opportunities to use electronic behavioral health records and national treatment data standards to...

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, 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: [email protected]

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

More in BZ, CA, CN, JP, MX

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No of GAIN Sites

None (Yet)

1 to 14

15 to 30

31 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

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

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.

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

NQ

F

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G

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NO

MS

NIA

TX P

FP

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

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

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 careSource: www.tresearch.org/centers/nqf_docs/NQF_Crosswalk.pdf

8.9%

21.2%

7.3%

0.6%1.0%0.5%0%

5%

10%

15%

20%

25%

12 to 17 18 to 25 26 or older

Abuse or Dependence in past yearTreatment in past year

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%

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

None54%

1 Disorder18%

2 Disorders10%

3 to 16 Disorders

18%

Substance Only3%

None48%

Sub.+Int4%

Ext.+Int.10%

Sub. + Ext. + Int. 8%

Sub.+Ext1%

Internalizing Only21%

Externalizing Only5%

(28%/46% Any)=61% Co-occurring

(13%/16% SUD)=81% Co-occurring

Lifetime Treatment Participation is related to the to Number of Dis. and Pattern of Multimorbidity


Number of Disorders Pattern of Disorders

5%

39%

54%

75%

4%

29%

19%

50%

49%

64%

60%

79%

0%10%20%30%40%50%60%70%80%90%

100%

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+ I

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Any Behavioral Health TxAny Mental Health TxAny Substance Disorder Tx

The problem is the higher the comorbidity, the less likely people are to reach Recovery (no past year symptoms)


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%

Non

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1 D

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2 D

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3 to

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Past YearRecovery Rate

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

http://sbirt.samhsa.gov/

Washington State Results with GAIN Short Screener: Adults

81%

78%

65%

64% 69

%

18%

68% 73

%

43%

44%

69%

17%

69%

51%

53%

51%

17%

4%

56%

46%

31%

31%

17%

3%

0%10%20%30%40%50%60%70%80%90%

100%

SubstanceAbuse

Treatment(n=75,208)

Eastern StateHospital(n=422)

Corrections:Community(n=2,723)

Corrections:Prison

(n=7,881)

Mental HealthTreatment(55,847)

ChildrensAdministration

(n=1,238)

Either High on Mental Health High on Substance High on Both

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/

Problems could be easily identified & Comorbidity common

http://publications.rda.dshs.wa.gov/1392/

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

17%

3%

59%

39%

22%

56%

0%

10%20%

30%40%

50%

60%70%

80%90%

100%

Substance Abuse Treatment(n=75,208)

Mental Health Treatment(55,847)

Childrens Administration(n=1,238)

GAIN Short Screener Clinical Indicators


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


0 20,0

00

40,0

00

60,0

00

80,0

00

100,

000

120,

000

Any Behavioral Health (n=106,818)

Mental Health (n=94,832)

Substance Abuse (n=67,115)

Co-Occurring (n=55,128)

Substance Abuse Treatment Eastern State HospitalCorrections: Community Corrections: PrisonMental Health Treatment Childrens Administration

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


77% 86

%

73%

75%

61%67

%

83%

62%

75%

60%

57%

40% 46

%

12%

12%

47%

37%

35%

12%

11%

0%10%20%30%40%50%60%70%80%90%

100%

Substance AbuseTreatment(n=8,213)

Student AssistancePrograms(n=8,777)

Juvenile Justice(n=2,024)

Mental HealthTreatment (10,937)

Children'sAdministration

(n=239)

Either High on Mental Health High on Substance High on Both


Washington State Results with GAIN Short Screener: Adolescent

Problems could be easily identified & Comorbidity common


35%

12%

11%

56%

34%

15%

9%

47%

0%10%20%30%40%50%60%70%80%90%

100%

Substance AbuseTreatment (n=8,213)

Juvenile Justice(n=2,024)

Mental HealthTreatment (10,937)

Children'sAdministration

(n=239)

GAIN Short Screener Clinical Indicators


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


0 5,000 10,000 15,000 20,000 25,000

Any BehavioralHealth (n=22,879)

Mental Health(21,568)

Substance AbuseNeed (10,464)

Co-occurring(9,155)

Substance Abuse Treatment Student Assistance ProgramJuvenile Justice Mental Health TreatmentChildren's Administration

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 systemsSAP+ SA Treatment

Over half of system


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

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 C

omprehensive S

pecial

More E

xtensive / Longer/ E

xpensive

Longer assessments identify more areas to address in treatment planning

40%

69%

94%98%

22%

13%

3% 0%

22%

8%

1% 0%

9%8%

1% 1%3% 1% 1%7%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

GAIN SS GAIN Q(v2)

GAIN Q(v3 -Beta)

GAIN I

0 Reported

1 Prob.

2 Probs.

3 Probs.

4 Probs.

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

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

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

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

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 wellSource: Adapted from Lipsey, 1997, 2005

27

Percentage Change in Abstinence (6 mo-Intake) by level of Adolescent Community Reinforcement Approach (A-CRA) Quality Assurance

4%

24%36%

0%10%20%30%40%50%60%70%80%90%

100%

Training Only Training,Coaching,

Monitoring

Clinical TrialOnsite Protocol

Monitors

% P

oint

Cha

nge

in A

bsti

nenc

e

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)

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

Key Challenges to Delivery of Quality Care in Behavioral Health Systems1. 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

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

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

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

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

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

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

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/Low Mod/High Total

Any Treatment 6 218 224

No Treatment 205 553 758

Total 211 771 982

Mental Health Problem (at intake) vs. Any MH Treatment by 3 months

79%

97%

72%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

% of Clients WithMod/High Need

(n=771/982)*

% w Need but No ServiceAfter 3 months

(n=553/771)

% of Services Going toThose in Need

(n=218/224)


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.

Residential Treatment need (at intake) vs. 7+ Residential days at 3 months

36%

52%

90%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

% of Clients WithMod/High Need

(n=349/980)*

% w Need but NoService After 3 months

(n=315/349)

% of Services Going toThose in Need (n=34/66)

Opportunity to redirect

existing funds through better

targeting


40

EHR can provide practice based evidence: Lessons from a Decade of GAIN data from CSAT Grants

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2009 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)

15-17 Years Old

71.2%, (n=15,705)

42

Diagnosis Time Period Matters

57%48%

18%

30%

32%

18%

13%19%

63%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Lifetime Past Year Past Month

No Use

Use

Abuse

Dependence


43

Definition of Substance Use Severity Matters

80%

54%

24%

93%

34%

5%

26%

48%

57%

72%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Past Year Substance Diagnosis

3 or More Years of Use

Weekly Use

Any Past Year Dependence

Any Withdrawal Symptoms in the Past Week

Severe Withdrawal (11+ Symptoms)

Can Give 1+ Reasons to Quit*

Client Believes Need ANY Treatment

Acknowledges Having an AOD Problem

Any Prior Substance Abuse Treatment

Source: CSAT 2009 Summary Analytic Data Set (n=21,816) *(n=11,066)

44

Multiple Clinical Problems are the NORM!

20%

41%

80%

48%

33%

63%

11%

24%

14%

34%

27%0% 10

%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Alcohol

Cannabis

Other drug disorder

Depression

Anxiety

Trauma

ADHD

CD

Suicide

Victimization

Violence/ illegal activity


45

The Number of Clinical Problems is related to Level of Care (over lapping but different mix)

41% 45%53%

65%

80%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

OP IOP CC-OP LTR STR

None

One

Two

Three

Four

Five to Twelve


Significantly more likely to

have 5+ problems (OR=5.8)

46

46%

71%

15%0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Low (0) Moderate (1-3) High (4-15)

None

One

Two

Three

Four

Five to Twelve

The Number of Major Clinical Problemsis highly related to Victimization


Significantly more likely to have 5+

problems (OR=13.9)

But this is the issue staff least

like to ask about!

Overcoming Staff Reluctance with General Victimization Scale

40%

31%

6%10%

1%8%9%

26%

29%7%

57%32%

19%11%

35%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Ever attacked w/ gun, knife, other weapon

Ever hurt by striking/beating

Abused emotionally

Ever forced sex acts against your will/anyone

Age of 1st abuse < 18

Any with more than one person involved

Any several times or for long time

Was person family member/trusted one

Were you afraid for your life/injury

People you told not believe you/help you

Result in oral, vaginal, anal sex

Currently worried someone attack

Currently worried someone beat/hurt

Currently worried someone abuse emotionally

Currently worried someone force sex acts

Source: CSAT 2009 Summary Analytic Data Set (n=19,318) 47

48

B1. Intoxication/Withdrawal Treatment Plan Needs

39%

22%

17%

1%

1%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Any Detox or withdrawal services

Ambulatory Detox (Risk/Mild)

Non-opioid Meds

Opiate Meds

Monitoring withdrawal and AOD medscompliance


49

B2. Biomedical Treatment Plan Needs

60%

33%

29%

17%

6%

1%

1%

78%

3%

4%

11%

16%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Tobacco cessation

Accom. for medical conditions

Discuss compliance w/ prescribed meds

Compliance with meds for PH probs

Discuss ER/hospitalization history

Currently treated for med problem

Tetanus shot

Eating disorder

Treatment of infectious diseases

Accommodations current pregnancy

Reduce sexual behavior risk

Reduce needle use/risk


50

B3. Psychological Treatment Plan Needs

59%

23%

22%

31%

18%

13%

12%

41%

74%

1%

4%

4%

8%

16%

17%

68%

72%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Any Co-occuring

Consq of behavior control problems

Refer to anger management

Suicidal risk intervention

Problems reading and writing

Compliance with psych meds

Currently treated for psych problem

Self-mutilation

Monitor self-mutilation

Cognitive impairment

Discuss lifetime mh hosp. history

Coordination with justice system

Consq of interpersonal illegal acts

Consq of drug-related illegal acts

Discuss lifetime arrest history

Consq of other illegal acts

Civil court proceedings


51

B4.Readiness Treatment Plan Needs

81%

16%

9%

3%

79%

73%

63%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Any Treatment Readiness Issues

Wrap-around or casemanagement services

Any pressure to be in treatment

Required to go to treatment

Reviw expectations for length oftreatment

Review dissatisfaction w/treatment

Partner to understandtreatment process


52

B5. Relapse Potential Treatment Plan Needs

67%

2%

84%

30%

28%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

High Relapse Potential

Recovery coach or mentor

Continuing Care aftercontrolled environment

Significant time in controlledenvironment

Discuss substance abusetreatment history


53

B6. Environment Treatment Plan Needs

63%

32%

29%

26%

32%

47%

54%

56%

70%

85%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Attended school in past 90 days

Coping with psycho-socialstressors

Child maltreatment

Recent school problems

Dissatisfaction withenvironment

Family fighting in the home

Vocational or governmentassistance

Substance use in the home

Employed in past 90 days

Housing situation


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/E2369.htm

http://www.astm.org/Standards/E2369.htm

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 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)

5. 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,

http://loinc.org/

http://www.ihtsdo.org/snomed-ct/

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

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: [email protected]. More information on the GAIN is available at www.chestnut.org/li/gain or by e-mailing [email protected] .

http://www.chestnut.org/li/posters

mailto:[email protected]

http://www.chestnut.org/li/gain

mailto:[email protected]

Additional Slides

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

Past Year Recovery “Rates” (Remission/Lifetime) by Disorders in the US


44%

66% 83

%

77%

58%

89%

89%

50%

45%

41% 56

%

57%

43%

31% 39

%

71%

48%

48%

44%

42%

41%

30%

0%10%20%30%40%50%60%70%80%90%

100%

Any

Dis

orde

r

Any

Sub

stan

ce D

isor

der

Dru

g D

isor

der

Alc

ohol

Dis

orde

r

Ext

erna

lizi

ng D

isor

der

Con

duct

Dis

orde

r

Opp

osit

iona

l Def

iant

AD

HD

Inte

rmit

tent

Exp

losi

ve

Inte

rnal

izin

g D

isor

der

Any

Moo

d D

isor

der:

Maj

or D

epre

ssiv

e E

pi.

Dys

thym

ia

Bi-

Pola

r I

or I

I

Any

Anx

iety

Dis

orde

r:

Adu

lt S

epar

atio

n A

nxie

ty

Gen

eral

ized

Anx

iety

Dis

.

Post

trau

mat

ic S

tres

s D

is.

Soci

al P

hobi

a

Pani

c D

isor

der

Ago

raph

obia

Oth

er S

peci

fic

Phob

ia

Past Year Recovery Rate

Prevalence of Lifetime Disorders and Past Year Remission in the US


47%

15%

8% 13% 25

%

10%

10%

8% 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

Dis

orde

r

Any

Sub

stan

ce D

isor

der

Dru

g D

isor

der

Alc

ohol

Dis

orde

r

Ext

erna

lizi

ng D

isor

der

Con

duct

Dis

orde

r

Opp

osit

iona

l Def

iant

AD

HD

Inte

rmit

tent

Exp

losi

ve

Inte

rnal

izin

g D

isor

der

Any

Moo

d D

isor

der:

Maj

or D

epre

ssiv

e E

pi.

Dys

thym

ia

Bi-

Pola

r I

or I

I

Any

Anx

iety

Dis

orde

r:

Adu

lt S

epar

atio

n A

nxie

ty

Gen

eral

ized

Anx

iety

Dis

.

Post

trau

mat

ic S

tres

s D

is.

Soci

al P

hobi

a

Pani

c D

isor

der

Ago

raph

obia

Oth

er S

peci

fic

Phob

ia

Lifetime Disorder

Past Year Remission

61

NOMS: Early Treatment Outcomes

56%

66%

76%

84%

72%

58%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Initiation within 14 days

Evidenced Based Practice

Engagement for at least 6weeks

Any Continuing Care (91-180 days)

Substance Use-Abstinent/Reduced 50% at 3 Months

12 month cost within bandsfor initial type of treatment

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

62

NOMS: Post Treatment Outcome (6-12 mo)

Source: CSAT 2009 SA Data Set subset to 1+ Follow ups

41%

90%

71%

12%

89%

80%

66%

17%

44%

99%

76%

68%

47%

44%

0% 10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Use

Abuse/Dependence Sx*

Physical Health

Mental Health

Nights of Psychiatric Inpatient

Illegal Activity

Arrests

Housed in Community**

Family/Home Problems

Vocational Problems

Social Support/Engagement

Recovery Environment Risk

Quarterly Cost to Society

In Work/School**

Reduced 50%or NoProblemNo Problem

*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

But Need to Control for the lack of Problems at Intake

Source: CSAT 2009 SA Data Set subset to 1+ Follow ups

98%

79%

13%

33%37%

52%

78%

61%

11%37%

42%19%

5%

2%

0%

10

%

20

%

30

%

40

%

50

%

60

%

70

%

80

%

90

%

10

0%

Use

Abuse/Dependence Sx*

Physical Health

Mental Health

Nights of Psychiatric Inpatient

Illegal Activity

Arrests

Housed in Community

Family/Home Problems

Vocational Problems

Social Support/Engagement

Recovery Environment Risk

Quarterly Cost to Society

In Work/School

* Variable measures the last 30 days. All others measure the past 90 days.

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)

8%6%8%

14%

12%

29%

11%

13%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Total

Five or More

Four

Three

Two

One

None

Negative one

Less than negative one

78% Improved in 1 or more areas (29% in 5 or more)

Outcomes May be Hidden by Subgroups: Example of HIV Risk Outcomes

-0.0

3

-0.1

0 -0.0

2

-0.80

-0.60

-0.40

-0.20

0.00

0.20

0.40

A. Low Risk

B. Mod. RiskW/O Trauma

C. Mod. RiskWith Trauma

D. High Risk

Total

Coh

en's

Eff

ect S

ize

d

Unprotected Sex Acts (f=.14)

Days of Victimization (f=.22)

Days of Needle Use (f=1.19)

-0.3

9

0.20

-0.0

4

-0.0

8

0.00

0.15

-0.2

9

0.01

0.10

0.27

0.00

-0.6

9

Source: Lloyd et al 2007

Any Illegal Activity can be better predicted by using Intake Severity on Crime/Violence and Substance Problem Scales

58%46%

36%53%

33%26%44%

27%20%

0%

20%

40%

60%

An

y I

leg

al

Ac

tiv

ity

(mo

nth

s1

-6)

High Mod Low LowMod

High

Crime/Violence Scale (Intake)

Substance Problem Scale

(Intake)

Source: CSAT 2008 V5 dataset Adolescents aged 12-17 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

opportunities to use electronic behavioral health records and national treatment data standards to...

Documents

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