Combating Opioid-related Overdose Kelly Dunn, Ph.D. Assistant Professor Behavioral Pharmacology Research Unit Department of Psychiatry and Behavioral Sciences Johns Hopkins University School of Medicine
Presentation Outline Learn about the epidemiology of opioid overdose Understand what tools are available to help combat the opioid overdose epidemic 2
Treatment of Pain in the U.S. is a Billion Dollar Industry IMS Health, National Prescription Audit, Dec 2013
Narcotics are Among the Top 5 Prescribed Medications (2013) IMS Health, National Prescription Audit, Dec 2013 4
Overdose is Increasing Throughout the US MMWR, 2011. Vol. 60 (43) 5
Overdose is Increasing Throughout the US Between 2000-2014, rate of drug OD increased by 137% In 2014, 47,055 people died from drug OD, 61% involved opioids Drug poisoning is the leading cause of accidental death among adults aged 25-64. MMWR, 2011. Vol. 60 (43); MMWR, 2016. Vol. 64 (50), 1378-82 6
Fentanyl Exposure is Also Increasing DEA-DCT-DIB-021-16 DEA Intelligence Brief 7
Fentanyl Exposure is Also Increasing Beginning in 2013, the prevalence of fentanyl-adulterated heroin rose to unprecedented levels The rate of overdose related to fentanyl has increased 79% between 2013 and 2015 MMWR, 2016 8
Overdose is Increasing Throughout the US Opioid OD has increased in all segments of society: Drug users Chronic pain patients Elderly Children Women Adolescents Homeless Individuals Significant risk factors for OD Detoxification Leaving jail or prison Induction onto methadone treatment When used together with alcohol or benzodiazepines Baggett et al., 2013; Bailey et al., 2009; Bohnert et al., 2011; Cobaugh et al., 2006; Coben et al., 2010; Dunn et al., 2010; Palmiere et al., 2010; Paulozzi et al., 2006; Rosca et al., 2012
Presentation Outline Learn about the epidemiology of opioid overdose Understand what tools are available to help combat the opioid overdose epidemic 10
Naloxone The majority of published opioid OD interventions focus on naloxone (Narcan) Historically available via injection
Naloxone Auto-injector: Evzio (Kaleo Inc.) Approved by FDA on 4/3/2014
Approved by FDA on 11/18/2015 Narcan
IN vs. IV naloxone Time to Spontaneous Respiration (min) Time to Glascow Coma Score Kelly et al., 2005; Medical Journal of Australia
TM Exonal
Dunn et al., unpublished Naloxone Formulations
Dunn et al., unpublished Naloxone Formulations
Wheeler et al., 2015, MMWR Bystander Interventions
Efforts to Develop a Brief Screen The majority of opioid OD interventions focus on naloxone (Narcan) Non-naloxone approaches important because: Naloxone is not available everywhere Naloxone requires training to administer Price of naloxone has increased substantially Naloxone has many legal barriers Naloxone reverses OD but is not necessarily preventative Naloxone may not reverse OD that occurs with concurrent alcohol/benzodiazepine use
Brief Opioid Overdose Knowledge (BOOK) Questionnaire Identified 59 OD risk behaviors from literature, developed self-report measure Data collected in 3 phases Phase 1: Opioid users (N=147) recruited from detoxification settings Phase 2: Opioid users (N=199) recruited from MAT, detoxification, & needle exchange in VT and MD Phase 3: Patients currently prescribed opioids for the treatment of chronic pain (N=502), recruited via Amazon Mechanical Turk crowdsourcing Dunn et al., 2016, Journal of Addiction Medicine
Brief Opioid Overdose Knowledge (BOOK) Questionnaire Illicit Users Illicit Users Chronic Pain (Sample 1) (Sample 2) (Sample 3) (N=147) (N=199) (N=502) p-value a Aged over 30 (%) 36.9 23.2 32.5 0.02 Male (%) 67.1 46.5 44.9 <.001 Caucasian (%) 61.6 58.7 80.3 <.001 Never Married (%) 72.6 64.8 38.8 <.001 Employed (%) 36.1 27.1 85.5 <.001 Overdosed on opioids (%) 38.3 33.7 19.3 <.001 Witnessed an overdose (%) 70.9 64.0 38.0 <.001 Trained to administer naloxone (%) 7.2 33.9 7.2 <.001 a Values based on chi-square comparisons Symbols designate significant between-group differences. Shared symbols represent no siginificant difference between groups at p<.05 Dunn et al., 2016, Journal of Addiction Medicine 21
Brief Opioid Overdose Knowledge (BOOK) Questionnaire 12 True/False/I don t know items General knowledge (4 items) e.g. long vs short acting drugs, withdrawal signs Overdose risk knowledge (4 items) e.g. OD signs and symptoms; drug combos Overdose response knowledge (4 items) E.g. rescue breathing; Narcan Dunn et al., 2016, Journal of Addiction Medicine 22
Brief Opioid Overdose Knowledge (BOOK) Mean Correct Responses (range 0-4) 4 3 2 1 0 Performance on BOOK Subscales p<.001 Dunn et al., 2016, Journal of Addiction Medicine Questionnaire Illicit Users (Samples 1 & 2) Chronic Pain Patients (Sample 3) ns General Opioid Opioid OD Risk Knowledge Subscale p<.001 Opioid OD Response
OD in Chronic Pain Patients Surveyed 501 individuals who reported pain in past 3 months and treatment with opioid OD Experience 19.3% had experienced an OD 37.8% had witnessed an OD Only 3% had been trained to administer naloxone Past 30 day behaviors: 53.8% had used opioids alone 37.5% had combined opioids with alcohol Predominate RXOP users Dunn et al., 2016, Pain Medicine 24
OD in Chronic Pain Patients Evaluated numerous predictors of OD. Only 2 items emerged: SOAPP-R, DSM Checklist ROC analyses revealed that established cutoffs on two measures predicted history of OD: Screener and Opioid Assessment for Patients with Pain (SOAPP-R) >7 Mild Opioid Use Disorder (>2 items) Dunn et al., 2016, Pain Medicine
OD in Rural vs. Urban Settings Surveyed 345 individuals with opioid use disorder in rural (n=98) and urban (n=247) settings OD Experience 35.6% had experienced an OD 67.5% had witnessed an OD Only 16.9% had been trained to administer naloxone Past 30 day behaviors: 55.1% had used opioids alone 45.6% had combined opioids with alcohol Predominate heroin users 26 Dunn et al., in press, Pain Medicine
OD in Rural vs. Urban Settings Table 2. Overdose History and Risk Factors Entire Sample Participants with History of Overdose Total Rural Urban p-value Total OD Rural OD Urban OD p-value (N=345) (N=98) (N=247) (N=123) (N=45) (N=78) Overdose (OD) History Lifetime Overdose (%) 35.6 45.9 31.6 <.01 100 100 100 N/A Number ODs (mean times, SD) a 1.3 (2.2) 1.5 (2.5) 1.0 (2.0) 0.04 3.2 (2.6) 3.3 (2.8) 3.1 (2.4) 0.66 OD past 30 days (%) 15.4 10.1 18.2 0.28 15.6 10.1 18.5 0.23 OD past year (%) 46.1 47.4 45.5 0.51 46.1 45.9 46.2 0.57 Gone to Emergency Department for OD (%) 26.1 31.9 23.9 0.08 45.1 34.1 51.3 0.05 Witnessed OD (%) 67.5 74.4 64.9 0.07 73.0 69.2 75.0 0.33 Naloxone History Received naloxone prescription (%) 16.9 34.4 9.6 <.001 20.5 39.5 9.5 <.001 Trained to administer naloxone (%) 22.6 46.9 12.6 <.001 22.9 48.8 8.0 <.001 Trained to administer CPR (%) 49.2 59.4 45.0 0.01 46.6 62.7 37.3 <.01 Past 30 Day Risk Behaviors (%) Used opioids by themselves 55.1 41.9 60.3 0.001 60.1 37.8 74.4 <.001 Number days past 30 (mean days, SD) a 2.0 (2.3) 1.2 (1.9) 2.7 (2.6) <.001 2.1 (2.0) 1.0 (1.6) 3.2 (2.5) <.001 Combining opioids with alcohol 45.6 32.6 50.1 <.01 61.2 38.9 64.1 <.001 Number days past 30 (mean days, SD) a 1.5 (2.0) 0.7 (1.5) 2.2 (2.6) <.001 1.5 (1.9) 0.5 (1.2) 2.5 (2.5) <.001 Using methadone 17.1 6.1 21.5 <.001 16.3 4.4 23.1 <.01 Number days past 30 (mean days, SD) a 0.3 (.93) 0.1 (.53) 0.5 (1.4) <.01 0.3 (.85) 0.1 (.47) 0.5 (1.2) 0.06 Undergoing detoxification from opioids 48.5 10.2 64.3 <.001 49.6 6.7 75.0 <.001 Number days past 30 (mean days, SD) a 0.5 (.99) 0.2 (.71) 0.9 (1.27) <.001 0.5 (.76) 0.1 (.25) 0.9 (1.3) <.001 Been in jail or prison 7.2 7.1 7.3 0.58 6.5 8.9 5.1 0.32 Number days past 30 (mean days, SD) a 0.2 (.07) 0.1 (.45) 0.2 (.91) 0.29 0.1 (.39) 0.2 (.56) 0.1 (.22) 0.15 P-values based on Chi-squares for dichotomous variables and independent groups t-tests for continuous variables. OD=overdose; SD=standard deviation a Represents mean reported by participants who endorsed the event b Defined as stimulants and/or benzodiazepines Dunn et al., 2016, 27 JSAT
OD in Rural vs. Urban 1 Settings Mean (SEM) C Only predictor of OD was performance on the BOOK Opioid and Knowledge Domain Opioid OD Knowledge subscales 0 General Opioid Opioid OD Risk Opioid OD Response Mean (SEM) Correct Responses 3 2 1 All 2D Participants Graph 2 4 Rural (N=98) Urban (N=247) Mean (SEM) Correct Responses 4 3 2 1 2D Graph 2 Participants with a History of OD * * Rural (N=45) Urban (N=78) * 0 General Opioid Opioid OD Risk Opioid OD Response Knowledge Domain 0 General Opioid Opioid OD Risk Opioid OD Response Knowledge Domain 2D Graph 2 Dunn et al., 2016, 28 JSAT
Opioid OD Knowledge Intervention Educational interventions Strengths: Show immediate and sustained gains in knowledge Limitations: Not yet evaluated in RCT Generally targeted towards drug users Often administered by trained professional in individualized or group settings Majority of published interventions focus primarily on naloxone administration Green et al., 2008; Piper et al., 2007; Strang et al., 2008; Tobin et al., 2009; Wagner et al., 2010
Opioid OD Knowledge Intervention RCT of an educational intervention Randomized to 1 of 3 groups: Pamphlets Computer intervention Computer intervention with questions Complete pre and post knowledge test; Single administration of intervention Complete 1 and 3 month follow-ups to assess extended knowledge
Opioid OD Knowledge Intervention
Opioid OD Knowledge Intervention
Opioid OD Knowledge Intervention
Opioid OD Knowledge Intervention Opioid users (N=76) recruited from 3-5 day outpatient buprenorphine detoxification program OD Experience 36.0% had experienced an OD 53.6% had witnessed an OD Only 10.6% had been trained to administer naloxone Past 30 day behaviors: 56.0% had used opioids alone 91.2% had combined opioids with alcohol Predominate heroin users 34 Dunn et al., under review
Opioid OD Knowledge Intervention 100 Opioid Knowledge Opioid OD Knowledge Opioid OD Response Knowledge 80 Mean Percent 60 40 20 0 Pre Pamphlet Computer Computer + Mastery Timepoint Post Pre Timepoint Post Pre Timepoint Post Dunn et al., under review
Opioid OD Knowledge Intervention The majority (87%) of participants had relapsed to opioids 9.4% had witnessed an OD by the 30-day follow-up Significant reductions in number of days used opioids alone in past 30, and combining opioids and alcohol 36 Dunn et al., under review
Opioid OD Knowledge Intervention 100 Opioid Knowledge Opioid OD Knowledge Opioid OD Response Knowledge Mean Percent Correct 80 60 40 20 0 Pamphlet Computer Computer + Mastery Pre. Post 1 m 3 m Timepoint Pre. Post 1 m 3 m Timepoint Pre. Post 1 m 3 m Timepoint Dunn et al., under review
Opioid OD Knowledge Intervention The Educational Intervention: a Pamphlet Computer Computer + Mastery (N=25) (N=24) (N=27) Was helpful 1.6 (0.9) 1.4 (0.9) 1.6 (0.9) 0.73 Taught me information I did not know before 1.6 (0.7) 1.5 (0.9) 1.5 (0.9) 0.21 Was easy to understand 1.9 (0.9) 1.3 (0.5) 1.5 (0.5) 0.03 Was fun 2.6 (1.2) 2.3 (0.9) 2.2 (1.1) 0.42 Took too long 2.7 (1.3) 3.3 (1.0) 3.2 (1.4) 0.14 Was Interesting 2.2 (1.2) 1.8 (1.0) 1.7 (0.7) 0.33 I would recommend this educational intervention to someone else a 2.2 (1.1) 1.5 (1.0) 1.7 (0.9) 0.20 I believe that more people should receive this educational intervention a 1.8 (1.2) 1.4 (1.0) 1.6 (1.0) 0.43 I DO NOT think that the educational intervention was useful a 4.0 (1.3) 4.2 (1.0) 4.3 (0.9) 0.47 The educational intervention was confusing a 3.7 (1.3) 4.2 (1.0) 3.9 (1.1) 0.05 How important is it to learn to prevent, recognize, and respond to an overdose b 2.0 (0) 2.0 (0) 2.0 (0.2) 0.39 This intervention will help me from overdosing in the future (%) 96.0 100.0 100.0 0.02 Feel this intervention will change the way you help people who are overdosing (%) 96.0 95.8 100 0.58 Would recommend this intervention to a family member or friend (%) 100 100 100 a Rated on 5-point Likert Scale: 1=Strongly Agree, 2=Agree, 3=Neither Agree not Disagree, 4=Disagree, 5=Strongly Disagree b Rated on 3-point Likert Scale: 0=Not at all Important, 1=Somewhat Important, 2=Very Important p-value Dunn et al., under review
Conclusions Opioid OD is a serious public health problem Brief Opioid Overdose Knowledge (BOOK) may have value as an outcome measure and clinically to inform conversations with patients Risk behaviors and low knowledge are prevalent across multiple different populations Computer-based intervention produces sustained gains in knowledge
Acknowledgements Many thanks to the Johns Hopkins Chemical Dependency Unit, Kathy Petrush, Suzan Berman, Anne Kelly, Carl Broker, and Eric Cunningham NIDA: R21 DA035327; R01DA035246 Thank you! Contact me at: Kelly Dunn, Ph.D. kdunn9@jhmi.edu P: 410-550-2254 40
Dunn et al., under review 41