A randomized clinical trial of a theory-based fentanyl overdose education and fentanyl test strip distribution intervention to reduce rates of opioid overdose: study protocol for a randomized controlled trial
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Abstract
Background
Opioid overdose deaths involving synthetic opioids, particularly illicitly manufactured
fentanyl, remain a substantial public health concern in North America. Responses to
overdose events (e.g., administration of naloxone and rescue breathing) are effective
at reducing mortality; however, more interventions are needed to prevent overdoses
involving illicitly manufactured fentanyl. This study protocol aims to evaluate the
effectiveness of a behavior change intervention that incorporates individual counseling,
practical training in fentanyl test strip use, and distribution of fentanyl test strips
for take-home use among people who use drugs.
Methods
Residents of Rhode Island aged 18–65 years who report recent substance use (including
prescription pills obtained from the street; heroin, powder cocaine, crack cocaine,
methamphetamine; or any drug by injection) (
n = 500) will be recruited through advertisements and targeted street-based outreach
into a two-arm randomized clinical trial with 12 months of post-randomization follow-up.
Eligible participants will be randomized (1:1) to receive either the RAPIDS intervention
(i.e., fentanyl-specific overdose education, behavior change motivational interviewing
(MI) sessions focused on using fentanyl test strips to reduce overdose risk, fentanyl
test strip training, and distribution of fentanyl test strips for personal use) or
standard overdose education as control. Participants will attend MI booster sessions
(intervention) or attention-matched control sessions at 1, 2, and 3 months post-randomization.
All participants will be offered naloxone at enrolment. The primary outcome is a composite
measure of self-reported overdose in the previous month at 6- and/or 12-month follow-up
visit. Secondary outcome measures include administratively linked data regarding fatal
(post-mortem investigation) and non-fatal (hospitalization or emergency medical service
utilization) overdoses.
Discussion
If the RAPIDS intervention is found to be effective, its brief MI and fentanyl test
strip training components could be easily incorporated into existing community-based
overdose prevention programming to help reduce the rates of fentanyl-related opioid
overdose.
Trial registration
ClinicalTrials.gov
NCT04372238. Registered on 01 May 2020
Of the 70,237 drug overdose deaths in the United States in 2017, approximately two thirds (47,600) involved an opioid ( 1 ). In recent years, increases in opioid-involved overdose deaths have been driven primarily by deaths involving synthetic opioids other than methadone (hereafter referred to as synthetic opioids) ( 1 ). CDC analyzed changes in age-adjusted death rates from 2017 to 2018 involving all opioids and opioid subcategories* by demographic characteristics, county urbanization levels, U.S. Census region, and state. During 2018, a total of 67,367 drug overdose deaths occurred in the United States, a 4.1% decline from 2017; 46,802 (69.5%) involved an opioid ( 2 ). From 2017 to 2018, deaths involving all opioids, prescription opioids, and heroin decreased 2%, 13.5%, and 4.1%, respectively. However, deaths involving synthetic opioids increased 10%, likely driven by illicitly manufactured fentanyl (IMF), including fentanyl analogs ( 1 , 3 ). Efforts related to all opioids, particularly deaths involving synthetic opioids, should be strengthened to sustain and accelerate declines in opioid-involved deaths. Comprehensive surveillance and prevention measures are critical to reducing opioid-involved deaths, including continued surveillance of evolving drug use and overdose, polysubstance use, and the changing illicit drug market; naloxone distribution and outreach to groups at risk for IMF exposure; linkage to evidence-based treatment for persons with substance use disorders; and continued partnerships with public safety. Drug overdose deaths were identified in National Vital Statistics System multiple cause-of-death mortality files † using the International Classification of Diseases, Tenth Revision (ICD-10) underlying cause-of-death codes X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), or Y10–Y14 (undetermined intent). Among deaths with drug overdose as the underlying cause, the opioid subcategory was determined by the following ICD-10 multiple cause-of-death codes: all opioids (T40.0, T40.1, T40.2, T40.3, T40.4, or T40.6) § ; prescription opioids (T40.2 or T40.3); heroin (T40.1); and synthetic opioids other than methadone (T40.4). Some deaths involved more than one opioid subcategory and were included in the rates for each; subcategories are not mutually exclusive. ¶ Changes from 2017 to 2018 in age-adjusted overdose death rates** were examined for all opioids, prescription opioids, heroin, and synthetic opioids. Death rates were stratified by age, sex, race/ethnicity, urbanization level, †† U.S. Census region, §§ and state. State-level analyses included 38 states and the District of Columbia (DC) with adequate drug specificity ¶¶ for 2017 and 2018.*** The drug or drugs involved in the drug overdose death were not specified on 12% of drug overdose death certificates in 2017 and on 8% of those from 2018. The percentage of 2018 death certificates with at least one drug specified ranged from 54.1% to 100% among states. Changes in death rates from 2017 to 2018 were compared using z-tests when deaths were ≥100 and nonoverlapping confidence intervals based on a gamma distribution when <100. ††† Changes presented in the text represent statistically significant findings, unless otherwise specified. During 2018, drug overdoses resulted in 67,367 deaths in the United States, a 4.1% decrease from 2017. Among these drug overdose deaths, 46,802 (69.5%) involved an opioid. From 2017 to 2018, opioid-involved death rates decreased 2.0%, from 14.9 per 100,000 population to 14.6 (Table 1); decreases occurred among females; persons aged 15–34 years and 45–54 years; non-Hispanic whites; and in small metro, micropolitan, and noncore areas; and in the Midwest and South regions. Rates during 2017–2018 increased among persons aged ≥65 years, non-Hispanic blacks, and Hispanics, and in the Northeast and the West regions. Rates decreased in 11 states and DC and increased in three states, with the largest relative (percentage) decrease in Iowa (–30.4%) and the largest absolute decrease (difference in rates) in Ohio (–9.6); the largest relative and absolute increase occurred in Missouri (18.8%, 3.1). The highest opioid-involved death rate in 2018 was in West Virginia (42.4 per 100,000). TABLE 1 Annual number and age-adjusted rate of drug overdose deaths* involving all opioids † and prescription opioids, § , ¶ by sex, age, race/ethnicity,** urbanization level, †† U.S. Census region, §§ and selected states ¶¶ — National Vital Statistics System, United States, 2017 and 2018 Decedent characteristic All opioids Prescription opioids 2017 2018 Rate change from 2017 to 2018*** 2017 2018 Rate change from 2017 to 2018*** No. (rate) No. (rate) Absolute change Relative change No. (rate) No. (rate) Absolute change Relative change All 47,600 (14.9) 46,802 (14.6) −0.3††† −2.0††† 17,029 (5.2) 14,975 (4.5) −0.7††† −13.5††† Sex Male 32,337 (20.4) 32,078 (20.1) −0.3 −1.5 9,873 (6.1) 8,723 (5.3) −0.8 ††† −13.1 ††† Female 15,263 (9.4) 14,724 (9.0) −0.4 ††† −4.3 ††† 7,156 (4.2) 6,252 (3.7) −0.5 ††† −11.9 ††† Age group (yrs) 0–14 79 (0.1) 65 (0.1) 0.0 0.0 50 (0.1) 36 (0.1) 0.0 0.0 15–24 4,094 (9.5) 3,618 (8.4) −1.1 ††† −11.6 ††† 1,050 (2.4) 790 (1.8) −0.6 ††† −25.0 ††† 25–34 13,181 (29.1) 12,839 (28.1) −1.0 ††† −3.4 ††† 3,408 (7.5) 2,862 (6.3) −1.2 ††† −16.0 ††† 35–44 11,149 (27.3) 11,414 (27.7) 0.4 1.5 3,714 (9.1) 3,350 (8.1) −1.0 ††† −11.0 ††† 45–54 10,207 (24.1) 9,565 (23.0) −1.1 ††† −4.6 ††† 4,238 (10.0) 3,490 (8.4) −1.6 ††† −16.0 ††† 55–64 7,153 (17.0) 7,278 (17.2) 0.2 1.2 3,509 (8.4) 3,291 (7.8) −0.6 ††† −7.1 ††† ≥65 1,724 (3.4) 2,012 (3.8) 0.4 ††† 11.8 ††† 1,055 (2.1) 1,152 (2.2) 0.1 4.8 Sex and age group (yrs) Male 15–24 2,885 (13.0) 2,527 (11.5) −1.5 ††† −11.5 ††† 728 (3.3) 548 (2.5) −0.8 ††† −24.2 ††† Male 25–44 17,352 (40.0) 17,240 (39.4) −0.6 −1.5 4,516 (10.4) 3,895 (8.9) −1.5 ††† −14.4 ††† Male 45–64 11,061 (26.9) 10,986 (26.8) −0.1 −0.4 4,089 (9.9) 3,637 (8.9) −1.0 ††† −10.1 ††† Female 15–24 1,209 (5.7) 1,091 (5.2) −0.5 ††† −8.8 ††† 322 (1.5) 242 (1.2) −0.3 ††† −20.0 ††† Female 25–44 6,978 (16.3) 7,013 (16.2) −0.1 −0.6 2,606 (6.1) 2,317 (5.4) −0.7 ††† −11.5 ††† Female 45–64 6,299 (14.6) 5,857 (13.6) −1.0 ††† −6.8 ††† 3,658 (8.5) 3,144 (7.3) −1.2 ††† −14.1 ††† Race/Ethnicity** White, non-Hispanic 37,113 (19.4) 35,363 (18.6) −0.8 ††† −4.1 ††† 13,900 (6.9) 12,085 (6.0) −0.9 ††† −13.0 ††† Black, non-Hispanic 5,513 (12.9) 6,088 (14.0) 1.1 ††† 8.5 ††† 1,508 (3.5) 1,444 (3.3) −0.2 −5.7 Hispanic 3,932 (6.8) 4,370 (7.5) 0.7 ††† 10.3 ††† 1,211 (2.2) 1,122 (2.0) −0.2 ††† −9.1 ††† American Indian/Alaska Native, non-Hispanic 408 (15.7) 373 (14.2) −1.5 −9.6 187 (7.2) 125 (4.7) −2.5 ††† −34.7 ††† Asian/Pacific Islander, non-Hispanic 348 (1.6) 345 (1.5) −0.1 −6.3 130 (0.6) 115 (0.5) −0.1 −16.7 County urbanization level†† Large central metro 14,518 (13.9) 14,767 (14.1) 0.2 1.4 4,945 (4.7) 4,394 (4.1) −0.6 ††† −12.8 ††† Large fringe metro 13,594 (17.2) 13,476 (17.0) −0.2 −1.2 4,273 (5.2) 3,791 (4.6) −0.6 ††† −11.5 ††† Medium metro 10,561 (16.2) 10,328 (15.8) −0.4 −2.5 3,951 (5.9) 3,539 (5.2) −0.7 ††† −11.9 ††† Small metro 3,560 (12.9) 3,379 (12.2) −0.7 ††† −5.4 ††† 1,479 (5.2) 1,278 (4.5) −0.7 ††† −13.5 ††† Micropolitan (nonmetro) 3,462 (13.9) 3,162 (12.7) −1.2 ††† −8.6 ††† 1,440 (5.6) 1,240 (4.7) −0.9 ††† −16.1 ††† Noncore (nonmetro) 1,905 (11.2) 1,690 (10.1) −1.1 ††† −9.8 ††† 941 (5.3) 733 (4.1) −1.2 ††† −22.6 ††† U.S. Census region of residence§§ Northeast 11,784 (21.3) 12,467 (22.8) 1.5 ††† 7.0 ††† 3,047 (5.3) 2,991 (5.3) 0.0 0.0 Midwest 12,483 (19.1) 11,268 (17.2) −1.9 ††† −9.9 ††† 3,702 (5.5) 2,965 (4.4) −1.1 ††† −20.0 ††† South 16,999 (14.1) 16,413 (13.5) −0.6 ††† −4.3 ††† 6,929 (5.6) 5,936 (4.7) −0.9 ††† −16.1 ††† West 6,334 (8.0) 6,654 (8.3) 0.3 ††† 3.8 ††† 3,351 (4.1) 3,083 (3.8) −0.3 ††† −7.3 ††† States with very good to excellent reporting (n = 29)¶¶ Alaska 102 (13.9) 68 (8.8) −5.1 −36.7 51 (7.0) 38 (4.9) −2.1 −30.0 Arizona 928 (13.5) 1,106 (15.9) 2.4 ††† 17.8 ††† 414 (5.9) 362 (5.0) −0.9 ††† −15.3 ††† Connecticut 955 (27.7) 948 (27.5) −0.2 −0.7 273 (7.7) 231 (6.4) −1.3 −16.9 District of Columbia 244 (34.7) 191 (26.7) −8.0 ††† −23.1 ††† 58 (8.4) 41 (5.7) −2.7 −32.1 Georgia 1,014 (9.7) 866 (8.3) −1.4 ††† −14.4 ††† 568 (5.4) 440 (4.1) −1.3 ††† −24.1 ††† Illinois 2,202 (17.2) 2,169 (17.0) −0.2 −1.2 623 (4.8) 539 (4.2) −0.6 ††† −12.5 ††† Iowa 206 (6.9) 143 (4.8) −2.1 ††† −30.4 ††† 104 (3.4) 64 (2.1) −1.3 ††† −38.2 ††† Maine 360 (29.9) 282 (23.4) −6.5 ††† −21.7 ††† 100 (7.6) 69 (5.1) −2.5 −32.9 Maryland 1,985 (32.2) 2,087 (33.7) 1.5 4.7 711 (11.5) 576 (9.2) −2.3 ††† −20.0 ††† Massachusetts 1,913 (28.2) 1,991 (29.3) 1.1 3.9 321 (4.6) 331 (4.7) 0.1 2.2 Missouri 952 (16.5) 1,132 (19.6) 3.1 ††† 18.8 ††† 253 (4.1) 265 (4.4) 0.3 7.3 Nevada 412 (13.3) 372 (11.5) −1.8 −13.5 276 (8.7) 235 (7.2) −1.5 ††† −17.2 ††† New Hampshire 424 (34.0) 412 (33.1) −0.9 −2.6 62 (4.8) 43 (3.1) −1.7 −35.4 New Mexico 332 (16.7) 338 (16.7) 0.0 0.0 171 (8.5) 176 (8.2) −0.3 −3.5 New York 3,224 (16.1) 2,991 (15.1) −1.0 ††† −6.2 ††† 1,044 (5.1) 998 (4.9) −0.2 −3.9 North Carolina 1,953 (19.8) 1,783 (17.9) −1.9 ††† −9.6 ††† 659 (6.5) 489 (4.7) −1.8 ††† −27.7 ††† Ohio 4,293 (39.2) 3,237 (29.6) −9.6 ††† −24.5 ††† 947 (8.4) 571 (5.0) −3.4 ††† −40.5 ††† Oklahoma 388 (10.2) 308 (7.8) −2.4 ††† −23.5 ††† 251 (6.7 172 (4.3) −2.4 ††† −35.8 ††† Oregon 344 (8.1) 339 (8.0) −0.1 −1.2 154 (3.5) 151 (3.4) −0.1 −2.9 Rhode Island 277 (26.9) 267 (25.9) −1.0 −3.7 99 (8.8) 85 (7.7) −1.1 −12.5 South Carolina 749 (15.5) 835 (17.1) 1.6 10.3 345 (7.1) 375 (7.4) 0.3 4.2 Tennessee 1,269 (19.3) 1,307 (19.9) 0.6 3.1 644 (9.6) 550 (8.2) −1.4 ††† −14.6 ††† Utah 456 (15.5) 437 (14.8) −0.7 −4.5 315 (10.8) 306 (10.5) −0.3 −2.8 Vermont 114 (20.0) 127 (22.8) 2.8 14.0 40 (6.3) 27 (4.4) −1.9 −30.2 Virginia 1,241 (14.8) 1,193 (14.3) −0.5 −3.4 404 (4.7) 326 (3.8) −0.9 ††† −19.1 ††† Washington 742 (9.6) 737 (9.4) −0.2 −2.1 343 (4.3) 301 (3.8) −0.5 −11.6 West Virginia 833 (49.6) 702 (42.4) −7.2 ††† −14.5 ††† 304 (17.2) 234 (13.1) −4.1 ††† −23.8 ††† Wisconsin 926 (16.9) 846 (15.3) −1.6 ††† −9.5 ††† 362 (6.4) 301 (5.3) −1.1 ††† −17.2 ††† Wyoming 47 (8.7) 40 (6.8) −1.9 −21.8 31 (6.0) 28 (4.6) −1.4 −23.3 States with good reporting (n = 10)¶¶ California 2,199 (5.3) 2,410 (5.8) 0.5 ††† 9.4 ††† 1,169 (2.8) 1,084 (2.6) −0.2 −7.1 Colorado 578 (10.0) 564 (9.5) −0.5 −5.0 300 (5.1) 268 (4.4) −0.7 −13.7 Florida 3,245 (16.3) 3,189 (15.8) −0.5 −3.1 1,272 (6.0) 1,282 (6.0) 0.0 0.0 Hawaii 53 (3.4) 59 (4.1) 0.7 20.6 40 (2.5) 33 (2.3) −0.2 −8.0 Indiana 1,176 (18.8) 1,104 (17.5) −1.3 −6.9 425 (6.6) 370 (5.6) −1.0 ††† −15.2 ††† Kentucky 1,160 (27.9) 989 (23.4) −4.5 ††† −16.1 ††† 433 (10.2) 315 (7.2) −3.0 ††† −29.4 ††† Michigan 2,033 (21.2) 2,011 (20.8) −0.4 −1.9 633 (6.5) 556 (5.6) −0.9 ††† −13.8 ††† Minnesota 422 (7.8) 343 (6.3) −1.5 ††† −19.2 ††† 195 (3.6) 136 (2.5) −1.1 ††† −30.6 ††† Mississippi 185 (6.4) 173 (6.1) −0.3 −4.7 96 (3.2) 92 (3.1) −0.1 −3.1 Texas 1,458 (5.1) 1,402 (4.8) −0.3 −5.9 646 (2.3) 547 (1.9) −0.4 −17.4 * Deaths were classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug overdose deaths were identified using underlying cause-of-death codes X40–X44, X60–X64, X85, and Y10–Y14. Rates are age-adjusted using the direct method and the 2000 U.S. standard population, except for age-specific crude rates. All rates are per 100,000 population. † Drug overdose deaths, as defined, that have opium (T40.0), heroin (T40.1), natural and semisynthetic opioids (T40.2), methadone (T40.3), synthetic opioids other than methadone (T40.4) or other and unspecified narcotics (T40.6) as a contributing cause. § Drug overdose deaths, as defined, that have natural and semisynthetic opioids (T40.2) or methadone (T40.3) as a contributing cause. ¶ Categories of deaths are not exclusive as deaths might involve more than one drug category. Summing of categories will result in more than the total number of deaths in a year. ** Data for Hispanic origin should be interpreted with caution; studies comparing Hispanic origin on death certificates and on Census surveys have shown inconsistent reporting on Hispanic ethnicity. Potential race misclassification might lead to underestimates for certain categories, primarily American Indian/Alaska Native non-Hispanic and Asian/Pacific Islander non-Hispanic decedents. https://www.cdc.gov/nchs/data/series/sr_02/sr02_172.pdf. †† By the 2013 National Center for Health Statistics Urban-Rural Classification Scheme for Counties. https://www.cdc.gov/nchs/data_access/urban_rural.htm. §§ Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont. Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia. West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. ¶¶ Analyses were limited to states meeting the following criteria. States with very good to excellent reporting had ≥90% of drug overdose deaths mention at least one specific drug in 2017, with the change in drug overdose deaths mentioning of at least one specific drug differing by <10 percentage points from 2017 to 2018. States with good reporting had 80% to <90% of drug overdose deaths mention at least one specific drug in 2017, with the change in the percentage of drug overdose deaths mentioning at least one specific drug differing by <10 percentage points from 2017 to 2018. States included also were required to have stable rate estimates (i.e., based on ≥20 deaths in at least two of the following drug categories: opioids, prescription opioids, synthetic opioids other than methadone, and heroin). *** Absolute rate change is the difference between 2017 and 2018 rates. Relative rate change is the absolute rate change divided by the 2017 rate, multiplied by 100. Nonoverlapping confidence intervals based on the gamma method were used if the number of deaths was <100 in 2017 or 2018, and z-tests were used if the number of deaths was ≥100 in both 2017 and 2018. ††† Statistically significant (p-value <0.05). Prescription opioid-involved death rates decreased by 13.5% from 2017 to 2018. Rates decreased in males and females, persons aged 15–64 years, non-Hispanic whites, Hispanics, non-Hispanic American Indian/Alaska Natives, and across all urbanization levels. Prescription opioid–involved death rates remained stable in the Northeast and decreased in the Midwest, South, and the West. Seventeen states experienced declines in prescription opioid–involved death rates, with no states experiencing significant increases. The largest relative decrease occurred in Ohio (–40.5%), whereas the largest absolute decrease occurred in West Virginia (–4.1), which also had the highest prescription opioid-involved death rate in 2018 (13.1 per 100,000). Heroin-involved death rates decreased 4.1% from 2017 to 2018; reductions occurred among males and females, persons aged 15–34 years, non-Hispanic whites, and in large central metro and large fringe metro areas (Table 2). Rates decreased in the Midwest and increased in the West. Rates decreased in seven states and DC and increased in three states from 2017 to 2018. The largest relative decrease occurred in Kentucky (50.0%), and the largest absolute decrease occurred in DC (–7.1); the largest relative and absolute increase was in Tennessee (18.8%, 0.9). The highest heroin-involved death rate in 2018 was in Vermont (12.5 per 100,000). TABLE 2 Annual number and age-adjusted rate of drug overdose deaths* involving heroin † and synthetic opioids other than methadone, § , ¶ by sex, age, race/ethnicity,** urbanization level, †† U.S. Census region, §§ and selected states ¶¶ — National Vital Statistics System, United States, 2017 and 2018 Decedent characteristic Heroin Synthetic opioids other than methadone 2017 2018 Rate change from 2017 to 2018*** 2017 2018 Rate change from 2017 to 2018*** No. (rate) No. (rate) Absolute change Relative change No. (rate) No. (rate) Absolute change Relative change All 15,482 (4.9) 14,996 (4.7) −0.2††† −4.1††† 28,466 (9.0) 31,335 (9.9) 0.9††† 10.0††† Sex Male 11,596 (7.3) 11,291 (7.1) −0.2 ††† −2.7 ††† 20,524 (13.0) 22,528 (14.2) 1.2 ††† 9.2 ††† Female 3,886 (2.5) 3,705 (2.3) −0.2 ††† −8.0 ††† 7,942 (5.0) 8,807 (5.5) 0.5 ††† 10.0 ††† Age group (yrs) 0–14 —§§§ —§§§ —§§§ —§§§ 33 (0.1) 29 (0.1) 0.0 0.0 15–24 1,454 (3.4) 1,160 (2.7) −0.7 ††† −20.6 ††† 2,655 (6.1) 2,640 (6.1) 0.0 0.0 25–34 4,890 (10.8) 4,642 (10.2) −0.6 ††† −5.6 ††† 8,825 (19.5) 9,568 (20.9) 1.4 ††† 7.2 ††† 35–44 3,713 (9.1) 3,740 (9.1) 0.0 0.0 7,084 (17.3) 8,070 (19.6) 2.3 ††† 13.3 ††† 45–54 3,043 (7.2) 2,922 (7.0) −0.2 −2.8 5,762 (13.6) 6,132 (14.7) 1.1 ††† 8.1 ††† 55–64 2,005 (4.8) 2,077 (4.9) 0.1 2.1 3,481 (8.3) 4,018 (9.5) 1.2 ††† 14.5 ††† ≥65 368 (0.7) 445 (0.8) 0.1 14.3 620 (1.2) 871 (1.7) 0.5 ††† 41.7 ††† Sex and age group (yrs) Male 15–24 1,031 (4.7) 821 (3.7) −1.0 ††† −21.3 ††† 1,877 (8.5) 1,841 (8.4) −0.1 −1.2 Male 25–44 6,428 (14.8) 6,305 (14.4) −0.4 −2.7 11,693 (27.0) 12,810 (29.2) 2.2 ††† 8.1 ††† Male 45–64 3,830 (9.3) 3,778 (9.2) −0.1 −1.1 6,524 (15.8) 7,195 (17.6) 1.8 ††† 11.4 ††† Female 15–24 423 (2.0) 339 (1.6) −0.4 ††† −20.0 ††† 778 (3.7) 799 (3.8) 0.1 2.7 Female 25–44 2,175 (5.1) 2,077 (4.8) −0.3 −5.9 4,216 (9.8) 4,828 (11.2) 1.4 ††† 14.3 ††† Female 45–64 1,218 (2.8) 1,221 (2.8) 0.0 0.0 2,719 (6.3) 2,955 (6.9) 0.6 ††† 9.5 ††† Race/Ethnicity** White, non-Hispanic 11,293 (6.1) 10,756 (5.8) −0.3 ††† −4.9 ††† 21,956 (11.9) 23,214 (12.6) 0.7 ††† 5.9 ††† Black, non-Hispanic 2,140 (4.9) 2,145 (4.9) 0.0 0.0 3,832 (9.0) 4,780 (11.0) 2.0 ††† 22.2 ††† Hispanic 1,669 (2.9) 1,768 (3.1) 0.2 6.9 2,152 (3.7) 2,766 (4.7) 1.0 ††† 27.0 ††† American Indian/Alaska Native, non-Hispanic 136 (5.2) 133 (5.1) −0.1 −1.9 171 (6.5) 191 (7.3) 0.8 12.3 Asian/Pacific Islander, non-Hispanic 119 (0.5) 85 (0.4) −0.1 −20.0 189 (0.8) 214 (1.0) 0.2 ††† 25.0 ††† County urbanization level†† Large central metro 5,820 (5.6) 5,467 (5.2) −0.4 ††† −7.1 ††† 8,511 (8.2) 9,804 (9.4) 1.2 ††† 14.6 ††† Large fringe metro 4,526 (5.8) 4,321 (5.5) −0.3 ††† −5.2 ††† 8,991 (11.6) 9,871 (12.7) 1.1 ††† 9.5 ††† Medium metro 2,973 (4.6) 3,091 (4.8) 0.2 4.3 6,254 (9.8) 6,750 (10.5) 0.7 ††† 7.1 ††† Small metro 972 (3.6) 949 (3.5) −0.1 −2.8 1,878 (7.0) 2,050 (7.6) 0.6 ††† 8.6 ††† Micropolitan (nonmetro) 801 (3.3) 780 (3.3) 0.0 0.0 1,860 (7.7) 1,925 (8.0) 0.3 3.9 Noncore (nonmetro) 390 (2.4) 388 (2.4) 0.0 0.0 972 (6.0) 935 (5.8) −0.2 −3.3 U.S. Census region of residence§§ Northeast 4,310 (7.8) 4,363 (8.0) 0.2 2.6 8,861 (16.2) 10,351 (19.1) 2.9 ††† 17.9 ††† Midwest 4,228 (6.5) 3,575 (5.5) −1.0 ††† −15.4 ††† 8,234 (12.8) 8,348 (12.9) 0.1 0.8 South 4,776 (4.0) 4,718 (3.9) −0.1 −2.5 9,906 (8.3) 10,443 (8.6) 0.3 ††† 3.6 ††† West 2,168 (2.8) 2,340 (3.0) 0.2 ††† 7.1 ††† 1,465 (1.9) 2,193 (2.8) 0.9 ††† 47.4 ††† States with very good to excellent reporting (n = 29)¶¶ Alaska 36 (4.9) 29 (3.8) −1.1 −22.4 37 (4.9) 18 –§§§ –§§§ –§§§ Arizona 334 (5.0) 352 (5.2) 0.2 4.0 267 (4.0) 522 (7.7) 3.7 ††† 92.5 ††† Connecticut 425 (12.4) 338 (9.9) −2.5 ††† −20.2 ††† 686 (20.3) 767 (22.5) 2.2 10.8 District of Columbia 127 (18) 79 (10.9) −7.1 ††† −39.4 ††† 182 (25.7) 162 (22.6) −3.1 −12.1 Georgia 263 (2.6) 299 (2.9) 0.3 11.5 419 (4.1) 349 (3.4) −0.7 ††† −17.1 ††† Illinois 1,187 (9.2) 1,050 (8.3) −0.9 ††† −9.8 ††† 1,251 (9.8) 1,568 (12.4) 2.6 ††† 26.5 ††† Iowa 61 (2.1) 37 (1.3) −0.8 −38.1 92 (3.2) 80 (2.8) −0.4 −12.5 Maine 76 (6.2) 71 (6.0) −0.2 −3.2 278 (23.5) 229 (19.8) −3.7 −15.7 Maryland 522 (8.6) 356 (5.9) −2.7 ††† −31.4 ††† 1,542 (25.2) 1,825 (29.6) 4.4 ††† 17.5 ††† Massachusetts 466 (7.0) 475 (7.0) 0.0 0.0 1,649 (24.5) 1,806 (26.8) 2.3 ††† 9.4 ††† Missouri 299 (5.3) 351 (6.1) 0.8 15.1 618 (10.9) 868 (15.3) 4.4 ††† 40.4 ††† Nevada 94 (3.1) 108 (3.5) 0.4 12.9 66 (2.2) 85 (2.8) 0.6 27.3 New Hampshire 28 (2.4) 12 –§§§ –§§§ –§§§ 374 (30.4) 386 (31.3) 0.9 3.0 New Mexico 144 (7.4) 130 (6.6) −0.8 −10.8 75 (3.7) 105 (5.4) 1.7 45.9 New York 1,356 (6.8) 1,243 (6.3) −0.5 −7.4 2,238 (11.3) 2,195 (11.2) −0.1 −0.9 North Carolina 537 (5.6) 619 (6.3) 0.7 12.5 1,285 (13.2) 1,272 (13.0) −0.2 −1.5 Ohio 1,000 (9.2) 721 (6.6) −2.6 ††† −28.3 ††† 3,523 (32.4) 2,783 (25.7) −6.7 ††† −20.7 ††† Oklahoma 61 (1.6) 84 (2.2) 0.6 37.5 102 (2.6) 79 (2.0) −0.6 −23.1 Oregon 124 (3.0) 154 (3.7) 0.7 23.3 85 (2.1) 97 (2.4) 0.3 14.3 Rhode Island 14—§§§ 24 (2.2) –§§§ –§§§ 201 (20.1) 213 (21.0) 0.9 4.5 South Carolina 153 (3.2) 183 (3.8) 0.6 18.8 404 (8.5) 510 (10.8) 2.3 ††† 27.1 ††† Tennessee 311 (4.8) 369 (5.7) 0.9 ††† 18.8 ††† 590 (9.3) 827 (12.8) 3.5 ††† 37.6 ††† Utah 147 (4.8) 156 (5.1) 0.3 6.3 92 (3.1) 83 (2.9) −0.2 −6.5 Vermont 41 (7.3) 68 (12.5) 5.2 71.2 77 (13.8) 106 (19.3) 5.5 39.9 Virginia 556 (6.7) 532 (6.4) −0.3 −4.5 829 (10.0) 852 (10.3) 0.3 3.0 Washington 306 (4.0) 328 (4.2) 0.2 5.0 143 (1.9) 221 (2.9) 1.0 ††† 52.6 ††† West Virginia 244 (14.9) 195 (12.3) −2.6 −17.4 618 (37.4) 551 (34.0) −3.4 −9.1 Wisconsin 414 (7.8) 327 (6.0) −1.8 ††† −23.1 ††† 466 (8.6) 506 (9.4) 0.8 9.3 Wyoming —§§§ —§§§ —§§§ —§§§ —§§§ —§§§ —§§§ —§§§ States with good reporting (n = 10)¶¶ California 715 (1.7) 778 (1.9) 0.2 ††† 11.8 ††† 536 (1.3) 865 (2.2) 0.9 ††† 69.2 ††† Colorado 224 (3.9) 233 (3.9) 0.0 0.0 112 (2.0) 134 (2.2) 0.2 10.0 Florida 707 (3.6) 689 (3.5) −0.1 −2.8 2,126 (11.0) 2,091 (10.7) −0.3 −2.7 Hawaii 10 —§§§ —§§§ —§§§ —§§§ —§§§ —§§§ —§§§ —§§§ Indiana 327 (5.3) 311 (5.0) −0.3 −5.7 649 (10.5) 713 (11.5) 1.0 9.5 Kentucky 269 (6.6) 140 (3.3) −3.3 ††† −50.0 ††† 780 (19.1) 744 (17.9) −1.2 −6.3 Michigan 783 (8.2) 633 (6.5) −1.7 ††† −20.7 ††† 1,368 (14.4) 1,531 (16.0) 1.6 ††† 11.1 ††† Minnesota 111 (2.0) 93 (1.7) −0.3 −15.0 184 (3.5) 202 (3.7) 0.2 5.7 Mississippi 34 (1.3) 39 (1.4) 0.1 7.7 81 (2.9) 72 (2.6) −0.3 −10.3 Texas 569 (2.0) 668 (2.3) 0.3 ††† 15.0 ††† 348 (1.2) 358 (1.2) 0.0 0.0 * Deaths were classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug overdose deaths were identified using underlying cause-of-death codes X40–X44, X60–X64, X85, and Y10–Y14. Rates are age-adjusted using the direct method and the 2000 U.S. standard population, except for age-specific crude rates. All rates were per 100,000 population. † Drug overdose deaths, as defined, that have heroin (T40.1) as a contributing cause. § Drug overdose deaths, as defined, that have semisynthetic opioids other than methadone (T40.4) as a contributing cause. ¶ Categories of deaths are not exclusive as deaths might involve more than one drug category. Summing of categories will result in more than the total number of deaths in a year. ** Data on Hispanic origin should be interpreted with caution; studies comparing Hispanic origin on death certificates and on Census surveys have shown inconsistent reporting on Hispanic ethnicity. Potential race misclassification might lead to underestimates for certain categories, primarily American Indian/Alaska Native non-Hispanic and Asian/Pacific Islander non-Hispanic decedents. https://www.cdc.gov/nchs/data/series/sr_02/sr02_172.pdf. †† By the 2013 National Center for Health Statistics Urban-Rural Classification Scheme for Counties. https://www.cdc.gov/nchs/data_access/urban_rural.htm. §§ Northeast: Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont. Midwest: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. South: Alabama, Arkansas, Delaware, District of Columbia, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, and West Virginia. West: Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. ¶¶ Analyses were limited to states meeting the following criteria. States with very good to excellent reporting had ≥90% of drug overdose deaths mention at least one specific drug in 2017, with the change in drug overdose deaths mentioning of at least one specific drug differing by <10 percentage points from 2017 to 2018. States with good reporting had 80% to <90% of drug overdose deaths mention at least one specific drug in 2017, with the change in the percentage of drug overdose deaths mentioning at least one specific drug differing by <10 percentage points from 2017 to 2018. States included also were required to have stable rate estimates (i.e., based on ≥20 deaths in at least two of the following drug categories: opioids, prescription opioids, synthetic opioids other than methadone, and heroin). *** Absolute rate change is the difference between 2017 and 2018 rates. Relative rate change is the absolute rate change divided by the 2017 rate, multiplied by 100. Nonoverlapping confidence intervals based on the gamma method were used if the number of deaths was <100 in 2017 or 2018, and z-tests were used if the number of deaths was ≥100 in both 2017 and 2018. ††† Statistically significant (p-value <0.05). §§§ Cells with nine or fewer deaths are not reported. Rates based on <20 deaths are not considered stable rate estimates and are not reported. Death rates involving synthetic opioids increased from 9.0 per 100,000 population in 2017 to 9.9 in 2018 and accounted for 67.0% of opioid-involved deaths in 2018. These rates increased from 2017 to 2018 among males and females, persons aged ≥25 years, non-Hispanic whites, non-Hispanic blacks, Hispanics, non-Hispanic Asian/Pacific Islanders, and in large central metro, large fringe metro, medium metro, and small metro counties. Synthetic opioid–involved death rates increased in the Northeast, South and West and remained stable in the Midwest. Rates increased in 10 states and decreased in two states. The largest relative increase occurred in Arizona (92.5%), and the largest absolute increase occurred in Maryland and Missouri (4.4 per 100,000 in both states); the largest relative and absolute decrease was in Ohio (–20.7%, –6.7). The highest synthetic opioid–involved death rate in 2018 occurred in West Virginia (34.0 per 100,000). Discussion During 1999–2018, opioids were involved in 446,032 deaths in the United States. §§§ From 2017 to 2018, relative decreases occurred in death rates involving all drug overdoses (–4.1%), all opioids (–2.0%), prescription opioids (–13.5%), and heroin (–4.1%); a relative increase occurred in the rate of overdose deaths involving synthetic opioids (10.0%). Decreases in all opioid-involved death rates were largely driven by those involving prescription opioids. The number of filled opioid prescriptions peaked in 2012 and decreased thereafter ( 4 ). Efforts to reduce high-dose opioid prescribing ¶¶¶ ( 4 ) have increased and have contributed to decreases in prescription opioid–involved deaths. Factors that might be contributing to the decrease in heroin-involved deaths include fewer persons initiating heroin use ( 5 ), shifts from a heroin-based market to a fentanyl-based market ( 6 ), increased treatment provision for persons using heroin, and expansion of naloxone access ( 5 , 7 ). Increases in synthetic opioid–involved deaths are likely driven by proliferation of IMF or fentanyl analogs in the illicit drug supply ( 3 , 5 , 6 ). According to the Drug Enforcement Administration, fentanyl was the most identified synthetic opioid found during drug seizures in the first half of 2017 ( 6 ); in addition, fentanyl reports in all regions increased during 2014–2018.**** This is consistent with current findings indicating recent increases in synthetic opioid–involved death rates in all regions except the Midwest. The findings in this report are subject to at least five limitations. First, postmortem toxicology testing varies by jurisdiction; improvements in testing might account for some reported increases. Second, the percentage of 2017 and 2018 death certificates with at least one drug specified varied among states and over time, limiting opioid subcategory rate comparisons. Third, because heroin is metabolized to morphine ( 8 ), some heroin deaths might have been misclassified as morphine deaths, resulting in an underreporting of heroin deaths. Fourth, potential race misclassification might have led to underestimates for certain categories, particularly American Indian/Alaska Natives and Asian/Pacific Islanders. †††† Finally, adequate drug specificity data were available from only 38 states and DC, which might limit generalizability of state-based analyses. From 2017 to 2018, small decreases occurred in all overdose deaths and in deaths involving all opioids, prescription opioids, and heroin; however, deaths involving synthetic opioids continued to increase in 2018 and accounted for two thirds of opioid-involved deaths. Findings also highlight increases in deaths among non-Hispanic blacks and Hispanics, indicating the need for culturally tailored interventions that address social determinants of health and structural-level factors. In addition, changing substance use patterns, including the resurgence of methamphetamine use, particularly among persons using opioids ( 9 ) and the mixing of opioids with methamphetamine and cocaine in the illicit drug supply ( 6 ), have continued to make the drug overdose landscape more complicated and surveillance and prevention efforts more challenging. To sustain decreases and prevent continued increases, continued urgent action is needed. Overdose Data to Action §§§§ is a 3-year cooperative agreement through which CDC funds health departments in 47 states, DC, two territories, and 16 cities and counties for surveillance and prevention efforts. These measures include obtaining more timely data on all drug overdoses, improving toxicology to better identify polysubstance-involved deaths, enhancing linkage to treatment for persons with opioid use disorder and risk for opioid overdose, improving prescription drug monitoring programs, implementing health systems interventions, partnering with public safety, and implementing other innovative surveillance and prevention activities. Because of the reductions observed in deaths involving prescription opioids, continued efforts to encourage safe prescribing practices, such as following the CDC Guideline for Prescribing Opioids for Chronic Pain ( 10 ) might be enhanced by increased use of nonopioid and nonpharmacologic treatments for pain. Additional public health efforts to reduce opioid-involved overdose deaths include expanding the distribution of naloxone, addressing polysubstance use, and increasing the provision of medication-assisted treatment. Enhanced and coordinated multisectoral surveillance of the illicit drug supply ¶¶¶¶ to track emerging threats, including the type and amount of specific drugs, could also help prevent overdoses. A comprehensive, multisectoral surveillance, prevention, and response approach remains critical for sustaining and expanding preliminary successes in reducing opioid-involved overdose deaths and specifically curtailing synthetic opioid–involved deaths and other emerging threats. Summary What is already known about this topic? In 2017, 68% of the 70,237 U.S. drug overdose deaths involved an opioid. During 2016–2017, deaths involving all opioids and synthetic opioids increased; deaths involving prescription opioids and heroin remained stable. What is added by this report? Opioids were involved in approximately 70% (46,802) of drug overdose deaths during 2018, representing decreases from 2017 in overdose death rates involving all opioids (2% decline), prescription opioids (14%), and heroin (4%); rates involving synthetic opioids increased 10%. What are the implications for public health practice? Surveillance of overdose and polysubstance use trends and the illicit drug supply to track emerging threats, enhancing linkage to treatment, and a multisectoral response are critical to sustaining and accelerating declines in opioid-involved deaths.
Opioid overdose survivors have an increased risk for death. Whether use of medications for opioid use disorder (MOUD) after overdose is associated with mortality is not known.
This paper summarises evidence for medicinal uses of opioids; harms related to the extra-medical use and dependence upon these drugs, and for a wide range of interventions to address the harms related to extra-medical opioid use. Finally, we use mathematical modelling to estimate harms and explore the overall health benefits of opioid agonist treatment (OAT) in a range of settings that vary in levels of opioid use and associated harms (overdose, HIV, HCV, suicide, accidental injuries) and responses. Estimates in 2017 suggest 40.5 million people were dependent upon opioids (40.5 million people, 95%UI 34.3–47.9 million) and 109,500 people died from opioid overdose (10.5,800–113,600). OAT can be highly effective in reducing illicit opioid use and improving multiple health and social outcomes, including reduced overall mortality and key causes of death including overdose, suicide, and other injuries. Modelling suggested scaling-up and retaining people in OAT, including providing OAT in prison, could avert a median of 7.7%, 14.5% and 25.9% deaths over the next 20 years (compared to scenarios without OAT) in Kentucky, Kyiv and Tehran, with more impact achieved in Tehran and Kyiv due to the added benefits on HIV mortality.. Other pharmacological and non-pharmacological treatments have varying levels of evidence for effectiveness and patient acceptability. Other effective interventions are those focused on preventing harms associated with problematic opioid use. Despite strong evidence for the effectiveness of a range of interventions to improve the health and well-being of people who are dependent on opioids, coverage is low even in high income countries. Treatment quality may be less than desirable, and considerable human, social, and economic harms arise from the criminalisation of illicit opioid use and dependence. Alternative policy frameworks are recommended that adopt a human rights and public health-based approach, do not make drug use a criminal behaviour and seek to reduce drug related harm at the population level.
Jacqueline E. Goldman: jacqueline_goldman1@brown.edu
Jesse L. Yedinak: jesse_yedinak@brown.edu
Edward Bernstein: ebernste@bu.edu
Scott E. Hadland: scott.hadland@bmc.org
Jane A. Buxton: jane.buxton@bccdc.ca
Susan G. Sherman: ssherman@jhu.edu
Katie B. Biello: katie_biello@brown.edu
Brandon D. L. Marshall:
ORCID: http://orcid.org/0000-0002-0134-7052
brandon_marshall@brown.edu
Journal
Journal ID (nlm-ta): Trials
Journal ID (iso-abbrev): Trials
Title:
Trials
Publisher:
BioMed Central
(London
)
ISSN
(Electronic):
1745-6215
Publication date
(Electronic):
26
November
2020
Publication date PMC-release: 26
November
2020
Publication date Collection: 2020
Volume: 21
Electronic Location Identifier: 976
Affiliations
[1
]GRID grid.40263.33, ISNI 0000 0004 1936 9094, Department of Epidemiology, , Brown University School of Public Health, ; Providence, Rhode Island USA
[2
]GRID grid.189504.1, ISNI 0000 0004 1936 7558, Department of Medicine, , Boston University School of Medicine, ; Boston, Massachusetts USA
[3
]GRID grid.189504.1, ISNI 0000 0004 1936 7558, School of Public Health, , Boston University, ; Boston, Massachusetts USA
[4
]GRID grid.239424.a, ISNI 0000 0001 2183 6745, Grayken Center for Addiction, , Boston Medical Center, ; Boston, Massachusetts USA
[5
]Department of Pediatrics, Boston Medicine Center, Boston, Massachusetts USA
[6
]GRID grid.189504.1, ISNI 0000 0004 1936 7558, Division of General Pediatrics, Department of Pediatrics, , Boston University School of Medicine, ; Boston, Massachusetts USA
[7
]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, School of Population and Public Health, , University of British Columbia, ; Vancouver, British Columbia Canada
[8
]GRID grid.418246.d, ISNI 0000 0001 0352 641X, British Columbia Centre for Disease Control, ; Vancouver, British Columbia Canada
[9
]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of Health, Behavior, and Society, , Johns Hopkins Bloomberg School of Public Health, ; Baltimore, Maryland USA
[10
]GRID grid.40263.33, ISNI 0000 0004 1936 9094, Department of Behavioral and Social Sciences, , School of Public Health, Brown University, ; Providence, Rhode Island United States
[11
]GRID grid.245849.6, ISNI 0000 0004 0457 1396, Fenway Institute, Fenway Health, ; Boston, Massachusetts USA
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History
Date
received
: 18
August
2020
Date
accepted
: 12
November
2020
Funding
Funded by: FundRef http://dx.doi.org/10.13039/100000026, National Institute on Drug Abuse;
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