1. Juvenile Treatment Drug Court GAIN Data Issues SAMHSA / CSAT Treatment Drug Court Grantee Meeting Melissa Ives Kate Moritz June 10, 2009 Anaheim, CA

2. Outline 1.Overview of current data: March 2009 JDTC/FDC data with YORP and CSAT 2008 2.Using your own GAIN data/Resources: Reminder of available GCC resources for evaluators A.Using the scales and variables files B.Review of current characteristics profile 3.Accessing CSAT GAIN data: Review of process for requesting cross-project data for publications, Available Datasets: A.Full GAIN data-Version 5 records only B.Summary analytic dataset Vertical C.Summary analytic dataset Horizontal

3. Growth in DC data set CSAT 2006 dataset, GAIN-I N = 79 –and 36 follow-ups (3m). CSAT 2007 dataset, GAIN-I N = 534 –and more than 700 follow-ups (3m-12m). CSAT 2008 dataset, GAIN-I N = 1,147 –and more than 1600 follow-ups (3m-12m). As of March 2009, GAIN-I N = 1,845 –and more than 1,600 follow-ups (3m-12m*). –more than doubled in 7 months! It is important to have HIGH follow-up rates –The goal is 80% or higher each wave. *9 and 12-month follow-ups are not required for Drug Court sites

4. Follow-up Rates for 3 and 6 month *(Of those) due for 3m wave **(Of those) due for 6m wave Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset

5. Demographics *Includes 2 Family Drug Court sites Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset JTDC like AT: Gender, Age JTDC like YORP: Minority Status (Hispanic)

6. Years of Use *Includes 2 Family Drug Court sites Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset

7. Index Admission Level of Care *Includes 2 Family Drug Court sites Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset JTDC like AT: Treatment Placement

8. Pattern of Comorbidity *Includes 2 Family Drug Court sites Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset

9. Past Month Abstinence *Includes 2 Family Drug Court sites; +9m & 12m not required Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset JTDC: Same pattern of improved abstinence, lower severity

10. No Past Month Substance Problems *Includes 2 Family Drug Court sites; +9m & 12m not required Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset

11. No Major Health Problems Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset *Includes 2 Family Drug Court sites; +9m & 12m not required

12. No Major Mental Health Problems Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset *Includes 2 Family Drug Court sites; +9m & 12m not required

13. No Illegal Activity Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset *Includes 2 Family Drug Court sites; +9m & 12m not required

14. No Family/Home Problems Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset *Includes 2 Family Drug Court sites; +9m & 12m not required

15. No problem or 50%+ Reduction on… (at last FU) *Includes 2 Family Drug Court sites Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset

16. No problem or 50%+ Reduction on… (at last FU) *Includes 2 Family Drug Court sites Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset

17. ASAM Treatment Planning Clusters *Includes 2 Family Drug Court sites Source: March 2009 YORP/JTDC, CSAT AT 2008 dataset

18. GRRS Treatment Planning Needs: Substance Use and Treatment Source: GI_GM_DrugCourt_033109_Horizontal

19. GRRS Treatment Planning Needs: Mental Health Source: GI_GM_DrugCourt_033109_Horizontal

20. GRRS Treatment Planning Needs: Physical Health Source: GI_GM_DrugCourt_033109_Horizontal

21. GRRS Treatment Planning Needs: Environment and Legal Environment Legal Source: GI_GM_DrugCourt_033109_Horizontal

22. GRRS Treatment Planning Needs: SES/Vocation Source: GI_GM_DrugCourt_033109_Horizontal

23. GRRS Treatment Planning Needs: HIV risk and Child issues Source: GI_GM_DrugCourt_033109_Horizontal

24. Intoxication (at intake) vs. Detox Treatment at 3 months (es=.06) *3+ on ASAM dimension B1 criteria Source: GI_GM_DrugCourt_033109_Horizontal Number in need at intake % with unmet need after 3 months How well sites are matching service based on need

25. Intoxication (at intake) vs. Detox Treatment at 3 months *3+ on ASAM dimension B1 criteria Source: GI_GM_DrugCourt_033109_Horizontal Higher values indicate more triage of services to those in need.

26. Physical Health problem (at intake) vs. Medical Treatment at 3 months *3+ on ASAM dimension B2 criteria Source: GI_GM_DrugCourt_033109_Horizontal

27. Mental Health Problem (at intake) vs. MH Treatment at 3 months *3+ on ASAM dimension B3 criteria Source: GI_GM_DrugCourt_033109_Horizontal

28. Tx Readiness Need (at intake) vs. Low Tx Motivation+ at 3 months *3+ on ASAM dimension B4 criteria Source: GI_GM_DrugCourt_033109_Horizontal

29. Relapse Potential (at intake) vs. Urine/Breathalyzer at 3 months *3+ on ASAM dimension B5 criteria Source: GI_GM_DrugCourt_033109_Horizontal

30. Recovery Environment (at intake) vs. Self Help at 3 months *3+ on ASAM dimension B6 criteria Source: GI_GM_DrugCourt_033109_Horizontal

31. Residential Treatment need (at intake) vs. 7+ Residential days at 3 months Source: GI_GM_DrugCourt_033109_Horizontal

32. Count of Unmet needs* by Program: Based on service area and placement recommendation Source: GI_GM_DrugCourt_033109_Horizontal *High Need (ASAM B1-B6,ResTx) & no treatment for those with 3m data and valid responses for need.

33. Count of Unmet needs* by Gender: Based on service area and placement recommendation Source: GI_GM_DrugCourt_033109_Horizontal *High Need (ASAM B1-B6,ResTx) & no treatment for those with 3m data and valid responses for need. Hidden slide

34. MH issues at intake vs. MH Treatment+ at 3 months Source: GI_GM_DrugCourt_033109_Horizontal Hidden slide

35. MH issues at intake vs. MH Treatment+ at 3 months Source: GI_GM_DrugCourt_033109_Horizontal

36. MH issues (victimization) at intake vs. MH Treatment+ at 3 months Source: GI_GM_DrugCourt_033109_Horizontal

37. HIV Risk at intake vs. HIV Prevention/Education at 3 months Source: GI_GM_DrugCourt_033109_Horizontal Hidden slide

38. HIV Risk at intake vs. HIV Prevention/Education at 3 months Source: GI_GM_DrugCourt_033109_Horizontal

39. Evaluator Or Analyst Adult & Adolescen t Norms FUL/TTL Reports Syntax & template files FTP Common Site LI Analytic Training Series Memos Site Profiles GAIN-I / M90 data Electronic Encyclopedia (GI S&V) Resources and Tools

40. Using Characteristics Profiles Profiles are updated quarterly (in January, April, July, October) for all CJ programs, posted on APSS site and e-mailed to each PI. Profiles include: –Demographics –Substance use data –Comorbidity data –Risk data –Treatment information –Selected outcomes –Individual site graphs –Two site comparison graphs

41. Where can I get more help understanding characteristics profiles? Read documentation and descriptors first on introduction page. For specific questions, email datasubmit@chestnut.org. datasubmit@chestnut.org A teleconference or web conference can be conducted to give targeted training on using characteristics reports, or FUL/TTL reports or anything else your site is having questions on regarding managing or using data.

42. Using Site data Each site may use it’s own local data for analysis. Sites may sign a Data Sharing Agreement with one or more other sites and share data for cross-site analysis. Fully prepared datasets are provided by the GCC Data Team to each site on a quarterly basis –(JTDC data returned in January, April, July and October) The FTP Common Site has SPSS syntax and information to help export and prepare local data. For more help, contact GAINSubmit@chestnut.orgGAINSubmit@chestnut.org

43. Process for accessing GAIN data Submit abstract to gaineval@chestnut.org for feasibility review.gaineval@chestnut.org After feasibility review and edits, abstracts are distributed to all PI’s via listserv. PI’s have 2 weeks to review and respond or participation is assumed. CSAT project officer gives final approval. Once this step is complete, the GCC Evaluation team will create dataset. For analyses on general topics using data from programs that are no longer in the field or if sites are not identified and using the full CSAT AT dataset of 17,000+ cases, PI distribution step is not needed but all other steps are.

44. Creating an abstract A structured abstract (maximum of 3 pages) containing the following information: 1. Title 2. Lead author 3. Other (potential) authors 4. Proposed forum(s) (journal or conference) 5. Target Dates 6. Data sources (what data set, data and/or time periods) 7. Objectives or questions to be addressed 8. Methods/Design/Main analyses 9. Variables to be created 10. Relevance to field

45. Abstract Planning and Evaluation Resources CSAT CJ Publication Policy FTP Common Site – Evaluator Folder ftp://data.chestnut.org ftp://data.chestnut.org Username: Common Password: public GAIN Website: www.chestnut.org\li\gainwww.chestnut.org\li\gain –Accessing GAIN Data – LI Training Series Memo –Data Sharing Agreements –GAIN-I Scales and Variables File Determine purpose, interpretations, availability, syntax –Norms for adolescents and adults APSS website www.chestnut.org/li/APSS/DCwww.chestnut.org/li/APSS/DC –Quarterly Follow-up, Treatment Transition reports –Site Characteristics Profiles tables and charts GAINEval@chestnut.org

46. What happens next…. Feasibility Review is completed. Abstract is updated if needed based on the results of the Feasibility Review. Final Abstract is presented to those from whom permission is sought (current grantees, CSAT). Grantees are provided time on the conference call to ask questions of the author(s). Grantees have 2 weeks after the conference call to decline participation. Data sharing agreement (DSA) is completed (can be done concurrently with above or in advance). A de-identified dataset is provided to the evaluator or analyst. Do the work and include the acknowledgement! Please stay in contact if you have questions and send us a copy of the final presentation or article!

47. GAIN datasets Full GAIN Version 5 dataset –Includes all GAIN records received. –Includes all GAIN variables and calculated items. –Doesn’t include ATM or CYT data –Doesn’t include FUL, TTL, WAI or TxSI data Summary Analytic dataset –Subset to records with planned GAIN Follow-up (not GPRA only), with GAIN-I data (no ‘loose’ M90s), with FUL data (FUPLAN=1), sites with >80% of GAIN data corresponding to FUL and TTL records, clients at or past the 3-month follow-up window. –Subset variables to Identifiers, Demographics, Days/Times variables, Scales, Indices, and calculated variables used in reports and analyses. –Matched with FUL, TTL, WAI/TxSI data (on the intake record.) –Does not include individual symptoms.

48. Horizontal vs. Vertical file WHEN to use –When ATM and CYT data should be used – If comparing to newer studies, be aware of version differences in scales and indices, –When WCG measures are needed (uses FUL and TTL data), or costs are needed. –When TxSI or WAI data are to be used, –When planned follow-up and opportunity for follow-up, accurate data, standard description are desired, –Stacked Vertical File: When NOT looking at individual change Example: running mixed linear models over time and want to have a random intercept –Spread Horizontal File: When individual change needs to be calculated and used

49. Types of Measures Scale: a set of “symptoms” or items that are inter- correlated (e.g., dependence, depression) where we are interested in the pattern (i.e. common variance) Index: a set of items that may not be directly related but add up to predict (e.g., sources of stress, barriers to treatment, expenses) Ratio Estimators: one measure divided by another (e.g., percent of unprotected sex acts) Status measures: a categorical status based on a single question or created across multiple (e.g., vocational status, housing status) Survival: Time to first event (e.g., time to first use)

50. Interpretative Cut-Points Definition of low, moderate and high clinical significance bands to aid interpretation and decision making (scale name + “g” for group) Useful for defining need at both the client and program level Basis: –DSM or other clinical standards where available (e.g., clinical is 3+/7 dependence) –50th & 90th percentile for common issues (e.g., days of alcohol use) –1+ and median of 1+ for zero saturated (more than half) and right skewed variables Reverse-coded if “up” is low clinical significance (e.g. Treatment Motivation)

51. Other Ways to get Help 1.Use our email support lines : for GAIN and QA/certification questions; gainsupport@chestnut.org gainsupport@chestnut.org for software questions: abssupport@chestnut.org; abssupport@chestnut.org for data submission/data questions: datasubmit@chestnut.org, datasubmit@chestnut.org for evaluation/analysis questions: gaineval@chestnut.org. gaineval@chestnut.org 2.Contact GCC DC Project Coordinator Kate Moritz kmoritz@chestnut.org 309-451-7831

52. Full presentation is available on the GAIN website www.chestnut.org\li\gain (under Research Presentations and Posters) or on the APSS\DrugCourt website (under Major Meeting Materials) www.chestnut.org/li/APSS/DC www.chestnut.org\li\gainwww.chestnut.org/li/APSS/DC