Emily Behar

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

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

BACKGROUND While drug users are frequently equipped with naloxone for lay opioid overdose reversal, the amount of education needed to ensure knowledge of indications and administration is unknown. METHODS We administered four instruments, assessing comfort and knowledge around opioid overdose and naloxone administration, to opioid users receiving naloxone for the first time (N=60) and upon returning for a refill (N=54) at community distribution programs. Participants completed the instruments prior to receiving naloxone; first-time recipients repeated the instruments immediately after the standardized 5-10min education. RESULTS Comfort with recognition of, response to, and administration of naloxone for an overdose event significantly increased after brief education among first-time recipients (p<0.05). Knowledge of appropriate responses to opioid overdose was high across all assessments; 96% of participants could identify at least one acceptable action to assess and one acceptable action to care for an opioid overdose. Facility with naloxone administration was high across all assessments and significantly increased for intranasal administration after education for first-time recipients (p<0.001). First-time recipients (before and after education) and refillers demonstrated a high level of knowledge on the Brief Overdose Recognition and Response Assessment, correctly identifying a mean of 13.7 out of 16 overdose scenarios. CONCLUSIONS Opioid users seeking naloxone in San Francisco have a high level of baseline knowledge around recognizing and responding to opioid overdose and those returning for refills retain that knowledge. Brief education is sufficient to improve comfort and facility in recognizing and managing overdose.

Correlates of overdose risk perception among illicit opioid users

BACKGROUND Opioid-related mortality continues to increase in the United States. The current study assesses demographic and behavioral predictors of perceived overdose risk among individuals who use opioids illicitly. By examining these correlates in the context of established overdose risk factors, we aim to assess whether characteristics and behaviors that have been associated with actual overdose risk translate to higher perception of risk. METHODS We conducted a cross-sectional survey of 172 adult illicit opioid users in San Francisco, CA and used multivariable logistic regression to identify predictors of perception of high risk for opioid overdose. RESULTS Age (aOR=0.96, 95%CI=0.93-1.00) and number of injection days per month (0.91, 0.86-0.97) were associated with a lower odds of perceived high overdose risk. There was no independent association between use of opioid analgesics, concurrent use of opioids and benzodiazepines or cocaine, or HIV status and overdose risk perception. CONCLUSIONS Opioid users who injected more frequently and those who were older were less likely to perceive themselves as being at risk of overdose, notwithstanding that those who inject more are at higher risk of overdose and those who are older are at higher risk overdose mortality. In addition, despite being established overdose risk factors, there was no relationship between use of opioid analgesics, concurrent use of opioids and cocaine or benzodiazepines, or self-reported HIV status and overdose risk perception. These findings highlight key populations of opioid users and established risk factors that may merit focused attention as part of education-based overdose prevention and opioid management strategies.

Performance Measures of Diagnostic Codes for Detecting Opioid Overdose in the Emergency Department

OBJECTIVES Opioid overdose mortality has tripled in the United States since 2000 and opioids are responsible for more than half of all drug overdose deaths, which reached an all-time high in 2014. Opioid overdoses resulting in death, however, represent only a small fraction of all opioid overdose events and efforts to improve surveillance of this public health problem should include tracking nonfatal overdose events. International Classification of Disease (ICD) diagnosis codes, increasingly used for the surveillance of nonfatal drug overdose events, have not been rigorously assessed for validity in capturing overdose events. The present study aimed to validate the use of ICD, 9th revision, Clinical Modification (ICD-9-CM) codes in identifying opioid overdose events in the emergency department (ED) by examining multiple performance measures, including sensitivity and specificity. METHODS Data on ED visits from January 1, 2012, to December 31, 2014, including clinical determination of whether the visit constituted an opioid overdose event, were abstracted from electronic medical records for patients prescribed long-term opioids for pain from any of six safety net primary care clinics in San Francisco, California. Combinations of ICD-9-CM codes were validated in the detection of overdose events as determined by medical chart review. Both sensitivity and specificity of different combinations of ICD-9-CM codes were calculated. Unadjusted logistic regression models with robust standard errors and accounting for clustering by patient were used to explore whether overdose ED visits with certain characteristics were more or less likely to be assigned an opioid poisoning ICD-9-CM code by the documenting physician. RESULTS Forty-four (1.4%) of 3,203 ED visits among 804 patients were determined to be opioid overdose events. Opioid-poisoning ICD-9-CM codes (E850.2-E850.2, 965.00-965.09) identified overdose ED visits with a sensitivity of 25.0% (95% confidence interval [CI] = 13.6% to 37.8%) and specificity of 99.9% (95% CI = 99.8% to 100.0%). Expanding the ICD-9-CM codes to include both nonspecified and general (i.e., without a decimal modifier) drug poisoning and drug abuse codes identified overdose ED visits with a sensitivity of 56.8% (95% CI = 43.6%-72.7%) and specificity of 96.2% (95% CI = 94.8%-97.2%). Additional ICD-9-CM codes not explicitly relevant to opioid overdose were necessary to further enhance sensitivity. Among the 44 overdose ED visits, neither naloxone administration during the visit, whether the patient responded to the naloxone, nor the specific opioids involved were associated with the assignment of an opioid poisoning ICD-9-CM code (p ≥ 0.05). CONCLUSIONS Tracking opioid overdose ED visits by diagnostic coding is fairly specific but insensitive, and coding was not influenced by administration of naloxone or the specific opioids involved. The reason for the high rate of missed cases is uncertain, although these results suggest that a more clearly defined case definition for overdose may be necessary to ensure effective opioid overdose surveillance. Changes in coding practices under ICD-10 might help to address these deficiencies.

Primary Care Patient Experience with Naloxone Prescription

PURPOSE Notwithstanding a paucity of data, prescription of the opioid antagonist naloxone to patients prescribed opioids is increasingly recommended in opioid stewardship guidelines. The aim of this study was to evaluate chronic pain patients’ attitudes toward being offered a naloxone prescription and their experience with naloxone. METHODS We interviewed 60 patients who received naloxone prescriptions across 6 safety-net primary care clinics (10 patients per clinic) from October 2013 to October 2015. We used a standardized questionnaire to collect information on substance use, perception of personal overdose risk, history of overdose, and experiences with naloxone prescription, including initial reaction, barriers to filling the prescription, storage and use of naloxone, associated behavioral changes, and opinions about future prescribing. RESULTS Respondents were demographically similar to all clinic patients receiving opioid prescriptions. Ninety percent had never previously received a naloxone prescription, 82% successfully filled a prescription for naloxone, and 97% believed that patients prescribed opioids for pain should be offered naloxone. Most patients had a positive (57%) or neutral (22%) response to being offered naloxone, and 37% reported beneficial behavior changes after receiving the prescription; there were no harmful behavior changes reported. Although 37% had personally experienced an opioid-poisoning event (17% of which were described as bad reactions but consistent with an overdose) and 5% reported that the prescribed naloxone had been used on them, 77% estimated their risk of overdose as low. CONCLUSIONS Primary care patients on opioids reported that receiving a prescription for naloxone was acceptable, the prescription reached patients who had not had access to naloxone, and having naloxone may be associated with beneficial changes in opioid use behaviors. Patients prescribed opioids may not interpret the terminology describing overdose to imply unintentional opioid poisoning.

Acceptability of Naloxone Dispensing Among Pharmacists

Background: The San Francisco Department of Public Health initiated naloxone prescribing at 6 safety net clinics. We evaluated this intervention, demonstrating that naloxone prescribing from primary care clinics is feasible and acceptable. Objective: To evaluate acceptability of naloxone dispensing to patients prescribed opioids among pharmacists serving clinics participating in a naloxone intervention. Methods: We surveyed 58 pharmacists from November 2013 through January 2015 at pharmacies that serviced San Francisco safety net clinics. Surveys collected information on demographics, experiences in dispensing naloxone, and interest in prescriptive authority. We conducted descriptive analyses and assessed bivariate relationships. Results: Most respondents were staff (56.9%) or supervising pharmacists (34.5%). Most (92.9%) were aware their pharmacy stocked naloxone and 86.8% felt it should be prescribed to some or all patients on long-term opioids. Most (82.1%) dispensed naloxone at least once in the past 12 months. More than half were comfortable providing naloxone education. Nearly half (43.4%) indicated they would want authority to furnish without a prescription. Over half (55.2%) reported no problems dispensing. The common problem was insufficient naloxone knowledge. Only 12% reported more than one problem in dispensing naloxone, which was associated with being uncomfortable with educating patients (P = .03). Conclusion: Naloxone dispensing was acceptable among pharmacists. Their most cited problem was insufficient naloxone education. This may be resolved with improved instructional materials, incentives for patient education, or mandatory training.

Quantity fluctuations of illicitly used opioids and overdose risk

BACKGROUND Reduced opioid tolerance is believed to be associated with overdose risk, although this relationship has primarily been examined in the context of gaps and frequency of opioid use. We sought to assess how changes in the quantity of opioids used, as opposed to periods of abstinence or overall frequency of use, relate to overdose risk. METHODS Among repeated visits of participants of a behavioral intervention trial from 2014 to 2016, we used multivariable logistic regression models fit with generalized estimating equations to examine the relationship between the percentage of opioid use days on which individuals used more or less than the quantity they used on average (i.e., quantity volatility) and the occurrence of opioid overdose. RESULTS Our sample included 290 four-month reporting periods among 63 participants (67% male). Opioid overdose events were reported by 28 (44%) participants during 48 (17%) reporting periods. Our measure of quantity volatility had a median of 20% (IQR 0.0-50.0). In multivariable analysis, using a quantity different than the quantity used on average on more than 20% of all opioid use days in the reporting period was significantly associated with odds of any opioid overdose (Adjusted OR = 3.55, 95%CI = 1.55-8.13, p = 0.003), controlling for confounders. CONCLUSION Quantity volatility of illicitly used opioids was positively associated with overdose risk and may contribute to the complex system of overlapping factors that influence overdose risk. Future observational research among opioid users should collect detailed opioid use data, including quantity used over time, to clarify the patterns that most elevate overdose risk.

Behavioral intervention to reduce opioid overdose among high-risk persons with opioid use disorder: A pilot randomized controlled trial

Objective The United States is amidst an opioid epidemic, including synthetic opioids that may result in rapid death, leaving minimal opportunity for bystander rescue. We pilot tested a behavioral intervention to reduce the occurrence of opioid overdose among opioid dependent persons at high-risk for subsequent overdose. Materials and methods We conducted a single-blinded randomized-controlled trial of a repeated dose motivational interviewing intervention (REBOOT) to reduce overdose versus treatment as usual, defined as information and referrals, over 16 months at the San Francisco Department of Public Health from 2014–2016. Participants were 18–65 years of age, had opioid use disorder by Structured Clinical Interview, active opioid use, opioid overdose within 5 years, and prior receipt of naloxone kits. The intervention was administered at months 0, 4, 8, and 12, preceded by the assessment which was also administered at month 16. Dual primary outcomes were any overdose event and number of events, collected by computer-assisted personal interview, as well as any fatal overdose events per vital records. Results A total of 78 persons were screened and 63 enrolled. Mean age was 43 years, 67% were born male, 65% White, 17% African-American, and 14% Latino. Ninety-two percent of visits and 93% of counseling sessions were completed. At baseline, 33.3% of participants had experienced an overdose in the past four months, with a similar mean number of overdoses in both arms (p = 0.95); 29% overdosed during follow-up. By intention-to-treat, participants assigned to REBOOT were less likely to experience any overdose (incidence rate ratio [IRR] 0.62 [95%CI 0.41–0.92, p = 0.019) and experienced fewer overdose events (IRR 0.46, 95%CI 0.24–0.90, p = 0.023), findings that were robust to sensitivity analyses. There were no differences between arms in days of opioid use, substance use treatment, or naloxone carriage. Conclusions REBOOT reduced the occurrence of any opioid overdose and the number of overdoses. Trial registration clinicaltrials.gov NCT02093559