sedative use and no recent crack use were independently associated with self-report of being hooked on prescription-type opioids prior to using heroin. These data quantify the phenomenon of being hooked on prescription-type opioids prior to initiating heroin use. Further research is needed to characterize the epidemiology, etiology and trajectory of prescription-type opioid and heroin use in the context of continuing widespread availability of prescription-type opioids.

Nonrandomized Intervention Study of Naloxone Coprescription for Primary Care Patients Receiving Long-Term Opioid Therapy for Pain

Racial/ethnic disparities in health and disease have been present in the United States for the past century. Although differences such as individual access to health care and health-related behaviors account for some of these health disparities, it is likely that a combination of individual and contextual-level factors determine the differential rates of disease between racial/ethnic groups. We studied fatal accidental drug overdose in New York City between 1990 and 1998 to describe differences in racial/ethnic patterns over time and to develop hypotheses about factors that might contribute to these differences. During this period, rates of overdose death were consistently higher among blacks and Latinos compared to whites. In addition, cocaine was more common among black decedents, while opiates and alcohol were more common among Latino and white decedents. Differences in situational factors, such as differential likelihood of activating emergency medical response, may in part explain the consistently higher overdose mortality rates observed among minorities. Further study to determine the individual and contextual factors that explain these observed disparities in overdose death may identify effective areas for public health intervention and provide insight into factors underlying racial/ethnic disparities in other health outcomes.

Dose-response associations between number and frequency of substance use and high-risk sexual behaviors among HIV-negative substance-using men who have sex with men (SUMSM) in San Francisco.

Opioid-involved overdose deaths are on the rise, both nationwide and in the state of Washington. In a survey of 443 participants at syringe exchanges in Seattle, Washington, 16% had overdosed in the last year. Several factors were significantly associated in bivariate analysis: lack of permanent housing; incarceration of five or more days in the past year; gender of sex partners; sharing of syringes and other injection paraphernalia; use of speedballs (cocaine and heroin together), goofballs (methamphetamine and heroin together), buprenorphine; injection use of crack cocaine and sedatives; and use of opioids with sedatives. Adjusting for other variables in multivariate logistic regression analyses, only recent incarceration and sharing of injection materials were still significantly associated with overdose. Correctional facilities, syringe exchange programs, and other agencies serving opioid injectors should include overdose prevention components in release planning and services.

Preliminary Evidence of Health Care Provider Support for Naloxone Prescription as Overdose Fatality Prevention Strategy in New York City

In the United States, the opioid analgesic overdose death rate increased from 1.4 to 5.4 per 100000 adults from 1999 to 2011 (1). Efforts to manage this increase in mortality have focused on modifying the prescribing practices of providers (2). Mandated urine testing, pain agreements, and inspections of prescription drug monitoring program data have become standard practice, yet few data support a link between such interventions and reduced opioid-related morbidity or mortality. In fact, whereas opioid analgesic deaths have recently plateaued, heroin use and overdose deaths have skyrocketed, suggesting possible unintended consequences of opioid stewardship initiatives (3, 4). Many communities have used the targeted distribution of naloxone, the short-acting opioid antagonist, to address opioid-related mortality (5). Provision of naloxone to those likely to witness or experience an opioid overdose, principally illicit drug users, has been associated with substantial reductions in community-level opioid overdose mortality relative to communities that did not implement naloxone distribution (6). Other observational and ecologic analyses have demonstrated marked reductions in opioid overdose mortality in communities that distributed naloxone, including Chicago, Illinois (7); New York City (8); and Scotland (9). A meta-analysis demonstrated a higher likelihood of survival in overdose situations when naloxone was administered by laypersons (10). Naloxone distribution to heroin users is remarkably cost-effective (11). In San Francisco, California, implementation and expansion of a targeted naloxone distribution program were temporally associated with a decline in heroin overdose deaths from as high as 180 per year to as few as 10 through 2012. The number of deaths attributed to opioid analgesics, however, exceeded 100 annually from 2010 to 2012 (12). Most of these decedents had received primary care in safety-net clinics, and most had received long-term opioid therapy for pain. However, literature to support naloxone prescribing to this population is limited to early descriptive analyses (13) and anecdotal reports (14). At U.S. Army Fort Bragg, overdoses seen in the emergency department (ED) declined from 8 per month to 0 after naloxone coprescription was started (14, 15); this finding suggests that naloxone prescription may have affected the overdose event rate by influencing patient and/or provider behavior, rather than simply being available as a reversal agent. These results are consistent with some data indicating that heroin users who receive naloxone reduce heroin use (16). In response to these data, we developed and coordinated a standardized naloxone coprescribing program at primary care clinics in a safety-net system in San Francisco. To inform the larger-scale implementation of naloxone prescribing for patients prescribed opioid medications, we assessed the feasibility of introducing and scaling up naloxone coprescribing in these primary care clinics and conducted analyses to assess the association of naloxone coprescribing with ED use and prescribed opioid dose. Methods Naloxone for Opioid Safety Evaluation (NOSE) staff coordinated the clinical program and conducted the evaluation. The study was approved by the Committee on Human Research of the University of California, San Francisco (CHR#13-11168). Clinical Program The clinical program was implemented in a rolling fashion from February 2013 to April 2014 at 6 clinics where patients had died of opioid overdose from 2010 to 2012. All clinics accepted only publicly insured or uninsured patients, and 2 were resident training sites. Onsite leaders were selected, and a consistent protocol was implemented across sites, beginning with training in naloxone prescribing for providers (physicians, nurse practitioners, and physician assistants) and staff (see Appendix and Appendix Table 1, for implementation plan and process outcomes). Training covered rationale and indications for prescribing naloxone (anyone who uses opioids long term or is otherwise at risk for witnessing or experiencing an opioid overdose), language to approach patients (for example, use such phrases as bad reaction instead of overdose), naloxone formulations, and pharmacy/payer coverage. Additionally, providers and staff were trained on how to educate patients on naloxone use, how to assemble the intranasal device (the U.S. Food and Drug Administration has since approved a device requiring no assembly [17]), and ensuring that caretakers know how and when to administer naloxone (Appendix Figure 1). Appendix Figure 1. Checklist for clinic staff to train patients receiving naloxone. CPR = cardiopulmonary resuscitation. Appendix Table 1. Implementation Plan and Process Outcomes for Naloxone Coprescribing at Safety-Net Clinics Initial training was provided to all sites approximately 30 days preceding initiation of naloxone coprescription; after initiation, additional training was provided and at least 1 reminder e-mail was sent to providers (Appendix Figure 2). Because most providers opted to prescribe the intranasal formulation of naloxone and the mucosal atomization device was not readily available from pharmacies, clinics could order the device and patient brochures (Appendix Figure 3) in zipper-seal plastic bags from the clinic systems central pharmacy. NOSE staff assisted with any logistic problems, and a clinical pharmacist educated any pharmacies that encountered problems ordering, dispensing, or billing for naloxone (Appendix Figure 4). Appendix Figure 2. E-mail template to remind providers about naloxone prescribing. ECW = eClinicalWorks; LCR = lifetime clinical record. Appendix Figure 3. Naloxone for opioid safety patient brochure. Appendix Figure 3. Continued. Appendix Figure 4. Informational sheet for pharmacists on ordering, dispensing, counseling, and billing for naloxone. Data Sources and Data Abstraction Feasibility was assessed through chart reviews of all patients receiving long-term opioid therapy by prescription. Patients receiving sufficient opioids to take at least 1 pill daily for more than 3 months were added to a pain management registry (PMR) by staff at each clinic. This list was downloaded every 3 months during the intervention period, and a merged list of 3138 patients with demographic data was generated in March 2015. A manual chart review was conducted to determine whether patients were valid PMR entrantCs during the study period and to collect the following data: 1) opioid type, dose, quantity per 30 days, and date prescribed at 2 clinic visits (the visit closest to the baseline date [start of naloxone coprescribing at the given clinic or the date the patient was added to the PMR, whichever was later] and the last visit at the clinic before chart review [that is, follow-up date]); 2) the date of initial naloxone prescription; and 3) dates of all ED visits at the county hospital and opioid-relatedness. The ED visits were coded as opioid-related in accordance with documentation for establishing drug-relatedness of ED visits from the Drug Abuse Warning Network (18). Visits were opioid-related if the documenting physician considered them to be primarily due to an adverse event from an opioid or to opioid-seeking behavior; a subset of visits was coded as oversedation if the assessment was an opioid poisoning or other complication attributed by the documenting physician to opioid-induced sedation. Staff reviewing charts included a physician who trained other staff and reviewed uncertain cases; 62.5% of charts were independently assessed by at least 2 reviewers (see Appendix for details). Death information was extracted from the California Electronic Death Record System on 14 July 2015. Feasibility Analysis We assessed bivariate relationships between all demographic and clinical characteristics presented in Table 1 and the receipt of naloxone during the study period using chi-square, Fisher exact (for comparisons with cell sizes <5), and Wilcoxon rank-sum tests. Morphine equivalent daily dose in milligrams (MEQ) was calculated for each patient at baseline and subsequent follow-up dates by using standard conversion ratios from the literature (19, 20). Table 1. Demographic and Clinical Characteristics of PMR Patients, by Receipt of Naloxone Prescription We fit a normal-logistic regression model, with random effects for providers, to assess both patient- and provider-level predictors of naloxone prescription. All baseline patient characteristics assessed in bivariate analyses were included in the model, except for opioid type; the latter was excluded because relevant elements of formulations (such as presence of acetaminophen or duration of action) do not necessarily correspond to opioid type. Only baseline history of any opioid-related ED visit was included in the model because this category of visit was hypothesized to be most relevant to naloxone prescribing. The model also included provider type (attending physician or fellow, resident physician, or other provider) and the size of each providers panel of PMR patients, while controlling for time in days from 1 February 2013 (the earliest program initiation date) to patient baseline date, as well as time between the baseline and follow-up visit dates. To characterize residual differences among providers in naloxone prescription rates, we calculated the odds ratio for the difference between the 25th and 75th percentile values of the random provider effect. A descriptive summary of the PMR panel size, number of patients prescribed naloxone, and percentage of patients prescribed naloxone per provider is presented in Appendix Table 2. Appendix Table 2. Provider-Level Data on Total Number of Patients, Number of Patients Prescribed Naloxone, and Percentage of Patients Prescribed Naloxone Analysis of ED Use In our prespecified plan to assess the association of naloxone receipt with opioid-related ED visits, numbers of opioid-rela

Brief overdose education is sufficient for naloxone distribution to opioid users

Abstract: We evaluated the relationship between frequency and number of substances used and HIV risk [ie, serodiscordant unprotected anal intercourse (SDUAI)] among 3173 HIV-negative substance-using MSM. Compared with nonusers, the adjusted odds ratio (AOR) for SDUAI among episodic and at least weekly users, respectively, was 3.31 [95% confidence interval (CI), 2.55 to 4.28] and 5.46 (95% CI, 3.80 to 7.84) for methamphetamine, 1.86 (95% CI, 1.51 to 2.29) and 3.13 (95% CI, 2.12 to 4.63) for cocaine, and 2.08 (95% CI, 1.68 to 2.56) and 2.54 (95% CI, 1.85 to 3.48) for poppers. Heavy alcohol drinkers reported more SDUAI than moderate drinkers [AOR, 1.90 (95% CI, 1.43 to 2.51)]. Compared with nonusers, AORs for using 1, 2, and ≥3 substances were 16.81 (95% CI, 12.25 to 23.08), 27.31 (95% CI, 18.93 to 39.39), and 46.38 (95% CI, 30.65 to 70.19), respectively. High-risk sexual behaviors were strongly associated with frequency and number of substances used.