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

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


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 Administrations (SAMHSA) Center
    for Substance Abuse Treatment (CSAT), Baltimore,
    MD, August 24-26, 2010.. This presentation
    reports on treatment research funded by the
    SAMHSA 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 consortium or government. Available on line
    at www.chestnut.org/LI/Posters or by contacting
    Joan Unsicker at 448 Wylie Drive, Normal, IL
    61761, phone (309) 451-7801, Fax (309)
    451-7763, e-mail junsicker_at_Chestnut.Org

2
Goals of this Presentation are to
  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

3
Will be using data from the Global Appraisal of
Individual Needs (GAIN) Collaborators
NH
WA
VT
ME
MT
MN
ND
MA
OR
WI
ID
SD
NY
RI
MI
WY
PA
CT
IA
NJ
NV
NE
OH
UT
IL
IN
CA
DE
CO
WV
MO
VA
MD
KS
KY
DC
NC
TN
OK
NM
State or Regional System
GAIN-Short Screener
GAIN-Quick GAIN-Full
AR
No of GAIN Sites
AZ
SC
GA
AL
None (Yet)
MS
1 to 14
TX
LA
15 to 30
AK
31 to 165
FL
HI
More in BZ, CA, CN, JP, MX
VI
PR
3/10
3
4
Some numbers as of June 2010
  • 1,501 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 WCG CSAT NOMS NIATX PFP
Initiation Treatment within 2 weeks of diagnosis X X X X X
Engagement 2 additional sessions within 30 days X X X X X
Continuing Care Any treatment 90-180 days out X X X
Detox Transfer Starting treatment within 2 weeks X X
Residential Step Down Starting OP Tx w/in 2wks X
Evidenced Based Practice From NREP/Other lists X X X X
Within Cost Bands see French et al 2009 X X
  • 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

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
  • Doesnt lead to specific changes or intervention
    with individuals
  • Doesnt address case mix or context issues
  • Doesnt easily lead to specific improvement at
    the program level
  • Doesnt 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 www.tresearch.org/centers/nqf_docs/NQF_Cro
    sswalk.pdf

9
Why we need to be expand beyond specialty care
into health care..
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
Inclusion of the whole behavioral health system
doubles the coverage, but still misses over 90
Source OAS, 2006 2003, 2004, and 2005 NSDUH
10
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 Chan forthcoming
National Co morbidity Study Replication
11
Lifetime 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
12
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
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
Problems could be easily identified Comorbidity
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/
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
http//publications.rda.dshs.wa.gov/1392/
16
Where in the System are the Adults with Mental
Health, Substance Abuse and Co-occurring?
Substance Abuse Treatment is over half of
treatment system for substance disorders, other
mental disorders, 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
http//publications.rda.dshs.wa.gov/1392/
17
Washington State Results with GAIN Short
Screener Adolescent
Problems could be easily identified Comorbidity
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/
18
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/
19
Where in the System are the Adolescents with
Mental Health, Substance Abuse and Co-occurring?
School Assistance Programs (SAP) largest part of
BH/MH system 2nd largest of SA Co-occurring
systems
SAP SA Treatment Over half of 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/
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

More Extensive / Longer/ Expensive
Screener Quick
Comprehensive Special
22
Longer assessments identify more areas to
address in treatment planning
Most substance users have multiple problems
5 min.
20 min
30 min
1-2 hr
Source Reclaiming Futures Portland, OR and
Santa Cruz, CA sites (n192)
22
23
Major Predictors of Bigger Effects Found in
Multiple Meta Analyses
  • A strong intervention protocol based on prior
    evidence
  • Quality assurance to ensure protocol adherence
    and project implementation
  • Proactive case supervision of individual
  • 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
The more features, the lower the recidivism
Average Practice
Source Adapted from Lipsey, 1997, 2005
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

NOTE There is generally little or no
differences in mean effect size between these
brand names
Source Adapted from Lipsey et al 2001, Waldron
et al, 2001, Dennis et al, 2004
26
Implementation is Essential (Reduction in
Recidivism from .50 Control Group Rate)
Thus one should optimally pick the strongest
intervention that one can implement well
Source Adapted from Lipsey, 1997, 2005
27
Percentage Change in Abstinence (6 mo-Intake) by
level of Adolescent Community Reinforcement
Approach (A-CRA) Quality Assurance
Effects associated with intensity of quality
assurance and monitoring (OR13.5)
Source CSAT 2008 SA Dataset subset to 6 Month
Follow up (n1,961)
27
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
  • 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)
  • 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

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
Electronic Health Records can also support more
substantive performance measures
Treatment Received in the first 3 months Mental Health Need at Intake Mental Health Need at Intake
Treatment Received in the first 3 months No/Low Mod/High Total
Any Treatment 6 218 224
No Treatment 205 553 758
Total 211 771 982
218/22497 to targeted
553/77172 unmet need
771/98279 in need
Size of the Problem
Extent to which services are not reaching those
in most need
Extent to which services are currently being
targeted
Source 2008 CSAT AAFT Summary Analytic Dataset
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
EHR can provide practice based evidence Lessons
from a Decade of GAIN data from CSAT Grants
NH
WA
VT
ME
MT
ND
MN
OR
MA
ID
NY
SD
WI
MI
WY
RI
CT
AAFT
IA
PA
NE
OH
ART
NJ
IN
NV
DC
UT
ATDC
CA
IL
DE
WV
VA
CO
MO
BIRT
KS
MD
JTDC
KY
EARMARK
NC
TN
AZ
EAT
OK
NM
SC
FDC
AR
JDC
GA
MS
AL
OJJDP
ORP
TX
LA
RCF
FL
AK
SAC
SCAN
SCY
HI
TCE
PR
YORP
VI
40
41
2009 CSAT Data Set by Age
18 Years or Older (18) 12.7, (n2,793)
Under 15 Years Old (lt15) 16.1, (n3,547)
15-17 Years Old 71.2, (n15,705)

Source CSAT 2009 Summary Analytic Data Set
(n22,045)
41
42
Diagnosis Time Period Matters
Source CSAT 2009 Summary Analytic Data Set
(n21,659)
42
43
Definition of Substance Use Severity Matters
(n11,066)
Source CSAT 2009 Summary Analytic Data Set
(n21,816)
43
44
Multiple Clinical Problems are the NORM!
Source CSAT 2009 Summary Analytic Data Set
(n20,826)
44
45
The Number of Clinical Problems is related to
Level of Care (over lapping but different mix)
Significantly more likely to have 5 problems
(OR5.8)
Source CSAT 2009 Summary Analytic Data Set
(n21,332)
45
46
The Number of Major Clinical Problems is highly
related to Victimization
Significantly more likely to have 5 problems
(OR13.9)
Source CSAT 2009 Summary Analytic Data Set
(n21,784)
46
47
Overcoming Staff Reluctance with General
Victimization Scale
Source CSAT 2009 Summary Analytic Data Set
(n19,318)
47
48
B1. Intoxication/Withdrawal Treatment Plan Needs
Source CSAT 2009 Summary Analytic Data Set
(n17,392)
48
49
B2. Biomedical Treatment Plan Needs
Source CSAT 2009 Summary Analytic Data Set
(n17,392)
49
50
B3. Psychological Treatment Plan Needs
Source CSAT 2009 Summary Analytic Data Set
(n18,733)
50
51
B4.Readiness Treatment Plan Needs
Source CSAT 2009 Summary Analytic Data Set
(n9,169)
51
52
B5. Relapse Potential Treatment Plan Needs
Source CSAT 2009 Summary Analytic Data Set
(n21,239)
52
53
B6. Environment Treatment Plan Needs
Source CSAT 2009 Summary Analytic Data Set
(n14,952)
53
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 http//www.astm.org/Standards/E2
    369.htm

55
Recommendations (Continued)
  1. 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 http//loinc.org/ so that others
    can pull or receive part or all them (e.g.,
    pulling GAIN treatment planning statements into
    WITS treatment planning module)
  2. Code the content of the short and/or long export
    files using Systematized Nomenclature of Medicine
    - Clinical Terms (SNOMED CT http//www.ihtsdo.org/
    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)
  1. 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
  2. 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)
  3. 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
  4. Build on prior work where you can, collaborate to
    share costs and anticipate problems where you
    cannot
  5. Keep fields for other so that you can learn
    from practice what you missed on the first pass

57
Acknowledgments and Contact Information
  • Available at www.chestnut.org/li/posters.
  • 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
    207-98-7047, 277-00-6500, 270-2003-00006 and
    270-2007-00004C 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 TI655374. 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 61761.
    Phone 1-309-451-7801 E-mail mdennis_at_chestnut.org
    . More information on the GAIN is available at
    www.chestnut.org/li/gain or by e-mailing
    gaininfo_at_chestnut.org .

57
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
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
44
60
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
Major Depressive Epi.
Other Specific Phobia
Externalizing Disorder
Any Anxiety Disorder
Any Substance Disorder
Generalized Anxiety Dis.
Adult Separation Anxiety
Posttraumatic Stress Dis.
Source Dennis, Scott, Funk Chan forthcoming
National Co morbidity Study Replication
60
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
25
40
20
19
30
15
13
12
13
10
10
8
8
8
8
7
20
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
Major Depressive Epi.
Other Specific Phobia
Externalizing Disorder
Any Anxiety Disorder
Any Substance Disorder
Generalized Anxiety Dis.
Adult Separation Anxiety
Posttraumatic Stress Dis.
Source Dennis, Scott, Funk Chan forthcoming
National Co morbidity Study Replication
61
NOMS Early Treatment Outcomes
Source CSAT 2009 SA Data Set subset to 1
Follow ups (n11,668)
61
62
NOMS Post Treatment Outcome (6-12 mo)
  • 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

Source CSAT 2009 SA Data Set subset to 1
Follow ups
62
63
But Need to Control for the lack of Problems at
Intake
Variable measures the last 30 days. All others
measure the past 90 days.
Source CSAT 2009 SA Data Set subset to 1 Follow
ups
63
64
Change in Number of Positive NOMS Outcomes (Last
Follow up Intake)
78 Improved in 1 or more areas (29 in 5 or more)
Source CSAT 2009 SA Data Set subset to 1 Follow
ups (n18,770)
64
65
Outcomes May be Hidden by Subgroups Example of
HIV Risk Outcomes
0.40
0.20
0.00
-0.02
-0.03
-0.10
Cohen's Effect Size d
-0.20
-0.40
Unprotected Sex Acts (f.14)
Days of Victimization (f.22)
-0.60
Days of Needle Use (f1.19)
-0.80
A.
B.
C.
D.
Total
Low Risk
Mod. Risk W/O Trauma
Mod. Risk
High Risk
With Trauma
Source Lloyd et al 2007
66
Any Illegal Activity can be better predicted by
using Intake Severity on Crime/Violence and
Substance Problem Scales
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 (N9006)
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