Applied Sciences

Predictors of participant engagement and naloxone utilization in a community-based naloxone distribution program

Christopher Rowe1, Glenn-Milo Santos2,3, Eric Vittinghoff3, Eliza Wheeler4, Peter Davidson5 & Philip O. Coffin2,3

University of California, Berkeley, School of Public Health, Division of Epidemiology, Berkeley, CA, USA,1 San Francisco Department of Public Health, San Francisco, CA, USA,2 University of California, San Francisco, San Francisco, CA, USA,3 Drug Overdose Prevention and Education Project, Harm Reduction Coalition, Oakland, CA, USA4 and University of California, San Diego, La Jolla, CA, USA5

ABSTRACT

Aims To describe characteristics of participants and overdose reversals associated with a community-based naloxone distribution program and identify predictors of obtaining naloxone refills and using naloxone for overdose reversal.

Design Bivariate statistical tests were used to compare characteristics of participants who obtained refills and reported overdose reversals versus those who did not. We fitted multiple logistic regression models to identify predictors of refills and reversals; zero-inflated multiple Poisson regression models were used to identify predictors of number of refills and reversals. Setting San Francisco, California, USA. Participants Naloxone program participants registered and reversals reported from 2010 to 2013. Measurements Baseline characteristics of participants and reported characteristics of reversals. Findings A total of 2500 participants were registered and 702 reversals were reported from 2010 to 2013. Participants who had witnessed an overdose [adjusted odds ratio (AOR)=2.02, 95% confidence interval (CI)=1.53–2.66; AOR=2.73, 95% CI=1.73–4.30] or used heroin (AOR=1.85, 95% CI= 1.44–2.37; AOR=2.19, 95% CI=1.54–3.13) or methamphetamine (AOR=1.71, 95% CI=1.37–2.15; AOR=1.61, 95% CI=1.18–2.19) had higher odds of obtaining a refill and reporting a reversal, respectively. African American (AOR=0.63, 95% CI=0.45–0.88) and Latino (AOR=0.65, 95% CI= 0.43–1.00) participants had lower odds of obtaining a naloxone refill, whereas Latino participants who obtained at least one refill reported a higher number of refills [incidence rate ratio (IRR)=1.33 (1.05–1.69)]. Conclusions Community naloxone distribution programs are capable of reaching sizeable populations of high-risk individuals and facilitating large numbers of overdose reversals. Community members most likely to engage with a naloxone program and use naloxone to reverse an overdose are active drug users.

Keywords Harm reduction, heroin, methamphetamine, naloxone, opiates, overdose, substance use.

Correspondence to: Philip O. Coffin, San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, CA 94102, USA. E-mail: pcoffin@gmail.com

Submitted 10 October 2014; initial review completed 6 February 2015; final version accepted 16 April 2015

INTRODUCTION

Drug-related deaths increased 92.7% world-wide between 1990 and 2013 [1], and drug overdose has been the larg- est cause of injury-related death among US adults since 2008 [2–4], a trend driven by increased opioid overdose mortality [5]. Naloxone, a short-acting mu-opioid antago- nist with no abuse potential, is recommended by theWorld Health Organization and others as a key strategy to reduce mortality related to opioid overdose [6–13]. Naloxone has been distributed to heroin users to facilitate lay reversal of

opioid overdoses since the mid-1990s [6,9,14]. As of 2010, there were at least 188 naloxone distribution programs in the United States but no programs in 19 of the 25 states with drug overdose death rates above the 2008median, indicating a critical need to expand commu- nity access to naloxone [6].

Extant literature demonstrates that drug users accept lay naloxone provision and frequently utilize naloxone suc- cessfully to reverse opioid overdoses [9]. Multiple studies also demonstrate reductions in opioid overdose associated temporally with introduction and expansion of naloxone

© 2015 Society for the Study of Addiction Addiction, 110, 1301–1310

RESEARCH REPORT doi:10.1111/add.12961

programming, including an interrupted time–series analy- sis demonstrating a relative reduction in opioid overdose in communities that distributed naloxone compared to those that did not distribute naloxone [15,16]. Cohort and pro- grammatic data from naloxone programs have described demographics as well as rates and characteristics of rever- sals [9]. Generally, 10–20% of substance users given nalox- onewill passively report a reversal event [17–19]; however, it is unclear what predicts reversals and what happens to the majority of naloxone kits. Understanding who is con- tinuing to access naloxone programs and who effectively utilizes naloxone in the community would identify pro- gramming strengths and gaps and inform the cost-effective expansion of community naloxone distribution.

To address these gaps, we analyzed data from the Drug Overdose Prevention Education Project (DOPE), a San Francisco County overdose prevention and naloxone distri- bution program in operation since 2003. DOPE was the first naloxone distribution program in the United States to be sanctioned and supported by a health department, the San Francisco Department of Public Health, and a prior study reported on participant demographics and refill and reversal characteristics between 2003 and 2009 [18]. Uti- lizing more comprehensive data collection from 2010 on- wards to understand who engages with a community naloxone program, we attempted to (1) describe DOPE par- ticipants and reversal events between 2010 and 2013, (2) compare demographic characteristics among subgroups based on whether or not they had returned to a DOPE site to obtain a refill of naloxone (henceforth referred to as a re- fill) or used naloxone to reverse an overdose (henceforth re- ferred to as a reversal), (3) identify predictors of obtaining refills and reporting reversals and (4) identify predictors of the numbers of refills obtained and reversals reported.

METHODS

Data collection and measures

DOPE participants

DOPE provides brief (5–10-minute) training for anyone who might witness or experience an opioid overdose in how to recognize and respond to overdose and dispenses two-dose intranasal or injectable naloxone kits. Services are provided at needle exchange sites, re-entry programs, pain management clinics, opioid substitution treatment programs and single room occupancy hotels (SROs). All participants complete a brief questionnaire during enroll- ment, linked to a unique identifier based on personal infor- mation that can be easily recalled on return to the program. Data collected include birth date, race/ethnicity, gender, housing status, use of specific substances in the preceding 30days and history of prior overdose, witnessing

of an overdose, naloxone administration and witnessing of naloxone administration.

Naloxone refill and reversal events

Participants returning to obtain a new naloxone kit com- pleted a separate questionnaire in which they indicated whether the refill was due to use or loss of their previous kit. If the participant had used the naloxone, they were asked about the individual to whom the naloxone was ad- ministered (e.g. relationship to recipient, substances used), as well as the setting and result of the naloxone administration.

Analysis

Due to more comprehensive data collection since 2010, we limited analysis to participants registered since 2010 and reversals performed since 2010. All data were ana- lyzed using Stata version 12 (College Station, TX, USA). This study was approved and deemed exempt from review by the University of California San Francisco Committee on Human Research (institutional review board study ID 12-09877).

DOPE participants

All participants were categorized into subgroups according to whether or not they had obtained a refill or reported an overdose reversal using naloxone. We calculated the mean age and frequencies of demographic and behavioral mea- sures for all participants and those in each subgroup.

Demographic and behavioral characteristic compari- sons between those who obtained a refill and those who did not, as well as between those who reported a reversal and those who did not, were conducted using unpaired Student’s t-test and Fisher’s exact test. We excluded any re- cords of clinical registration (n=9) and refills (n=10) where a single unique identifier was given to multiple indi- viduals at initial registration and that unique identifier was associated with at least one refill. Additionally, we excluded from analysis any records of refills (n=183) where no unique identifier could be linked to an existing clinical registration.

We also conducted a subgroup analysis among partici- pants who obtained refills, in which we compared charac- teristics of those who did and did not report a reversal (please see Supporting information, Table S1)

Naloxone administration events

We calculated frequencies of circumstantial measures for all naloxone administration events occurring between 1 January 2010 and 31December 2013, regardless of when the participant underwent initial clinical registration or whether their unique identifier could be linked to an existing clinical registration.

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Multiple regression analyses

We used multiple logistic regression models to examine the relationship between demographic (e.g. age, gender, race, housing status) and behavioral characteristics (e.g. prior experience of overdose, prior witnessing of overdose, sub- stance use) of participants trained from 2010 to 2013 and whether or not participants obtained naloxone refills or reported reversals in the same time-frame (see Table 3 for complete list of predictors). In sensitivity analyses, we fitted logistic regression models described above, but with measures on baseline history of naloxone administration andwitnessing of naloxone administration, instead of base- line history of witnessing an overdose; these predictors were not fitted simultaneously to avoid collinearity.We also conducted a subgroup analysis examining predictors of re- fills and reversals restricted to opioid users.

We conducted an exploratory analysis assessing poten- tial synergistic effects between demographic characteristics (age, race and gender) and specific behavioral characteris- tics (heroin use, meth use and history of witnessing an overdose) in separate multiple logistic regression models predicting odds of obtaining a naloxone refill. We used like- lihood ratio tests to assess the joint statistical significance of the independent contributions of each set of interaction terms. Jointly significant interaction terms (P<0.05) were summarized qualitatively in the results due to the explor- atory nature of the analyses.

We used zero-inflated multiple Poisson regression models to examine the relationship between demographic and behavioral characteristics of participants trained from 2010 to 2013 and counts of both refills and reversals in the same time-frame. Models included the same covariates as the multiple logistic regression models as well as an offset for time of follow-up for each participant, calculated from date of initial registration to 31December 2013. The zero-inflated Poisson model rests on the assumption that in an unobservable subset of the population, the count out- come is always (structurally) zero, while in a second, com- plementary subset, it arises from a standard Poisson distribution (including the expected proportion of random zeroes). These models estimate covariate effects on both subpopulation membership as well as the mean of the Poisson distribution in the second population subset.

We conducted additional subgroup analyses limiting the logistic regression and Poisson regression models to those who had obtained refills, which is included in the ap- pendix (Supporting information, Tables S2 and S3).

RESULTS

DOPE participants

DOPE trained and prescribed naloxone to 2500 partici- pants from 2010 to 2013. The majority of participants

were male (60.5%), of European background/white (58.8%) and homeless or unstably housed (56.1%), with a mean age of 38.6 (Table 1). Most participants (73.9%) engaged in some illicit substance use in the 30days prior to initial registration; 50.7% used opioids. Roughly one- third of participants had overdosed (32.5%) and nearly twice as many (63.7%) had witnessed at least one over- dose. Approximately one-third (32.0%) had witnessed nal- oxone administration and 10.8% had used naloxone on another individual prior to their initial training.

Among participants who obtained at least one refill, the median number of refills was one [interquartile range (IQR)=1–3]. The differences between participants who obtained at least one refill compared to thosewho did not re- turn for any refills are summarized in Table 1. Those who received refills were significantly more likely to be male, of European background, homeless or unstably housed or to have previously overdosed, witnessed an overdose, used naloxone on another individual or witnessed the use of naloxone on another individual. Additionally, participants who obtained refills were more likely to use any drugs, mul- tiple drugs, heroin, other opioids or methamphetamine.

Correlates were similar for those who reported at least one reversal (median overdose reversals reported was one (IQR=1–2). Compared to those who did not report any re- versals, those who reported at least one reversal were younger, more likely to be of European background and homeless or unstably housed or to have overdosed, witnessed an overdose, used naloxone on another individ- ual or witnessed the use of naloxone on another individual. Additionally, participants who reported reversals were more likely to use any drugs, multiple drugs, heroin or methamphetamine.

Comparisons between participants who did and did not report reversals among those who obtained refills are pre- sented in Supporting information, Table S1.

Naloxone administration events

DOPE recorded 702 naloxone administration events be- tween 2010 and 2013 (405 reported by participants ini- tially registered from 2010 to 2013, 270 by participants registered before 2010 and 27 by participants whose unique identifier was not linkable to a registration record). Themost common setting was a private residence (40.5%), followed by a SRO (29.6%). Naloxone was used mainly on companions or acquaintances of participants (74.6%) and 95.7% of recipients were known to have survived. Of 10 re- ported deaths (1.4% of reversals), in six cases participants reported that they arrived too late but administered nalox- one anyway. Heroin was the most commonly reported sub- stance consumed by the person reversed by naloxone (90.3%). Roughly one-quarter (27.4%) of reversal attempts also involved a call to emergencymedical services (Table 2).

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Table 1 Baseline characteristics of Drug Overdose Prevention Education Project (DOPE) participants registered 2010–13 by refill and reversal status.

All participants Participants who obtained a refill†

Participants who did not obtain a refill

Participants who reported a reversal†

Participants who did not report a reversal

Demographic and behavioral characteristics* n (%) n (%) n (%) n (%) n (%)

n 2500 613 (24.5) 1887 (75.5) 257 (10.3) 2243 (89.7) Mean ageb (SD) 38.6 (12.7) 38.0 (12.1) 38.8 (12.9) 37.1 (12.3) 38.8 (12.7) Gendera

Male 1513 (60.5) 403 (65.7) 1110 (58.8) 170 (66.1) 1343 (59.9) Female 929 (37.2) 199 (32.5) 730 (38.7) 81 (31.5) 848 (37.8) Transgender/other gender 55 (2.2) 11 (1.8) 44 (2.3) 6 (2.3) 49 (2.2) Missing 3 (0.1) 0 (0.0) 3 (0.2) 0 (0.0) 3 (0.1)

Racea

European background/white 1471 (58.8) 403 (65.7) 1068 (56.6) 181 (70.4) 1290 (57.5) African American 505 (20.2) 79 (12.9) 426 (22.6) 26 (10.1) 479 (21.4) Latino 224 (9.0) 41 (6.7) 183 (9.7) 16 (6.2) 208 (9.3) Mixed/other race 264 (10.6) 79 (12.9) 185 (9.8) 28 (10.9) 236 (10.5) Missing 36 (1.4) 11 (1.8) 25 (1.3) 6 (2.3) 30 (1.3)

Housing statusa,b

Stably housed 1007 (40.3) 197 (32.1) 810 (42.9) 86 (33.5) 921 (41.1) Homeless/unstably housed 1403 (56.1) 391 (63.8) 1012 (53.6) 156 (60.7) 1247 (55.6) Missing 90 (3.6) 25 (4.1) 65 (3.4) 15 (5.8) 75 (3.3)

Overdosea,b

Prior overdose 813 (32.5) 256 (41.8) 557 (29.5) 120 (46.7) 693 (30.9) No prior overdose 1505 (60.2) 296 (48.3) 1209 (64.1) 111 (43.2) 1394 (62.1) Missing 182 (7.3) 61 (10.0) 121 (6.4) 26 (10.1) 156 (7.0)

Witness of overdosea,b

Witnessed an overdose 1592 (63.7) 464 (75.7) 1128 (59.8) 210 (81.7) 1382 (61.6) Never witnessed an overdose 747 (29.9) 97 (15.8) 650 (34.4) 27 (10.5) 720 (32.1) Missing 162 (6.5) 52 (8.5) 110 (5.8) 20 (7.8) 142 (6.3)

Naloxone administrationa,b

Administered naloxone 270 (10.8) 100 (16.3) 170 (9.0) 68 (26.5) 202 (9.0) Never administered naloxone 2016 (80.6) 451 (73.6) 1565 (82.9) 166 (64.6) 1850 (82.5) Missing 214 (8.6) 62 (10.1) 152 (8.1) 23 (8.9) 191 (8.5)

Witness of naloxone administrationa,b

Witnessed naloxone administration 800 (32.0) 280 (45.7) 520 (27.6) 147 (57.2) 653 (29.1) Never witnessed naloxone administration 1484 (59.4) 270 (44.0) 1214 (64.3) 87 (33.9) 1397 (62.3) Missing 216 (8.6) 63 (10.3) 153 (8.1) 23 (8.9) 193 (8.6)

General substance use in last 30 daysa,b

Any substance use 1847 (73.9) 508 (82.9) 1339 (71.0) 216 (84.0) 1631 (72.7) No substance use 265 (10.6) 19 (3.1) 246 (13.0) 9 (3.5) 256 (11.4) Missing 388 (15.5) 86 (14.0) 302 (16.0) 32 (12.5) 356 (15.9) Polydrug use in last 30 daysa,b

Polydrug use 1144 (45.8) 371 (60.5) 773 (41.0) 171 (66.5) 973 (43.4) No polydrug use 968 (38.7) 156 (25.4) 812 (43.0) 54 (21.0) 914 (40.7) Missing 388 (15.5) 86 (14.0) 302 (16.0) 32 (12.5) 356 (15.9) Specific substance use in last 30 days Any opioidsa,b 1267 (50.7) 399 (65.1) 868 (46.0) 177 (68.9) 1090 (48.6) Heroina,b 892 (35.7) 318 (51.9) 574 (30.4) 151 (58.8) 741 (33.0) Methadonea,b 584 (23.4) 193 (31.5) 391 (20.7) 82 (31.9) 502 (22.4) Benzodiazepinesa,b 497 (19.9) 174 (28.4) 323 (17.1) 87 (33.9) 410 (18.3) Other opioidsa,b 612 (24.5) 206 (33.6) 406 (21.5) 95 (37.0) 517 (23.0) Cocaine/cracka,b 687 (27.5) 219 (35.7) 468 (24.8) 93 (36.2) 594 (26.5) Alcohol 864 (34.6) 221 (36.1) 643 (34.1) 90 (35.0) 774 (34.5) Methamphetamine/speeda,b 776 (31.0) 268 (43.7) 508 (26.9) 122 (47.5) 654 (29.2) Other substances 371 (14.8) 107 (17.5) 264 (14.0) 48 (18.7) 323 (14.4)

*All characteristics were assessed at baseline during initial registration between 1 January 2010 and 31 December 2013. †All considered refills and reversals occurred between 1 January 2010 and 31 December 2013. aP< 0.05 for Fisher’s exact test or t-test comparing participants who did and did not obtain refills. bP< 0.05 for Fisher’s exact test or t-test comparing participants who did and did not report reversals. SD = standard deviation.

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Multiple regression analyses

The results of multiple logistic regression analyses evalu- ating predictors of obtaining at least one refill and reporting at least one reversal are summarized in Table 3. With regard to refills, African American and Latino partic- ipants had lower odds of obtaining a refill. Participants of

mixed/other race and those who had witnessed an overdose, used heroin or used methamphetamine had higher odds of obtaining a refill. In a subgroup analysis ex- amining only opioid-using participants, African American participants also had lower odds of obtaining a naloxone refill [adjusted odds ratio (AOR)=0.59, 95% confidence interval (CI) =0.39–0.90].

Table 2 Characteristics of reported reversal events reported 2010–13 byDrugOverdose Prevention Education Project (DOPE) participants.

Reversals by all participants, regardless of initial registration date

Reversals by participants initially registered 2010–13

n (%) n (%)

n 702 405 Setting Private residence 284 (40.5) 154 (38.0) Single room occupancy hotel (SRO) 208 (29.6) 120 (29.6) Public park 58 (8.3) 39 (9.6) Public toilet 27 (3.8) 15 (3.7) Other 102 (14.5) 70 (17.3) Missing 23 (3.3) 7 (1.7) Recipient relationship Companion (friend, partner, family member) 524 (74.6) 295 (72.8) Stranger 139 (19.8) 91 (22.5) Self 34 (4.8) 17 (4.2) Missing 5 (0.7) 2 (0.5) Result Reversed, all reasons 673 (95.9) 390 (96.3) Reversed due to participant administering naloxone 658 (93.7) 385 (95.1) Reversed following EMS response 15 (2.1) 5 (1.2) Death 10† (1.4) 9 (2.2) Unknown 9 (1.3) 1 (0.2) Missing 10 (1.4) 2 (0.5) General substance use details Single substance 416 (59.3) 246 (60.7) Multiple substances 286 (40.7) 159 (39.3) Missing 18 (2.6) 9 (2.2) Specific substance Heroin 634 (90.3) 363 (89.6) Heroin alone 379 (54.0) 222 (54.8) Heroin with other substances 255 (36.3) 141 (34.8) Benzodiazepine 107 (15.2) 57 (14.1) Alcohol 109 (15.5) 56 (13.8) Other opioids 90 (12.8) 58 (14.3) Meth 86 (12.3) 53 (13.1) Cocaine/crack 54 (7.7) 30 (7.4) Methadone 37 (5.3) 20 (4.9) Other drugs 14 (2.0) 8 (2.0) Other measures taken Sternum rub 243 (34.6) 136 (33.6) Call 9-1-1 192 (27.4) 118 (29.1) Rescue breathing 364 (51.9) 209 (51.6) Missing 3 (0.4) 1 (0.2)

†Of 10 deaths, victim was already deceased in two, respondent reported arriving ‘too late’ in four others. EMS = emergency medical services.

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In the exploratory models addressing the interaction ef- fects between demographic and behavioral predictors, those with history of overdose had differential odds of obtaining a refill depending on the race of the participant, with a stronger effect among African Americans and participants of mixed/other race compared to participants of European background. There were no other significant interaction effects in these models.

With regard to reversals, participants who used alcohol had lower odds of reporting a reversal while participants who had witnessed an overdose, used heroin or used methamphetamine had higher odds of reporting a reversal. In a subgroup analysis examining only opioid- using participants, African American participants had lower odds of reporting a reversal (AOR=0.50, 95% CI=0.26–0.95).

In sensitivity analyses, both prior naloxone administra- tion (AOR=1.37, 95% CI=1.01–1.88; AOR 2.49, 95% CI=1.73–3.59) and previously witnessing naloxone being administered (AOR=1.85, 95% CI=1.47–2.32; AOR=2.67, 95% CI=1.94–3.67) were associated with higher odds of obtaining a refill and reporting a reversal, respectively.

Table 4 summarizes the results of the zero-inflated mul- tiple Poisson regression models evaluating predictors of the number of naloxone refills and number of overdose reversal

events among those who obtained at least one refill and re- ported at least one reversal, respectively. With regard to re- fills, Latino participants who had obtained at least one refill had a greater average number of refills than participants of European background. Participants who were homeless, had experienced an overdose, used heroin or used meth- amphetamine also had a greater average number of nalox- one refills. Those who used methadone had a lower number of refills than those who did not use methadone. With regard to reversal events, participants of mixed/other race reported a greater average number of reversals than participants of European background, and those who used heroin or methamphetamine reported a greater average number of reversal events than thosewho did not use these substances.

Results of subgroup analyses assessing the odds of reporting a reversal and the number of reversals among participants who had obtained refills are reported in the Supporting information. For themultiple logistic regression analysis among this subgroup, those who had witnessed an overdose or used heroin had higher odds of reporting a reversal (Supporting information, Table S2). For the zero-inflated multiple Poisson regression analysis among this subgroup, female participants reported a greater average number of reversals than male participants and African American participants and those of mixed/other

Table 3 Multiple logistic regression models predicting naloxone refills and reversals among Drug Overdose Prevention Education Project (DOPE) participants registered 2010–13 (n=1972).

Refill† Reversal†

AOR 95% CI P-value AOR 95% CI P-value

Age 1.01 (1.00, 1.02) 0.125 1.00 (0.99, 1.02) 0.620 Gender Male – – – – – – Female 0.81 (0.64, 1.02) 0.073 0.96 (0.70, 1.33) 0.825 Transgender/other 0.76 (0.32, 1.81) 0.533 1.27 (0.42, 3.84) 0.666 Race European background/white – – – – – – African American 0.63* (0.45, 0.88) 0.007 0.62 (0.37, 1.03) 0.063 Latino 0.65* (0.43, 1.00) 0.050 0.58 (0.31, 1.09) 0.091 Mixed/other race 1.51* (1.07, 2.11) 0.018 1.13 (0.70, 1.82) 0.614 Homeless 1.14 (0.90, 1.44) 0.280 0.95 (0.69, 1.30) 0.734 Prior overdose 1.03 (0.82, 1.31) 0.775 1.14 (0.83, 1.57) 0.411 Witnessed overdose 2.02* (1.53, 2.66) <0.001 2.73* (1.73, 4.30) <0.001 Use heroin 1.85* (1.44, 2.37) <0.001 2.19* (1.54, 3.13) <0.001 Use methadone 1.22 (0.96, 1.56) 0.109 0.99 (0.71, 1.37) 0.934 Use benzodiazepines 1.14 (0.87, 1.51) 0.340 1.35 (0.94, 1.94) 0.108 Use other opioids 1.18 (0.92, 1.52) 0.201 1.25 (0.89, 1.75) 0.203 Use cocaine/crack 0.15 (0.92, 1.52) 0.187 1.04 (0.74, 1.46) 0.833 Use alcohol 0.82 (0.65, 1.03) 0.094 0.72* (0.52, 1.00) 0.049 Use methamphetamine 1.71* (1.37, 2.15) <0.001 1.61* (1.18, 2.19) 0.003 Use other drugs 1.00 (0.75, 1.32) 0.978 0.97 (0.66, 1.43) 0.875

†All considered refills and reversals occurred between 1 January 2010 and 31 December 2013. *P ≤ 0.05. AOR= adjusted odds ratio; CI = confidence interval.

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race reported a greater average number of reversals than participants of European background. Participants who had a prior overdose, used heroin or usedmethamphetamine also

reported greater average numbers of reversals. Participants who used cocaine or crack reported a lower average number of reversals (Supporting information, Table S2).

Table 4 Zero-inflated multiple Poisson regression models predicting naloxone refill and reversal counts among Drug Overdose Prevention Education Project (DOPE) participants registered 2010–13 (n=1972).

Refill count† Refill count inflate component†

IRR 95% CI P-value Coefficient 95% CI P-value

Age 0.98* (0.98, 0.99) <0.001 –0.03* (–0.04, –0.01) <0.001 Gender Male – – – – – – Female 1.11 (0.97, 1.28) 0.132 0.29* (0.01, 0.57) 0.040 Transgender/other 0.90 (0.48, 1.68) 0.745 0.32 (–0.79, 1.43) 0.577 Race European background/white – – – – – – African American 0.97 (0.75, 1.26) 0.831 0.62* (0.20, 1.05) 0.004 Latino 1.33* (1.05, 1.69) 0.019 0.67* (0.19, 1.15) 0.006 Mixed/other race 0.84 (0.69, 1.03) 0.095 –0.60* (–1.06, –0.15) 0.010 Homeless 1.24* (1.07, 1.45) 0.005 0.06 (–0.24, 0.35) 0.711 Prior overdose 1.22* (1.07, 1.41) 0.004 0.05 (–0.23, 0.33) 0.732 Witnessed overdose 0.96 (0.81, 1.15) 0.683 –0.70* (–1.02, –0.38) <0.001 Use heroin 1.30* (1.09, 1.54) 0.003 –0.62* (–0.93, –0.31) <0.001 Use methadone 0.83* (0.71, 0.96) 0.013 –0.30 (–0.61, 0.01) 0.055 Use benzodiazepines 0.93 (0.80, 1.09) 0.389 –0.28 (–0.62, 0.06) 0.110 Use other opioids 1.05 (0.90, 1.22) 0.535 –0.16 (–0.47, 0.15) 0.321 Use cocaine/crack 1.09 (0.94, 1.27) 0.240 –0.08 (–0.39, 0.23) 0.601 Use alcohol 0.93 (0.80, 1.07) 0.298 0.21 (–0.08, 0.49)_ 0.158 Use methamphetamine 1.83* (1.57, 2.13) <0.001 –0.36* (–0.64, –0.08) 0.011 Use other drugs 0.79* (0.66, 0.95) 0.012 –0.10 (–0.46, 0.25) 0.563

Reversal count† Reversal count inflate component†

IRR 95% CI P-value Coefficient 95% CI P-value

Age 0.99 (0.98, 1.01) 0.432 –0.01 (–0.03, 0.00) 0.133 Gender Male – – – – – – Female 1.31 (0.95, 1.81) 0.105 0.20 (–0.20, 0.61) 0.328 Transgender/other 0.92 (0.28, 2.97) 0.884 –0.20 (–1.60, 1.19) 0.776 Race European background/white – – – – – – African American 1.49 (0.83, 2.65) 0.180 0.88* (0.23, 1.53) 0.008 Latino 1.56 (0.93, 2.61) 0.094 0.91* (0.19, 1.63) 0.013 Mixed/other race 1.75* (1.16, 2.65) 0.008 0.25 (–0.31, 0.81) 0.383 Homeless 0.84 (0.61, 1.16) 0.297 0.00 (–0.41, 0.41) 0.994 Prior overdose 1.29 (0.94, 1.76) 0.114 0.01 (–0.40, 0.42) 0.955 Witnessed overdose 1.33 (0.82, 2.15) 0.248 –0.86* (–1.44, –0.29) 0.003 Use heroin 1.61* (1.05, 2.47) 0.028 –0.62* (–1.11, –0.13) 0.013 Use methadone 0.96 (0.70, 1.30) 0.789 0.08 (–0.35, 0.50) 0.727 Use benzodiazepines 1.00 (0.68, 1.47) 0.996 –0.40 (–0.89, 0.08) 0.105 Use other opioids 1.07 (0.76, 1.51) 0.701 –0.23 (–0.68, 0.22) 0.312 Use cocaine/crack 0.81 (0.58, 1.14) 0.230 –0.12 (–0.57, 0.32) 0.589 Use alcohol 0.84 (0.61, 1.16) 0.295 0.27 (–0.15, 0.69) 0.203 Use methamphetamine 1.61* (1.18, 2.19) 0.003 –0.31 (–0.71, 0.09) 0.132 Use other drugs 0.85 (0.57, 1.25) 0.412 –0.06 (–0.57, 0.45) 0.816

†All considered refills and reversals occurred between 1 January 2010 and 31 December 2013. *P ≤ 0.05. IRR = incidence risk ratio; CI = confidence interval.

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DISCUSSION

We identified unique demographic and behavioral charac- teristics associated with continuous engagement in a nal- oxone distribution program. Specifically, we observed that participants who were of European background, had prior experiences with overdoses and used heroin or metham- phetamine were more likely to return for refills and those who had prior experiences with overdoses and used heroin or methamphetamine were more likely to report reversals. To our knowledge, these findings are the first to analyze predictors of obtaining naloxone refills and of reporting re- versals. These results emphasize the impact, with regard to utilization of this medication, of directly reaching drug users with lay naloxone programming.

DOPE participants were mainly of European back- ground, homeless or unstably housed and used multiple substances, while approximately one-third drank alcohol and one-third reported a prior personal overdose. These findings are highly consistent with other research on over- dose identifying European background, homelessness, use of multiple substances, use of alcohol and having experi- enced a prior overdose as risk factors for a subsequent over- dose [20–23]. These results suggest that naloxone distributed through DOPE is reaching very high-risk indi- viduals and, based on the multiple logistic regression anal- yses, that these high-risk individuals are also the most likely to utilize this intervention in an overdose scenario.

Additionally, multiple logistic regression analyses re- vealed that witnessing an overdose was associated signifi- cantly with greater odds of both obtaining a refill and reporting a reversal. This relationship is supported by the Information–Motivation–Behavior Skills (IMB) model of behavior change, which posits that behavior change occurs when individuals have information about a target behavior, motivation to prevent future outcomes and skills to prevent or reverse outcomes [24,25]. DOPE offers information on overdose management; having witnessed an overdose may; provide the motivation to prepare for future overdoses and DOPE provides participants with tools to address overdose. Our findings suggest that those who are at high risk for overdose are also likely to witness an overdose, consistent with other data, and that the most efficient approach to getting naloxone at the scene of overdose events is to put it in the hands of those at greatest risk for overdose themselves [26].

We also reported several unique findings that merit fur- ther exploration. Participants who used methadone ob- tained fewer refills; if methadone use was in a maintenance program, participants may be using illicit opioids less frequently and thus be less likely to visit a DOPE site or witness an overdose [27]. Participants reporting methamphetamine use had higher odds of obtaining a refill and reporting a reversal. We assessed and found a

significant bivariate association between methamphet- amine use and polydrug use, suggesting that methamphet- amine users may be more likely to use multiple substances, highlighting the importance of engaging drug users broadly, and not just opioid users, as part of naloxone distri- bution programs.

With regard to race/ethnicity, African Americans con- stitute only 6.1% of San Francisco County residents yet made up 23.9% of accidental drug-related deaths in 2010–11, including those related to opioid overdose [28,29], and 20% of DOPE participants, again suggesting that DOPE is effective in reaching at-risk populations. Moreover, Latino participants who reported obtaining re- fills on average obtained greater number of refills and, among participants who obtained refills, African Americans who reported at least one reversal on average reported more reversals (Supporting information, Table S3), suggesting that some participants of racial/ethnic minority groups were heavily engaged in naloxone programming. This is supported further by our assessment of statistical in- teraction between race and prior witnessing of an overdose, in which the association between witnessing of an over- dose and odds of obtaining a refill was stronger in African Americans and participants of mixed/other race compared to participants of European background. Regardless of these findings on number of refills and number of reversals, both African American and Latino participants had lower odds of any obtaining refills. Even among the subgroup of only-opioid-using participants, African Americans were less likely to both obtain refills and report any reversals, suggesting that this finding is robust and not mediated by drug of choice. The discrepancy between lower early en- gagement with naloxone programming and the potential for higher subsequent engagement among racial/ethnic minority participants reveals an important opportunity to further engage these populations through outreach efforts and services that are both culturally sensitive and relevant. These findings also highlight the need for further research, including the use of qualitative methods, to better under- stand the underlying causes of these racial/ethnic trends.

DOPE has documented a substantial increase in re- ported annual reversals with naloxone since 2003 (from five in 2003 to 252 in 2013), which has paralleled a sub- stantial decline in heroin-related overdose mortality in San Francisco [18,28,30,31]. Moreover, our results show that 90.3% of the naloxone administrations have targeted overdoses that involved heroin. The tendency of partici- pants to use naloxone to primarily reverse heroin-related overdoses, the growing number of reversals and the declin- ing number of deaths from heroin overdose suggest that the DOPE Project and naloxone distribution may be having an effect on population-level overdose mortality among heroin users. As heroin-related overdose mortality has de- creased in San Francisco, however, there has been a

1308 Christopher Rowe et al.

© 2015 Society for the Study of Addiction Addiction, 110, 1301–1310

corresponding rise in deaths and emergency room visits related to opioid analgesics [28,30–32]. Opioids besides heroin were used by a minority of DOPE participants and were involved in only a small minority of reversed overdoses, suggesting that DOPE activities are not sufficiently reaching the population of opioid analgesic users at risk for overdose. The finding that the use of heroin is associated with greater odds of obtaining a refill of naloxone or reporting a reversal, as shown in our multiple logistic regression analyses, is likely because most DOPE activities are based at needle exchange program sites, highlighting the need to explore alternative naloxone distri- bution streams to reach other populations at risk. Efforts are under way in San Francisco to achieve this by identifying patients receiving opioid analgesics through primary care for naloxone prescription (NIDA R21 DA036776).

This study has several limitations. All information is self-reported by participants and may be subject to social desirability and/or recall bias. Additionally, reversals were only reported by participants who visited a DOPE site to ob- tain a refill of naloxone (i.e. ‘passive surveillance’), which excludes reversals that may have been performed by partic- ipants who did not obtain refills. Thus, the reversal analy- ses may be subject to collider-stratification bias, if obtaining a refill is a common effect of our predictors and the reversals analyzed. Behavioral characteristics of partic- ipants, many of which are subject to changes over time, are only collected during initial registration, precluding the analyses from accounting for the effects of recent changes in characteristics such as housing status, substance use and overdose experience.

In conclusion, we have identified demographic and be- havioral characteristics associated with subsequent en- gagement with naloxone programming and utilization of naloxone to reverse overdoses. Our results reaffirm the suc- cess of community-based naloxone distribution in reaching the most at-risk populations and identify opportunities for service expansion to reach or re-engage other populations in need.

Acknowledgements

This study was supported by funding from the National In- stitutes of Health (NIDA R03 DA038084). The authors would like to acknowledge those who participated in the establishment and conduct of the DOPE Project, including Pete Morse, Rachel McClean, Emalie Huriaux, Lauren Enteen and Alex Kral, as well as medical director Josh Bamberger.

Disclaimer

The authors are solely responsible for the content of this article, which does not necessarily represent the official views of the San Francisco Department of Public Health.

Declarations of interest

None.

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