Creating a Recovery Oriented and Better Adolescent Treatment System in King County

1. Creating a Recovery Oriented and Better Adolescent Treatment System in King County Michael Dennis, Ph.D. Chestnut Health Systems, Normal, IL September 23-24, 2010 Presentation for the King County Substance Abuse and Mental Health Sr. Staff at the Recovery Cafe. This presentation was supported by King County. The author would like to thank Dennis Deck for providing the tables of 2009 SAPISP data. The presentation also reports on treatment & research funded by the Center for Substance Abuse Treatment (CSAT), Substance Abuse and Mental Health Services Administration (SAMHSA) under contract 270-07-0191, as well as several individual CSAT, NIAAA, NIDA and private foundation grants. The opinions are those of the author and do not reflect official positions of the government. Available on line at www.chestnut.org/LI/Posters or by contacting Michael Dennis, Chestnut Health Systems, 448 Wylie Drive, Normal, IL 61761, phone 309-451-7801, fax 309-451-7765, e-Mail: mdennis@Chestnut.Org Questions about the GAIN can also be sent to gaininfo@chestnut.org

2. Parts of this Presentation • Understanding Addiction as a Chronic Condition and its Implications for Public Health and Safety • No Wrong Door: The Move Toward Screening, Brief Intervention, and Referral to (Long-Term) Treatment • Trends in Washington State Publicly Funded Treatment: 1999 to 2009 Target Data • Highlight What It Takes to Move the Field Toward Evidence-Based Practice Related to Assessment, Treatment, Program Evaluation, and Planning • Preliminary Findings from King County: 2004 to 2010 • Common Treatment Planning Needs, Strengths, Social Support and Potential Mentoring of King County Adolescents

3. Part 1 Understanding Addiction as a Chronic Condition and its Implications for Public Health and Safety

4. Severity of Past Year Substance Use/Disorders(2002 U.S. Household Population age 12+= 235,143,246) Dependence 5% Abuse 4% No Alcohol or Regular AOD Drug Use 32% Use 8% Any Infrequent Drug Use 4% Light Alcohol Use Only 47% Source: 2002 NSDUH, Dennis & Scott 2007

5. Over 90% of use and problems start between the ages of 12-20 It takes decades before most recover or die Problems Vary by Age NSDUH Age Groups 100 People with drug dependence die an average of 22.5 years sooner than those without a diagnosis 90 80 70 60 Severity Category 50 No Alcohol or Drug Use Light Alcohol Use Only 40 Any Infrequent Drug Use 30 Regular AOD Use 20 Abuse 10 Dependence 0 65+ 12-13 14-15 16-17 18-20 21-29 30-34 35-49 50-64 Source: 2002 NSDUH and Dennis & Scott 2007

6. Mean (95% CI) $3,058 This includes people who are in recovery, elderly, or do not use because of health problems Higher Costs $1,613 $1,528 $1,309 $1,078 $948 Higher Severity is Associated with Higher Annual Cost to Society Per Person $4,000 Median (50th percentile) $3,500 $3,000 $2,500 $2,000 $1,500 $1,000 $725 $406 $500 $231 $231 $0 $0 $0 No Alcohol or Light Alcohol Regular AOD Any Dependence Abuse Infrequent Drug Use Use Only Drug Use Use Source: 2002 NSDUH

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

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

9. 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.

10. 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.

11. 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

12. 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.

13. People Entering Publicly Funded Treatment Generally Use For Decades It takes 27 years before half reach 1 or more years of abstinence or die 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Percent still using Years from first use to 1+ years of abstinence 0 5 10 15 20 25 30 Source: Dennis et al., 2005

14. The Younger They Start, The Longer They Use 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Percent still using Age of First Use* Years from first use to 1+ years of abstinence under 15 60% longer 15-20 21+ 0 5 10 15 20 25 30 * p<.05 Source: Dennis et al., 2005

15. The Sooner They Get The Treatment, The Quicker They Get To Abstinence 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Years to first Treatment Admission* Percent still using 20 or more years Years from first use to 1+ years of abstinence 57% quicker 10 to 19 years 0 to 9 years 0 5 10 15 20 25 30 • p<.05 Source: Dennis et al., 2005

16. 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 • Treatment predicts who starts abstinence • Self help engagement predicts who stays abstinent Source: Dennis et al., 2005, Scott et al 2005

17. 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)

18. 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)

19. The Risk of Death goes down with years of sustained abstinence Sustained Abstinence Also ReducesThe Risk of Death Users/Early Abstainers more likely to die in the next 12 months It takes 4 or more years of abstinence for risk to get down to community levels Deaths in the next 12 months - (Matched on Gender, Race & Age) Source: Scott, Dennis, Simeone & Funk (forthcoming)

20. 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

21. 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

22. Comorbidity is Common in Household Population (28%/46% Any)= 61% Co-occurring Lifetime Pattern of Disorders Lifetime Number of Disorders (13%/16% SUD)= 81% Co-occurring Source: Dennis, Scott, Funk & Chanforthcoming; National Co morbidity Study Replication

23. 100% 90% 80% 68% 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 The problem is the higher the comorbidity, the less likely people are to reach Recovery (no past year symptoms) Pattern of Disorders Number of Disorders Source: Dennis, Scott, Funk & Chan forthcoming; National Co morbidity Study Replication

24. 4% 4% 16% 17% 27% 18% 21% 9 % 14% 22% 24% 17% Treatment is the most likely path to recovery Adolescents Have Complex Pathways to Recovery What predicts who enters and maintains recovery? Incarcerated (41% stable) In the In Recovery Community (61% stable) Using (60% stable) Avg of 48% change status each quarter In Treatment (45% stable) Source: 2009 CSAT AT data set; unique n = 11,710

25. Risk Factors Older Male Caucasian Substance Problems Substance Frequency Repeated Treatment Mental Health Problems Illegal Activity Employment Protective Factors Younger Female Racial Minority Recent Treatment Number of Drug Screens Attend 12 Step Meetings Positive Social Peers Positive Recovery Environment School Attendance/ Conduct Risk and Protective Factors Associated with Transitioning to/Remaining in Recovery Source: 2009 CSAT Adolescent Treatment Dataset

26. Recovery* by Level of Care 100% Outpatient (+79%, -1%) 90% Residential(+143%, +17%) 80% Post Corr/Res (+220%, +18%) 70% CC better 60% Percent in Past Month Recovery* 50% OP & Resid Similar 40% 30% 20% 10% 0% Pre-Intake Mon 1-3 Mon 4-6 Mon 7-9 Mon 10-12 * Recovery defined as no past month use, abuse, or dependence symptoms while living in the community. Percentages in parentheses are the treatment outcome (intake to 12 month change) and the stability of the outcomes (3months to 12 month change) Source: CSAT Adolescent Treatment Outcome Data Set (n-9,276)

27. Opportunities to Better Support Adolescent Recovery Evidenced Based Recovery Services for Adolescents (1-2 Clinical Trials) • Telephone Counseling (Kaminer et al., 2008) • Assertive Continuing Care (Godley et al., 2007; 2010) • Motivational Incentives (Godley et al., forthcoming) Other Promising Recovery Services • Alcohol/Drug Test Monitoring • CRAFT (Meyers & Smith, 2005) family recovery support groups • Recovery Schools • Adolescent-focused self help groups • Technology-based Recovery Supports (e.g., social networking, self-monitoring, e-therapy)

28. Part 2. No Wrong Door: The Move Toward Screening, Brief Intervention, and Referral to (Long-Term) Treatment

29. Few Get Treatment: 1 in 19 adolescents, 1 in 21 young adults, 1 in 12 adults Substance Use Disorders are Common,But Treatment Participation Rates Are Low:United States (US) 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, 2009 – 2006, 2007, and 2008 NSDUH

30. Substance Use Disorders are Common,But Treatment Participation Rates Are Low:Washington State Similar rates for young adults: 1 in 18 Higher rates for adolescents : 1 in 10 Similar problems rate, and more treatment participation for adults: 1 in 10 Source: OAS, 2009 – 2006, 2007, and 2008 NSDUH

31. Substance Use Disorders are Common,But Treatment Participation Rates Are Low:Seattle & King County, WA High higher problems rate, but better treatment rates for young adults, 1 in 15; Similar for adults: 1 in 9 Similar problem rate but better Treatment Rate: 1 in 6 adolescents Source: OAS, 2009 – 2006, 2007, and 2008 NSDUH

32. Cost of Substance Abuse Treatment Episode SBIRT models popular due to ease of implementation and low cost • $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

33. 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 • Treatment drug courts 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)

34. The Movement to Increase Screening • Screening, Brief Intervention, and Referral to Treatment (SBIRT) has been shown to be effective in identifying people not currently in treatment, initiating treatment/change, and improving outcomes (see http://sbirt.samhsa.gov/ ) • The US Preventive Services Task Force (USPSTF; 2004, 2007), National Quality Forum (NQF, 2007), and Healthy People 2010 have each recommended: • regular screening, brief intervention, and referral to treatment (SBIRT) for tobacco and alcohol abuse in general medical settings for everyone • SBIRT for drug use in high-risk populations (e.g., adolescents, pregnant and postpartum women, people with HIV, and people with co-occurring psychiatric conditions) • CSAT and NIDA are both funding several demonstration and research projects to develop and evaluate models for doing this • Washington State mandated screening in all adolescent and adult substance abuse treatment, mental health, justice, and child welfare programs

35. GAIN Short Screener (GAIN-SS) • Administration Time: A 5-minute screener • Purpose: Used in general populations to • identify or rule out clients who will be identified as having any behavioral health disorders on the 60-120 min versions of the GAIN • triage area of problem • serve as a simple measure of change • ease administration and interpretation by staff with minimal training or direct supervision • Mode: Designed for self- or staff administration, with paper and pen, computer, or on the web • Scales: Four screeners for Internalizing Disorders, Externalizing Disorders, Substance Disorders, and Crime/Violence Disorders, and a Total Disorder Screener

36. GAIN Short Screener (GAIN-SS) (continued) • Response Set: Recency of 20 problems rated past month (3), 2-12 months ago (2), more than a year ago (1), never (0) • Interpretation: Combined by cumulative time period as: • Past-month count (3s) to measure change • Past-year count (2s or 3s) to predict diagnosis • Lifetime count (1s, 2s, or 3s) as a measure of peak severity • Can be classified within time period as low (0), moderate (1-2), or high (3) • Can also be used to classify remission as • Early (lifetime but not past month) • Sustained (lifetime but not past year) • Reports: Narrative, tabular, and graphical reports built into web- based GAIN ABS or ASP application for local hosting Source: Dennis, Chan, and Funk (2006)

37. Adolescent Rates of High (2+) Scores on Mental Health (MH) or Substance Abuse (SA) Screener by Setting in Washington State Problems could be easily identified Comorbidity is common Source: Lucenko et al. (2009). Report to the Legislature: Co-Occurring Disorders Among DSHS Clients. Olympia, WA: Department of Social and Health Services. Retrieved from http://publications.rda.dshs.wa.gov/1392/

38. Adolescent Client Validation of Hi Co-occurring from GAIN Short Screener vs Clinical Records by Setting in Washington State Two page measure closely approximated all found in the clinical record after the next two years Source: Lucenko et al. (2009). Report to the Legislature: Co-Occurring Disorders Among DSHS Clients. Olympia, WA: Department of Social and Health Services. Retrieved from http://publications.rda.dshs.wa.gov/1392/

39. Where in the System Are the Adolescents with Mental Health, Substance Abuse, and Co-occurring? 2/3 of the teens with mental health issues are seen in substance abuse treatment or student assistance programs Student assistance programs represent 1/3 of the behavioral health system Source: Lucenko et al. (2009). Report to the Legislature: Co-Occurring Disorders Among DSHS Clients. Olympia, WA: Department of Social and Health Services. Retrieved from http://publications.rda.dshs.wa.gov/1392/

40. Adult Rates of High (2+) Scores on Mental Health (MH) or Substance Abuse (SA) Screener by Setting in Washington State Lower than expected rates of SA in mental health and children’s admin Source: Lucenko et al. (2009). Report to the Legislature: Co-Occurring Disorders Among DSHS Clients. Olympia, WA: Department of Social and Health Services. Retrieved from http://publications.rda.dshs.wa.gov/1392/

41. Where in the System Are the Adults with Mental Health, Substance Abuse, and Co-occurring? More mental health treated in substance abuse treatment Source: Lucenko et al. (2009). Report to the Legislature: Co-Occurring Disorders Among DSHS Clients. Olympia, WA: Department of Social and Health Services. Retrieved from http://publications.rda.dshs.wa.gov/1392/

42. Higher rate in clinical record in mental health and children’s administration. But that was based on • “any use” vs. “week use + abuse/dependence” • - and 2 years vs. past year Adult Client Validation of Hi Co-occurring from GAIN Short Screener vs Clinical Records by Setting in Washington State Source: Lucenko et al. (2009). Report to the Legislature: Co-Occurring Disorders Among DSHS Clients. Olympia, WA: Department of Social and Health Services. Retrieved from http://publications.rda.dshs.wa.gov/1392/

43. Student Assistance Prevention and Intervention Services Program (SAPISP) • Core funding is funneled from DASA via OSPI and combined with a variety of other local, state, and federal funding sources (e.g., DFSCA, SSHS, SPF-SIG). • 13 grantees (the nine ESDs and four largest school districts) hire specialists to serve about 75% of MS and HS statewide. • Specialists conduct some primary prevention activities and serve about 16,000 students specifically referred for assistance related to mental health, alcohol or drug use, tobacco use, or other behavioral problems. • Screening using the GAIN-SS was first implemented in the 2007-2008 school year. • Reporting is optional for “Quick” referrals that are seen only once or twice. • Data presented here are for the 2008 to 2009 school year.

44. Total Disorder Screener Severity by Level of Care About 30% of OP and SAP are in the high severity range more typical of residential Outpatient and student asst. prog. are similar (median 6.0 vs. 6.4) Residential median (10.5) is higher Well targeted 95% 1+ 85% 3+ Source: SAPISP 2009 data and Dennis et al., 2006 46

45. SAPISP Results: Statewide (n = 10,924) SAP Similar to Residential on Mental Health but like OP on Substance use and crime Source: SAPISP 2009 data 47

46. Track gap between prior and current lifetime problems to identify underreporting Track progress in reducing current (past month) symptoms) GAIN-SS Can Also Be Used for Monitoring 20 12+ Mon.s ago (#1s) 2-12 Mon.s ago (#2s) 16 Past Month (#3s) Lifetime (#1,2,or 3) 11 12 10 10 9 9 8 8 3 4 2 2 0 Intake 3 6 9 12 15 18 21 24 Mon Mon Mon Mon Mon Mon Mon Mon Total Disorder Screener (TDScr) Monitor for relapse

47. Translations • Chestnut has led the translations of the GAIN SS, Quick and Full from into English and Spanish versions and maded available in hard and electronic versions. • Chestnut is currently collaborating with other researchers translating all measures into French in Quebec and Portuguese in Brazil • King County collaborators have also translated hard copies of the GAIN SS into 19 languages (Arabic, Cambodian, Farsi, French, Hindi, Indonesian, Korean, Laotian, Mandarin (simple and traditional), Marathi, Mongolian , Portuguese, Punjabi, Russian, Somali, Spanish, Tagalog, Vietnamese) • Others have translated the GAIN SS into American Sign Language (ASL), Hindi, Portuguese, Punjabi, Vietnamese CHS TRANSLATION CONTACT: Janet Titus <jtitus@chestnut.org>

48. The GAIN Short Screener can readily identify youth in need of behavioral health treatment and distinguish the type of need While the Student Assistance Program (SAP) system was originally set up largely targeted at substance use, mental health problems are more common and it plays it is a large and important part of the behavioral health system The GAIN SS has the potential to help with identification, referral, and monitoring of cases The availability of multiple translations and paired down software for referral sources and self administration should open additional doors. Implications 50

49. Comparison of Against Medical Advice (AMA) / At Staff Request (ASR) Adol. Discharge Rates Worse than Average AMA/ASR Discharge Rates in Residential & IOP Little Better than Average AMA/ASR Discharge Rates in OP *Seattle, Tacoma-Bellevue Metro Source: OAS 2007 TEDS-D, 2007

50. Comparison of Adolescent Transfer Rates Better than Average Transfer Rates in Residential, IOP & OP *Seattle, Tacoma-Bellevue Metro Source: OAS 2007 TEDS-D, 2007