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Opportunities to use electronic behavioral health records and national treatment data standards to improve the quality, effectiveness and cost-effectives.

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Presentation on theme: "Opportunities to use electronic behavioral health records and national treatment data standards to improve the quality, effectiveness and cost-effectives."— Presentation transcript:

1 Opportunities to use electronic behavioral health records and national treatment data standards to improve the quality, effectiveness and cost-effectives of care Michael Dennis, Ph.D. Chestnut Health Systems, Normal, IL Presentation at the ninth State Systems Development Program (SSDP IX) conference sponsored by the Substance Abuse and Mental Health Services Administration’s (SAMHSA) Center for Substance Abuse Treatment (CSAT), Baltimore, MD, August 24-26, This presentation reports on treatment & research funded by the SAMHSA contract , 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 consortium or government. Available on line at or by contacting Joan Unsicker at 448 Wylie Drive, Normal, IL 61761, phone: (309) , Fax: (309) ,

2 1.Examine the limits of existing performance measures and shift focus from structure to clinical utility, and quality 2.Demonstrate the need to connect with general health care and value of even short common measures 3.Explore the value to clinical care of electronic behavioral health record (EBHR) systems that incorporate support for clinical decision making 4.Link back to why this makes embracing the more detailed requirements (e.g., CCR, LOINC, SNOMED) desirable for our field and clients Goals of this Presentation are to

3 More in BZ, CA, CN, JP, MX ID IL MO ND VI ME OK PR SD AR KS MS MT NM WV IN AL AK IA MN NJ NV RI SC UT HI LA DE NE TN PA VT VA DC MI CO KY GA OH OR MD AZ TX NY NH WI CA NC CT FL MA WA WY No of GAIN Sites None (Yet) 1 to to to 165 Will be using data from the Global Appraisal of Individual Needs (GAIN) Collaborators State or Regional System GAIN-Short Screener GAIN-Quick GAIN-Full 3/10 3

4 Some numbers as of June ,501 Licensed GAIN administrative units from 49 states (all by ND) and 7 countries 3,270 users in 396 Agencies using GAIN ABS 60,380 intake assessments (largest in field) 22,045 (88% w 1+ follow-up) from 278 CSAT grantees 22 states, 12 Federal, 6 Canadian provinces, 6 other countries, and 3 foundations mandate or strongly encourage its use 4 dozen researchers have published 179 GAIN- related research publications to date 4

5 The GAIN is.. A family of instruments ranging from screening, to quick assessment to a full Biopsychosocial and monitoring tools Designed to integrate clinical and research assessment Designed to support clinical decision making at the individual client level Designed to support evaluation and planning at program level Designed to support secondary analyses and comparisons across individuals and programs The GAIN is NOT an electronic health record (EHR), but a component that can interface with and support EHRs.

6 Some Common Record Based Performance Measures * NQF: National Quality Forum; WCG: Washington Circle Group; CSAT: Center for Substance Abuse Treatment evaluations; NOMS: National Outcome Monitoring System; NIATX: Network for the Improvement of Addiction Treatment; PFP: Pay for Performance evaluations NQFWCGCSATNOMSNIATXPFP Initiation: Treatment within 2 weeks of diagnosis XXXXX Engagement: 2 additional sessions within 30 days XXXXX Continuing Care: Any treatment days out XXX Detox Transfer: Starting treatment within 2 weeks XX Residential Step Down: Starting OP Tx w/in 2wks X Evidenced Based Practice: From NREP/Other listsXXXX Within Cost Bands: see French et al 2009XX

7 Evaluation of Existing Measures Strengths: – Easy to collect/ calculate in electronic health records – Give broad overview of where problems – Useful for program evaluation and pay for performance Weaknesses: – Doesn’t lead to specific changes or intervention with individuals – Doesn’t address case mix or context issues – Doesn’t easily lead to specific improvement at the program level – Doesn’t address relationships with other gaps in the macro system Linkage to other behavioral health record systems is efficient, but limited by the coverage, content and quality of those systems

8 Additional NQF Standards of Care Annual screening for tobacco, alcohol and other drugs using systematic methods Referral for further multidimensional assessment to guide patient-centered treatment planning Brief intervention, referral to treatment and supportive services where needed Pharmacotherapy to help manage withdrawal, tobacco, alcohol and opioid dependence Provision of empirically validated psychosocial interventions Monitoring and the provision of continuing care Source:

9 Why we need to be expand beyond specialty care into health care.. Source: OAS, 2006 – 2003, 2004, and 2005 NSDUH Over 88% of adolescent and young adult treatment and over 50% of adult treatment is publicly funded and expected to increase under health care reform Few Get Treatment: 1 in 17 adolescents, 1 in 22 young adults, 1 in 12 adults Inclusion of the whole behavioral health system doubles the coverage, but still misses over 90%

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

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

12 The problem is the higher the comorbidity, the less likely people are to reach Recovery (no past year symptoms) Source: Dennis, Scott, Funk & Chan forthcoming; National Co morbidity Study Replication Number of Disorders Pattern of Disorders 64% 50% 19% 68% 65% 41% 51% 26% 24% 16% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% None 1 Disorder 2 Disorders 3 to 16 Disorders None Substance Only Externalizing Only Internalizing Only Substance+Externalizing Substance+Internalizing Externalizing+Internalizing Sub. + Ext. + Int. Past Year Recovery Rate

13 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 SBIRT for tobacco, alcohol and increasingly drugs 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 with the 5 minute Global Appraisal of Individual Needs (GAIN) short screener

14 Washington State Results with GAIN Short Screener: Adults 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 Problems could be easily identified & Comorbidity common

15 Washington State Validation of Co-occurring: GAIN Short Screener vs Clinical Records 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 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

16 Where in the System are the Adults with Mental Health, Substance Abuse and Co-occurring? 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 Substance Abuse Treatment is over half of treatment system for substance disorders, other mental disorders, and co-occurring

17 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 Washington State Results with GAIN Short Screener: Adolescent Problems could be easily identified & Comorbidity common

18 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 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

19 Where in the System are the Adolescents with Mental Health, Substance Abuse and Co-occurring? 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 School Assistance Programs (SAP) largest part of BH/MH system; 2 nd largest of SA & Co- occurring systems SAP+ SA Treatment Over half of system

20 Use of a short common screener can Provide immediate clinical feedback that is a good approximation of diagnosis and be used to guide placement and treatment planning Can be used repeatedly to track change Support evaluation and planning at program or state level (e.g., needs, case mix, services needed) Provide practice based evidence to guide future clinical decision Be incorporated into health risk/ wellness assessments and/or school surveys

21 In practice we need a Continuum of Measurement (Common Measures) Screening to Identify Who Needs to be “Assessed” (5-10 min) – Focus on brevity, simplicity for administration & scoring – Needs to be adequate for triage and referral – GAIN Short Screener for SUD, MH & Crime – ASSIST, AUDIT, CAGE, CRAFT, DAST, MAST for SUD – SCL, HSCL, BSI, CANS for Mental Health – LSI, MAYSI, YLS for Crime Quick Assessment for Targeted Referral (20-30 min) – Assessment of who needs a feedback, brief intervention or referral for more specialized assessment or treatment – Needs to be adequate for brief intervention – GAIN Quick – ADI, ASI, SASSI, T-ASI, MINI Comprehensive Biopsychosocial (1-2 hours) – Used to identify common problems and how they are interrelated – Needs to be adequate for diagnosis, treatment planning and placement of common problems – GAIN Initial (Clinical Core and Full) – CASI, A-CASI, MATE Specialized Assessment (additional time per area) – Additional assessment by a specialist (e.g., psychiatrist, MD, nurse, spec ed) may be needed to rule out a diagnosis or develop a treatment plan or individual education plan – CIDI, DISC, KSADS, PDI, SCAN Screener Quick Comprehensive Special More Extensive / Longer/ Expensive

22 Longer assessments identify more areas to address in treatment planning Source: Reclaiming Futures Portland, OR and Santa Cruz, CA sites (n=192) Most substance users have multiple problems 22 5 min. 20 min 30 min 1-2 hr

23 Major Predictors of Bigger Effects Found in Multiple Meta Analyses 1. A strong intervention protocol based on prior evidence 2. Quality assurance to ensure protocol adherence and project implementation 3. Proactive case supervision of individual 4. Triage to focus on the highest severity subgroup

24 Impact of the numbers of these Favorable features on Recidivism in 509 Juvenile Justice Studies in Lipsey Meta Analysis Source: Adapted from Lipsey, 1997, 2005 Average Practice The more features, the lower the recidivism

25 Evidenced Based Treatment (EBT) that Typically do Better than Usual Practice in Reducing Juvenile Recidivism (29% vs. 40%) Aggression Replacement Training Reasoning & Rehabilitation Moral Reconation Therapy Thinking for a Change Interpersonal Social Problem Solving MET/CBT combinations and Other manualized CBT Multisystemic Therapy (MST) Functional Family Therapy (FFT) Multidimensional Family Therapy (MDFT) Adolescent Community Reinforcement Approach (ACRA) Assertive Continuing Care Source: Adapted from Lipsey et al 2001, Waldron et al, 2001, Dennis et al, 2004 NOTE: There is generally little or no differences in mean effect size between these brand names

26 Implementation is Essential ( Reduction in Recidivism from.50 Control Group Rate) The effect of a well implemented weak program is as big as a strong program implemented poorly The best is to have a strong program implemented well Thus one should optimally pick the strongest intervention that one can implement well Source: Adapted from Lipsey, 1997, 2005

27 27 Percentage Change in Abstinence (6 mo-Intake) by level of Adolescent Community Reinforcement Approach (A-CRA) Quality Assurance Source: CSAT 2008 SA Dataset subset to 6 Month Follow up (n=1,961) Effects associated with intensity of quality assurance and monitoring (OR=13.5)

28 So what does it mean to move towards Evidence Based Practice (EBP)? Introducing explicit intervention protocols that are – Targeted at specific problems/subgroups and outcomes – Having explicit quality assurance procedures to cause adherence at the individual level and implementation at the program level Introducing reliable and valid assessment that can be used – At the individual level to immediately guide clinical judgments about diagnosis/severity, placement, treatment planning, and the response to treatment – At the program level to drive program evaluation, needs assessment, performance monitoring and long term program planning Having the ability to evaluate client and program outcomes – For the same person or program over time, – Relative to other people or interventions

29 Key Challenges to Delivery of Quality Care in Behavioral Health Systems 1.High turnover workforce with variable education background related to diagnosis, placement, treatment planning and referral to other services 2.Heterogeneous needs and severity characterized by multiple problems, chronic relapse, and multiple episodes of care over several years 3.Lack of access to or use of data at the program level to guide immediate clinical decisions, billing and program planning 4.Missing, bad or misrepresented data that needs to be minimized and incorporated into interpretations 5.Lack of Infrastructure that is needed to support implementation and fidelity

30 1. High Turnover Workforce with Variable Education Questions spelled out and simple question format Lay wording mapped onto expert standards for given area Built in definitions, transition statements, prompts, and checks for inconsistent and missing information. Standardized approach to asking questions across domains Range checks and skip logic built into electronic applications Formal training and certification protocols on administration, clinical interpretation, data management, coordination, local, regional, and national “trainers” Above focuses on consistency across populations, level of care, staff and time On-going quality assurance and data monitoring for the reoccurrence or problems at the staff (site or item) level Availability of training resources, responses to frequently asked questions, and technical assistance Outcome: Improved Reliability and Efficiency

31 2. Heterogeneous Needs and Severity Multiple domains Focus on most common problems Participant self description of characteristics, problems, needs, personal strengths and resources Behavior problem recency, breadth, and frequency Utilization lifetime, recency and frequency Dimensional measures to measure change with interpretative cut points to facilitate decisions Items and cut points mapped onto DSM for diagnosis, ASAM for placement, and to multiple standards and evidence- based practices for treatment planning Computer generated scoring and reports to guide decisions Treatment planning recommendations and links to evidence-based practice Basic and advanced clinical interpretation training and certification Outcome: Comprehensive Assessment

32 3. Lack of Access to or use of Data at the Program Level Data immediately available to support clinical decision making for a case Data can be transferred to other clinical information system to support billing, progress reports, treatment planning and on-going monitoring Data can be exported and cleaned to support further analyses Data can be pooled with other sites to facilitate comparison and evaluation PC and web based software applications and support Formal training and certification on using data at the individual level and data management at the program level Data routinely pooled to support comparisons across programs and secondary analysis Over three dozen scientists already working with data to link to evidence-based practice Outcome: Improved Program Planning and Outcomes

33 4. Missing, Bad or Misrepresented Data Assurances, time anchoring, definitions, transition, and question order to reduce confusion and increase valid responses Cognitive impairment check Validity checks on missing, bad, inconsistency and unlikely responses Validity checks for atypical and overly random symptom presentations Validity ratings by staff Training on optimizing clinical rapport Training on time anchoring Training answering questions, resolving vague or inconsistent responses, following assessment protocol and accurate documentation. Utilization and documentation of other sources of information Post hoc checks for on-going site, staff or item problems Outcome: Improved Validity

34 5. Lack of Infrastructure Direct Services Training and quality assurance on administration, clinical interpretation, data management, follow-up and project coordination Data management Evaluation and data available for secondary analysis Software support Technical assistance and back up to local trainer/expert Development Clinical Product Development Software Development Collaboration with IT vendors (e.g., WITS) Over 36 internal & external scientists and students Workgroups focused on specific subgroup, problem, or treatment approach Labor supply (e.g., consultant pool, college courses) Outcome: Implementation with Fidelity

35 Whether getting a paper or electronic referral: These issues go across the continuum of measurement and specific measures While there are things that can be done with the measure, getting good data is as much about the human factors on the right The degree to which you are willing to trust the data at the individual or program level depends on how well you believe these issues are addressed Thus rather than just pass on generic/ collapsed information (like current performance measures) it is better to include more information on how things were measured, who measured them and basic information on how to interpret them

36 Source: 2008 CSAT AAFT Summary Analytic Dataset 553/771=72% unmet need 218/224=97% to targeted 771/982=79% in need Electronic Health Records can also support more substantive performance measures Size of the Problem Extent to which services are currently being targeted Extent to which services are not reaching those in most need Treatment Received in the first 3 months Mental Health Need at Intake No/LowMod/HighTotal Any Treatment No Treatment Total

37 Mental Health Problem (at intake) vs. Any MH Treatment by 3 months Source: 2008 CSAT AAFT Summary Analytic Dataset

38 Why Do We Care About Unmet Need? If we subset to those in need, getting mental health services predicts reduced mental health problems Both psychosocial and medication interventions are associated with reduced problems If we subset to those NOT in need, getting mental health services does NOT predict change in mental health problems Conversely, we also care about services being poorly targeted to those in need.

39 Residential Treatment need (at intake) vs. 7+ Residential days at 3 months Opportunity to redirect existing funds through better targeting Source: 2008 CSAT AAFT Summary Analytic Dataset

40 40 EHR can provide practice based evidence: Lessons from a Decade of GAIN data from CSAT Grants AK AL AR AZ CA CO CT DC DE FL GA HI IA ID IL IN KS KY LA MA MD ME MI MN MO MS MT NC ND NE NH NJ NM NV NY OH OK OR PA RI SC SD TN TX UT VA VT WA WI WV WY PR VI AAFT ART ATDC BIRT JTDC EARMARK EAT FDC JDC OJJDP ORP RCF SAC SCAN SCY TCE YORP

41 CSAT Data Set by Age Source: CSAT 2009 Summary Analytic Data Set (n=22,045) 18 Years or Older (18+) 12.7%, (n=2,793) Under 15 Years Old (<15) 16.1%, (n=3,547) Years Old 71.2%, (n=15,705)

42 42 Diagnosis Time Period Matters Source: CSAT 2009 Summary Analytic Data Set (n=21,659)

43 43 Definition of Substance Use Severity Matters Source: CSAT 2009 Summary Analytic Data Set (n=21,816) *(n=11,066)

44 44 Multiple Clinical Problems are the NORM! Source: CSAT 2009 Summary Analytic Data Set (n=20,826)

45 45 The Number of Clinical Problems is related to Level of Care (over lapping but different mix) Source: CSAT 2009 Summary Analytic Data Set (n=21,332) Significantly more likely to have 5+ problems (OR=5.8)

46 46 The Number of Major Clinical Problems is highly related to Victimization Source: CSAT 2009 Summary Analytic Data Set (n=21,784) Significantly more likely to have 5+ problems (OR=13.9) But this is the issue staff least like to ask about!

47 Overcoming Staff Reluctance with General Victimization Scale Source: CSAT 2009 Summary Analytic Data Set (n=19,318) 47

48 48 B1. Intoxication/Withdrawal Treatment Plan Needs Source: CSAT 2009 Summary Analytic Data Set (n=17,392)

49 49 B2. Biomedical Treatment Plan Needs Source: CSAT 2009 Summary Analytic Data Set (n=17,392)

50 50 B3. Psychological Treatment Plan Needs Source: CSAT 2009 Summary Analytic Data Set (n=18,733)

51 51 B4.Readiness Treatment Plan Needs Source: CSAT 2009 Summary Analytic Data Set (n=9,169)

52 52 B5. Relapse Potential Treatment Plan Needs Source: CSAT 2009 Summary Analytic Data Set (n=21,239)

53 53 B6. Environment Treatment Plan Needs Source: CSAT 2009 Summary Analytic Data Set (n=14,952)

54 Recommendations 1. Build on existing performance measures using the current period as a baseline against which to judge progress 2. Identify useful standardized assessment tools and electronic behavioral health record systems already in use and evaluate the extent to which they address the 5 big issues in the field 3. Identify core information currently reported out and create an export file in XML that can be read into any other electronic health record where both are mapped on the Continuity of Care Record (CCR) standard at

55 Recommendations (Continued) 4. Where a more detailed assessment or report is available and used across multiple programs/systems - file the Logical Observation Identifiers Names and Codes (LOINC) of their full export files at so that others can pull or receive part or all them (e.g., pulling GAIN treatment planning statements into WITS treatment planning module)http://loinc.org/ 5. Code the content of the short and/or long export files using Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT ) so that other systems can interpret the content; in so doing, include information on type of assessment or record, who did it, any certification, time period, created scale/variables, cut point, and interpretation,

56 Recommendations (Continued) 6. Review and as necessary work on standardizing cut points for interpreting measures, linkage between assessment and treatment / evidenced based practices, and automate the linkage to increase clinical support 7. Move away from open ended text which is time consuming to create, not readily usable electronically, and has little impact on care (relative to checklists) 8. Allow for multiple diagnoses, treatment plans, etc and keep them filed separately in the data base so that you can track need, unmet need and service targeting 9. Build on prior work where you can, collaborate to share costs and anticipate problems where you cannot 10. Keep fields for “other” so that you can “learn” from practice what you missed on the first pass

57 57 Acknowledgments and Contact Information Available at This presentation was supported by analytic runs provided by Chestnut Health Systems for the Substance Abuse and Mental Health Services Administration's (SAMHSA's) Center for Substance Abuse Treatment (CSAT) under Contracts , , and C using data provided by the following 152 grantees: TI11317 TI11321 TI11323 TI11324 TI11422 TI11423 TI11424 TI11432 TI11433 TI11871 TI11874 TI11888 TI11892 TI11894 TI13190TI13305 TI13308 TI13313 TI13322 TI13323 TI13344 TI13345 TI13354 TI13356 TI13601 TI14090 TI14188 TI14189 TI14196 TI14252 TI14261 TI14267 TI14271 TI14272 TI14283 TI14311 TI14315 TI14376 TI15413 TI15415 TI15421 TI15433 TI15438 TI15446 TI15447 TI15458 TI15461 TI15466 TI15467 TI15469 TI15475 TI15478 TI15479 TI15481 TI15483 TI15485 TI15486 TI15489 TI15511 TI15514 TI15524 TI15524 TI15527 TI15545 TI15562 TI15577 TI15584 TI15586 TI15670 TI15671 TI15672 TI15674 TI15677 TI15678 TI15682 TI15686 TI16386 TI16400 TI16414 TI16904 TI16928 TI16939 TI16961 TI16984 TI16992 TI17046 TI17070 TI17071 TI17334 TI17433 TI17434 TI17446 TI17475 TI17476 TI17484 TI17486 TI17490 TI17517 TI17523 TI17535 TI17547 TI17589 TI17604 TI17605 TI17638 TI17646 TI17648 TI17673 TI17702 TI17719 TI17724 TI17728 TI17742 TI17744 TI17751 TI17755 TI17761 TI17763 TI17765 TI17769 TI17775 TI17779 TI17786 TI17788 TI17812 TI17817 TI17825 TI17830 TI17831 TI17864 TI18406 TI18587 TI18671 TI18723 TI19313 TI19323 TI Any opinions about this data are those of the authors and do not reflect official positions of the government or individual grantees. Comments or questions can be addressed to Michael Dennis, Chestnut Health Systems, 448 Wylie Drive, Normal, IL Phone ; More information on the GAIN is available at or by ing

58 Additional Slides The following slides were not used in the presentation, but included in the event of questions

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

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

61 61 NOMS: Early Treatment Outcomes Source: CSAT 2009 SA Data Set subset to 1+ Follow ups (n=11,668)

62 62 NOMS: Post Treatment Outcome (6-12 mo) Source: CSAT 2009 SA Data Set subset to 1+ Follow ups *This variable measures the last 30 days. All others measure the past 90 days **The blue bar represents an increase of 50% or no problem

63 63 But Need to Control for the lack of Problems at Intake Source: CSAT 2009 SA Data Set subset to 1+ Follow ups * Variable measures the last 30 days. All others measure the past 90 days.

64 64 Change in Number of Positive NOMS Outcomes (Last Follow up – Intake) Source: CSAT 2009 SA Data Set subset to 1+ Follow ups (n=18,770) 78% Improved in 1 or more areas (29% in 5 or more)

65 Outcomes May be Hidden by Subgroups: Example of HIV Risk Outcomes A. Low Risk B. Mod. Risk W/O Trauma C. Mod. Risk With Trauma D. High Risk Total Cohen's Effect Size d Unprotected Sex Acts (f=.14) Days of Victimization (f=.22) Days of Needle Use (f=1.19) Source: Lloyd et al 2007

66 Any Illegal Activity can be better predicted by using Intake Severity on Crime/Violence and Substance Problem Scales Source: CSAT 2008 V5 dataset Adolescents aged with 3 and/or 6 month follow-up (N=9006) Intake Crime/ Violence Severity Predicts Recidivism Intake Substance Problem Severity Predicts Recidivism Knowing both is a better predictor (high –high group is 5.5 times more likely than low low) While there is risk, most (42- 80%) actually do not commit additional crime


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