Managing Chronic Addiction and Mental Health Conditions

1. Managing Chronic Addiction and Mental Health Conditions Michael L. Dennis, Ph.D. and Christy K. Scott, Ph.D. Chestnut Health Systems Normal and Chicago, IL Presentation at Addictions Ontario’s 2011 Annual Addictions conference, Toronto, ON, Canada, May 31, 2011. .This presentation was supported by funds from Addiction Ontario and data from NIDA grants no. R01 DA15523, R37-DA11323, R01 DA021174, and CSAT contract no. 270-07-0191. It is available electronically at www.chestnut.org/li/posters . The opinions are those of the authors do not reflect official positions of the government. Please address comments or questions to the author at mdennis@chestnut.org or 309-451-7801. .p

2. The Goals of this Presentation are to: • review epidemiological data to illustrate the high rates of concurrent disorders, the rates of recovery across conditions, and their chronic nature • summarize the results of recent efforts to increase early identification of concurrent disorders in Ontario • examine how the results of recent experiments to improve the ways in which recovery is managed across time and multiple episodes of care

3. Prevalence of Lifetime Disorders and Past Year Remission in the US 100% 90% Lifetime Disorder 80% Past Year Remission 70% 47% 60% 37% 50% 31% 40% 25% 20% 19% 30% 15% 13% 13% 12% 10% 10% 8% 8% 8% 8% 20% 7% 7% 5% 4% 2% 2% 10% 0% ADHD Dysthymia Agoraphobia Any Disorder Drug Disorder Social Phobia Bi-Polar I or II Panic Disorder Alcohol Disorder Conduct Disorder Oppositional Defiant Any Mood Disorder: Intermittent Explosive Internalizing Disorder Other Specific Phobia Major Depressive Epi. Externalizing Disorder Any Anxiety Disorder: Any Substance Disorder Generalized Anxiety Dis. Posttraumatic Stress Dis. Adult Separation Anxiety Source: Dennis, Scott, Funk & Chan forthcoming; National Co morbidity Study Replication

4. Past Year Recovery “Rates” (Remission/Lifetime) by Disorders in the US 89% 89% 100% Past Year Recovery Rate 83% 90% 77% 71% 66% 80% 57% 58% 56% 70% 50% 45% 48% 48% 43% 44% 41% 42% 60% 44% 41% 39% 30% 50% 31% 40% 30% 20% 10% 0% ADHD Dysthymia Agoraphobia Any Disorder Drug Disorder Social Phobia Bi-Polar I or II Panic Disorder Alcohol Disorder Conduct Disorder Oppositional Defiant Any Mood Disorder: Intermittent Explosive Internalizing Disorder Other Specific Phobia Major Depressive Epi. Externalizing Disorder Any Anxiety Disorder: Any Substance Disorder Generalized Anxiety Dis. Posttraumatic Stress Dis. Adult Separation Anxiety Source: Dennis, Scott, Funk & Chanforthcoming; National Co morbidity Study Replication

5. Multimorbidity is Common Pattern of Disorders Number of Disorders Source: Dennis, Scott, Funk & Chanforthcoming; National Co morbidity Study Replication

6. Remission is Related to Number of Disorders and Pattern of Multimorbidity Pattern of Disorders Number of Disorders Source: Dennis, Scott, Funk & Chan forthcoming; National Co morbidity Study Replication

7. Recovery Rate is related to the to Number of Disorders and Pattern of Multimorbidity 100% 90% 68% 80% Past Year 65% 64% 70% Recovery Rate 51% 50% 60% 41% 50% 40% 26% 24% 19% 30% 16% 20% 10% 0% None None 1 Disorder 2 Disorders Substance Only 3 to 16 Disorders Internalizing Only Sub. + Ext. + Int. Externalizing Only Substance+Internalizing Substance+Externalizing Externalizing+Internalizing Pattern of Disorders Number of Disorders Source: Dennis, Scott, Funk & Chan forthcoming; National Co morbidity Study Replication

8. Treatment Participation is related to the to Number of Dis. and Pattern of Multimorbidity Pattern of Disorders Number of Disorders Source: Dennis, Scott, Funk & Chan forthcoming; National Co morbidity Study Replication

9. Few Get Treatment: 1 in 17 adolescents, 1 in 22 young adults, 1 in 12 adults Substance Use Disorders are Common, But U.S. Treatment Participation Rates Are Low Over 88% of adolescent and young adult treatment and over 50% of adult treatment is publicly funded Much of the private funding is limited to 30 days or less and authorized day by day or week by week Source: OAS, 2006 – 2003, 2004, and 2005 NSDUH

10. Cost of Substance Abuse Treatment Episode • $750 per night in Detox • $1,115 per night in hospital • $13,000 per week in intensive • care for premature baby • $27,000 per robbery • $67,000 per assault $70,000/year to keep a child in detention $22,000 / year to incarcerate an adult $30,000/ child-year in foster care Source: French et al., 2008; Chandler et al., 2009; Capriccioso, 2004

11. Investing in Treatment has a Positive Annual Return on Investment (ROI) • Substance abuse treatment has been shown to have a ROI of between $1.28 to $7.26 per dollar invested • Even the long term and more intensive Treatment Drug Courts programs have an average ROI of $2.14 to $2.71 per dollar invested This also means that for every dollar treatment is cut, we lose more money than we saved. Source: Bhati et al., (2008); Ettner et al., (2006)

12. Over 90% of use and problems start between the ages of 12-20 It takes decades before most recover or die Alcohol and Other Drug Abuse, Dependence and Problem Use Peaks at Age 20 100 People with drug dependence die an average of 22.5 years sooner than those without a diagnosis 90 Percentage 80 70 60 Severity Category 50 Other drug or heavy alcohol use in the past year 40 30 Alcohol or Drug Use (AOD) Abuse or Dependence in the past year 20 10 0 65+ 12-13 14-15 16-17 18-20 21-29 30-34 35-49 50-64 Age Source: 2002 NSDUH and Dennis & Scott, 2007, Neumark et al., 2000

13. Substance use severity is related to crime and violence Crime & Violence by Substance Severity Adolescents 12-17 Source: NSDUH 2006

14. ..as well as family, school and mental health problems Family, Vocational & MH by Substance Severity Adolescents 12-17 Source: NSDUH 2006

15. pain Adolescent Brain Development Occurs from the Inside to Out and from Back to Front Photo courtesy of the NIDA Web site. From A Slide Teaching Packet: The Brain and the Actions of Cocaine, Opiates, and Marijuana.

16. Brain Activity on PET Scan After Using Cocaine Rapid rise in brain activity after taking cocaine Actually ends up lower than they started Photo courtesy of Nora Volkow, Ph.D. Mapping cocaine binding sites in human and baboon brain in vivo. Fowler JS, Volkow ND, Wolf AP, Dewey SL, Schlyer DJ, Macgregor RIR, Hitzemann R, Logan J, Bendreim B, Gatley ST. et al. Synapse 1989;4(4):371-377.

17. Prolonged Substance Use Injures The Brain: Healing Takes Time Normal levels of brain activity in PET scans show up in yellow to red Normal Reduced brain activity after regular use can be seen even after 10 days of abstinence 10 days of abstinence After 100 days of abstinence, we can see brain activity “starting” to recover 100 days of abstinence Source: Volkow ND, Hitzemann R, Wang C-I, Fowler IS, Wolf AP, Dewey SL. Long-term frontal brain metabolic changes in cocaine abusers. Synapse 11:184-190, 1992; Volkow ND, Fowler JS, Wang G-J, Hitzemann R, Logan J, Schlyer D, Dewey 5, Wolf AP. Decreased dopamine D2 receptor availability is associated with reduced frontal metabolism in cocaine abusers. Synapse 14:169-177, 1993.

18. The effects on the brain can be long lasting(Serotonin Present in Cerebral Cortex Neurons) Still not back to normal after 7 years Reduced in response to excessive use Image courtesy of Dr. GA Ricaurte, Johns Hopkins University School of Medicine

19. Co-occurring Mental Health Problems are Common, but the Type of Problems also Changes with Age Internalizing Disorders go up with age Externalizing Disorders go down with age (but do NOT go away) Source: Chan, YF; Dennis, M L.; Funk, RR. (2008). Prevalence and comorbidity of major internalizing and externalizing problems among adolescents and adults presenting to substance abuse treatment. Journal of Substance Abuse Treatment, 34(1) 14-24 .

20. Knowing both is a better predictor (high –high group is 5.5 times more likely than low low) Intake Crime/ Violence Severity Predicts Recidivism Intake Substance Problem Severity Predicts Recidivism Intake Crime/Violence and Psychopathology interact to Predict future Illegal Activity While there is risk, most (42-80%) actually do not commit additional crime Source: CSAT 2008 V5 dataset Adolescents aged 12-17 with 3 and/or 6 month follow-up (N=9006)

21. Global Appraisal of Individual Needs (GAIN) Hierarchical Factor Structure of Psychopathology and Psychopathy Source: Dennis, Chan, and Funk (2006) 21

22. GAIN-Short Screener (GSS)

23. Screener items were selected using the Rasch Measurement Model Items around key decision point Source: Riley et al 2007 -1.89 -.8 -.32 +.28 +.71 23

24. GAIN Short Screener (continued) • Efficiency: The 20 item GSS and its four subscales are highly correlated (.84 to .94) with the full scale, have 90% sensitivity and over 90% area under the curve relative to the full GAIN (Dennis et al 2006) • Validation: Confirmatory Factor Analysis (Dennis, Chan & Funk, 2006), Validation to Other Substance Disorder Screeners (McDonnell et al 2009), Validation to Other Psychiatric Screeners and SCID (McDonnell et al 2009; Riley et al 2009; Rush et al 2008), and to All Records for co-occurring (Lucenko et al, 2009, 2010) • Dissemination: Currently in one or more regional systems in 12 states in the US and 4 provinces in Canada; Translated into a dozen languages; tabular and clinical narrative reports 24

25. Findings from Toronto’sGAIN Collaborating Network Project Source: Chaim, G., & Henderson, J. (2009).  Innovations in Collaboration. Findings from the GAIN Collaborating Network Project. A screening initiative examining youth substance use and mental health concerns. Toronto, ON: GAIN Collaborating Network Project.

26. Methods • Context: Attempt to implement recommendations to have no wrong door for behavior services recommended by Health Canada (2002) and the Canadian Mental Health Commission (2006, 2009) • Participants: 422 youth (80% participation) including • 182 from hospital-based treatment (HBT) agencies • 120 from community-based treatment (CBT) agencie • 120 from outreach, housing and support (OHS) agencies • Characteristics • 18 median age, ranging from 11 to 26 • 67% male, 29% female, 2% transsexual/transgender • 51% White, 25% Black, 6% Asian, 5% Aboriginal, 4% Hispanic • 84% Canadian Born, 88% English as first language • Screening with GAIN SS+ other forms, provider survey and focus Groups Source: Chaim, G., & Henderson, J. (2009).  Innovations in Collaboration. Findings from the GAIN Collaborating Network Project. A screening initiative examining youth substance use and mental health concerns. Toronto, ON: GAIN Collaborating Network Project.

27. GAIN Short Screener Profile Source: Chaim, G., & Henderson, J. (2009).  Innovations in Collaboration. Findings from the GAIN Collaborating Network Project. A screening initiative examining youth substance use and mental health concerns. Toronto, ON: GAIN Collaborating Network Project.

28. Type of Concern in the Past year Source: Chaim, G., & Henderson, J. (2009).  Innovations in Collaboration. Findings from the GAIN Collaborating Network Project. A screening initiative examining youth substance use and mental health concerns. Toronto, ON: GAIN Collaborating Network Project.

29. Youth with Concurrent Disorders Source: Chaim, G., & Henderson, J. (2009).  Innovations in Collaboration. Findings from the GAIN Collaborating Network Project. A screening initiative examining youth substance use and mental health concerns. Toronto, ON: GAIN Collaborating Network Project.

30. Provider Feedback Survey (n=44) Source: Chaim, G., & Henderson, J. (2009).  Innovations in Collaboration. Findings from the GAIN Collaborating Network Project. A screening initiative examining youth substance use and mental health concerns. Toronto, ON: GAIN Collaborating Network Project.

31. Provider Feedback Survey Comments Source: Chaim, G., & Henderson, J. (2009).  Innovations in Collaboration. Findings from the GAIN Collaborating Network Project. A screening initiative examining youth substance use and mental health concerns. Toronto, ON: GAIN Collaborating Network Project.

32. Provider Feedback Survey Comments Source: Chaim, G., & Henderson, J. (2009).  Innovations in Collaboration. Findings from the GAIN Collaborating Network Project. A screening initiative examining youth substance use and mental health concerns. Toronto, ON: GAIN Collaborating Network Project.

33. Pathways to Recovery (CSAT # T100664, 270977011; NIDA DA15523) Source: Dennis et al., 2005; Scott et al 2005

34. 9- Year Pathways to Recovery Sample (N=1326) 100% 20% 40% 60% 80% 0% African American Age 30-49 Female Current CJ Involved Past Year Dependence Prior Treatment Residential Treatment Other Mental Disorders Homeless Physical Health Problems Source: Dennis et al., 2005; Scott et al 2005

35. Substance Use Careers Last for Decades 1.0 Median of 27 years from first use to 1+ years abstinence .9 Cumulative Survival .8 .7 Years from first use to 1+ years abstinence .6 .5 .4 .3 .2 .1 0.0 0 5 10 15 20 25 30 Source: Dennis et al., 2005

36. Substance Use Careers are Longer the Younger the Age of First Use Age of 1st Use Groups 1.0 .9 .8 Cumulative Survival .7 Years from first use to 1+ years abstinence .6 .5 under 15* .4 15-20* .3 .2 21+ .1 0.0 * p<.05 (different from 21+) 0 5 10 15 20 25 30 Source: Dennis et al., 2005

37. Substance Use Careers are Shorter the Quicker People Access Treatment Year to 1st Tx Groups 1.0 .9 .8 Cumulative Survival .7 Years from first use to 1+ years abstinence 20+ .6 .5 .4 .3 10-19* .2 .1 0.0 0-9* * p<.05 (different from 20+) 0 5 10 15 20 25 30 Source: Dennis et al., 2005

38. After Initial Treatment… • Relapse is common, particularly for those who: • Are Younger • Have already been to treatment multiple times • Have more mental health issues or pain • It takes an average of 3 to 4 treatment admissions over 9 years before half reach a year of abstinence • Yet over 2/3rds do eventually abstain Source: Dennis et al., 2005, Scott et al 2005

39. The Cyclical Course of Relapse, Incarceration, Treatment and Recovery (Pathway Adults) P not the same in both directions 6% 7% 25% 30% 8% 28% 29% 4% 7% 44% 31% 13% Treatment is the most likely path to recovery Over half change status annually Incarcerated (37% stable) In the In Recovery Community (58% stable) Using (53% stable) In Treatment (21% stable) Source: Scott, Dennis, & Foss (2005)

40. Predictors of Change Also Vary by Direction • Probability of Transitioning from Using to Abstinence • mental distress (0.88) + older at first use (1.12) • ASI legal composite (0.84) + homelessness (1.27) • + # of sober friend (1.23) • + per 8 weeks in treatment (1.14) In the 28% In Recovery Community (58% stable) Using 29% (53% stable) Probability of Sustaining Abstinence - times in treatment (0.83) + Female (1.72) - homelessness (0.61) + ASI legal composite (1.19) - number of arrests (0.89) + # of sober friend (1.22) + per 77 self help sessions (1.82) Source: Scott, Dennis, & Foss (2005)

41. 86% 66% 36% After 4 years of abstinence, about 86% will make it another year The Likelihood of Sustaining Abstinence Another Year Grows Over Time After 1 to 3 years of abstinence, 2/3rds will make it another year 100% . Only a third of people with 1 to 12 months of abstinence will sustain it another year 90% 80% 70% 60% % Sustaining Abstinence Another Year 50% 40% 30% 20% 10% 0% 1 to 12 months 1 to 3 years 4 to 7 years But even after 7 years of abstinence, about 14% relapse each year Duration of Abstinence Source: Dennis, Foss & Scott (2007)

42. What does recovery look like on average? Duration of Abstinence 1-12 Months 1-3 Years 4-7 Years • More clean and sober friends • Less illegal activity and • incarceration • Less homelessness, violence and • victimization • Less use by others at home, work, • and by social peers • Virtual elimination of illegal activity and illegal • income • Better housing and living situations • Increasing employment and income • More social and spiritual support • Better mental health • Housing and living situations continue to improve • Dramatic rise in employment and income • Dramatic drop in people living below the poverty line Source: Dennis, Foss & Scott (2007)

43. The Risk of Death goes down with years of sustained abstinence Death Rate by Years of Abstinence Users/ Early Abstainers 2.87 times more likely to die in the next year It takes 4 or more years of abstinence for risk to get down to community levels 11.9% 7.1% 3.8% Source: Scott, Dennis, Simeone & Funk (2011)

44. 1.82 1.85 1.14 14.4 0.14 1.32 0.81 0.77 0.75 0.68 1.42 1.68 0.74 Relationship of Treatment, Abstinence and Death Age in Decades - Intake Chronic Condition - Intake Illegal Acts for $ -Intake Years to Mortality % Time in PH Hospital - Months 7-96 No of SA Treatment Episodes Months 0-6 Years of Abstinence % Time w Illegal Activity for $ - Months 7-96 No of SA Treatment Episodes - Months 7-96 % of Time in SA Treatment - Months 7-96 Good % of Time Abstinent Months 7-96 Bad Note: Numbers are Odds Ratio per decade, time or per 10% points Source: Scott, Dennis, Laudet, Simeone & Funk (2011)

45. Early Re-Intervention Experiment 1 (ERI-1) (ERI1; DA11323) Source: Dennis et al., 2003; Scott et al 2005

46. Early Re-Intervention Experiment 2 (ERI-2) (ERI1; DA11323) Source: Scott et al 2009, in press

47. Sample Characteristics of ERI-1 & -2 Experiments 100% 20% 40% 60% 80% 0% African American Age 30-49 Female Current CJ Involved Past Year Dependence Prior Treatment Residential Treatment Other Mental Disorders Homeless ERI 1 (n=448) ERI 2 (n=446) Physical Health Problems

48. Less Risk Behaviors, MH and Crime Less Successive Quarters Using Reduce Time to Re-admission Relative to Control, RMC will reduce the time from relapse to readmission The quicker the return to treatment, the less successive quarters using in the community The less quarters using in the community, the less HIV Risk Behaviors, Mental Health and Crime Problems Early Re-Intervention (ERI) Experiment and Hypotheses Monitoring and Early Re-Intervention Source: Dennis et al 2003, 2007; Scott et al 2005, in press

49. Recovery Management Checkups (RMC) • Quarterly Screening to determining “Eligibility” and “Need” • Linkage meeting/motivational interviewing to: • provide personalized feedback to participants about their substance use and related problems, • help the participant recognize the problem and consider returning to treatment, • address existing barriers to treatment, and • schedule an assessment. • Linkage assistance • reminder calls and rescheduling • Transportation and being escorted as needed • Treatment Engagement Specialist

50. 630-403 = -200 days ERI-1 Time to Treatment Re-Entry 100% 90% 80% 70% (n=221) 60% ERI-1 RMC* Percent Readmitted 1+ Times 60% 51% ERI-1 OM (n=224) 50% 40% 30% Revisions to the protocol 20% *Cohen's d=+0.22 10% Wilcoxon-Gehen 0% Statistic (df=1) 630 270 360 450 540 180 90 0 =5.15, p <.05 Days to Re-Admission (from 3 month interview)