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1
Managing Substance Use Disorders (SUDS) as a Chronic Condition
Michael L. Dennis, Ph.D. Chestnut Health Systems
720 W. Chestnut, Bloomington, IL 61701, USA E-mail: [email protected]
Presentation in the Recovery Conference: Vision to Outcomes
Hartford, CT, May 16-17, 2006
This presentation was supported by funds from the Connecticut Department of Mental Health and Addiction Services and data from NIDA grant no. R37-DA11323, and R01 DA15523 and SAMHSA/CSAT contract no. 270-2003-00006 . The opinions are those of the author do not reflect official positions of the government . Please address comments or questions to the author at [email protected] or 309-820-3805. A copy of
these slides will be posted at www.chestnut.org/li/posters
.
2
Problem and Purpose
• Over the past several decades there has been a growing recognition that a subset of substance users suffers from a chronic condition that requires multiple episodes of care over several years.
• This presentation will focus on 1. Describing the prevalence and characteristics of this subset of
people 2. the course of these disorders, and 3. the results of three experiments designed to improve the ways
in which this condition is managed across time and multiple episodes of care.
3
Definition of Chronic SUD• While terms like substance use, abuse, dependence, and addiction are
frequently used interchangeably, state regulators, accreditation programs, clinical providers and more recently clinical researchers have become increasingly consistent in how they define chronic substance use disorders.
• The American Psychiatric Association (APA, 1994, 2000) and the World Health Organization (WHO, 1999) use the term “substance dependence” to indicate a pattern of chronic problems (e.g., withdrawal, inability to stop, giving up activities) that are likely to persist.
• They use the term “substance abuse” and “hazardous use”respectively to identify people not meeting the dependence criteria but having other moderate severity symptoms (e.g., hazardous use, legal problems) suggesting the need for treatment.
• These standards also recognize that the course of substance use disorders includes periods of relapse, treatment, incarceration, and remission (i.e., the absence of symptoms while in the community)
4
Severity of Past Year Substance Use/Disorders (2002 U.S. Household Population age 12+= 235,143,246)
Dependence 5%
Abuse 4%
Regular AOD Use 8%
Any Infrequent Drug Use 4%
Light Alcohol Use Only 47%
No Alcohol or Drug Use
32%
Source: 2002 NSDUH and Dennis & Scott under review
5
Problems Vary by Age
Source: 2002 NSDUH and Dennis & Scott under review
0
10
20
30
40
50
60
70
80
90
100
12-13
14-15
16-17
18-20
21-29
30-34
35-49
50-64
65+
No Alcohol or Drug Use
Light Alcohol Use Only
Any Infrequent Drug Use
Regular AOD Use
Abuse
Dependence
NSDUH Age Groups
Severity CategoryAdolescent
OnsetRemission
Increasing rate of non-
users
6
Higher Severity is Associated with Higher Annual Cost to Society Per Person
Source: 2002 NSDUH and Dennis & Scott under review
$0$231 $231
$725$406
$0$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
$3,500
$4,000
No Alcohol orDrug Use
Light Alcohol
Use Only
AnyInfrequentDrug Use
Regular AODUse
Abuse Dependence
Median (50th percentile)
$948
$1,613
$1,078$1,309
$1,528
$3,058Mean (95% CI)
This includes people who are in recovery, elderly, or do not use
because of health problems Higher Costs
7
Age of First Use Predicts Symptoms of Dependence an Average of 22 years Later
Source: Dennis, Babor, Roebuck & Donaldson (2002) and 1998 NHSDA
3945
63
71
3734
51
62
30
23
41
48
0
10
20
30
40
50
60
70
80
90
100
Tobacco, OR=1.3*,Pop.=151,442,082
Alcohol, OR=1.9*,Pop.=176,188,916
Marijuana, OR=1.5*,Pop.=71,704,012
Other, OR=1.5*, Pop.=38,997,916
% w
ith
1+ P
ast Y
ear
Sym
ptom
s
Under Age 15
Aged 15-17
Aged 18 or older
Tobacco: Pop.=151,442,082
OR=1.49*
Alcohol: Pop.=176,188,916
OR=2.74*
* p<.05
Marijuana:Pop.=71,704,012
OR=2.45*
Other Drugs:Pop.=38,997,916
OR=2.65*
8
Study 2. Pathways to Recovery (Scott & Dennis)
Recruitment: 1995 to 1997
Sample: 1,326 participants from sequential admissions to a stratified sample of 22 treatment units in 12 facilities, administered by 10 agencies on Chicago's west side.
Levels of Care: Adult OP, IOP, MTP, HH, STR, LTR
Instrument: Augmented version of the Addiction SeverityIndex (A-ASI)
Follow-up: Of those alive and due, follow-up interviews werecompleted with 94 to 98% in annual interviews out
to 8 years (going to 10 years); over 80% completed within +/- 1 week of target date.
Funding: CSAT grant # T100664, contract # 270-97-7011NIDA grant 1R01 DA15523
9
Intake Characteristics
• Participants were mostly African-American (88%), female (59%), and in their 30s (48%); At intake, 32% were homeless and 25% were involved in the criminal justice system.
• The most common substances used weekly were: cocaine (33%), heroin (31%), alcohol (27%), and marijuana (7%).
• Many met criteria for Major Depression (36%) or Generalized Anxiety Disorder (36%).
• 54% have been in treatment before (27% 2+ times)• The participants were initially referred to outpatient (19%),
methadone (19%), intensive outpatient (18%), halfway house (10%), short term residential (20%), long term residential (13%).
10
Survival Analysis
• Time frames related to age of use, treatment, and death were measured across all sources and waves of information (taking the earliest first use, treatment episode, and 12 month period of abstinence or death).
• Age at last use was defined as the age when a person first completed a period of 12 month abstinence or had died (35 or 2.6% of the people died in 3 years).
• Durations were estimated with Cox Proportional Hazards Regression– censoring people who were in treatment or still using, – censoring years past which we had less than 100 people to make the estimate, and– creating a 30 year window of observation on the trajectory of substance use
disorders starting at the time of first use
11
Age Distributions
0
20
40
60
80
100
120
140
160
180
0 10 20 30 40 50 60
Age
Age at first Use (0% censored)
Age at First Tx (0% cesored)
Age at Study Intake (0% censored)
Age at recovery or death (53% censored)
12
Substance Use Careers Last for Decades P
erce
nt
in R
ecov
ery
Years from first use to 1+ years abstinence
302520151050
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Median duration of
27 years(IQR: 18 to
30+)
Source: Dennis et al 2005 (n=1,271)
13
Substance Use Careers are Longer, the Younger the Age of First Use
Per
cen
t in
Rec
over
y
Years from first use to 1+ years abstinence
302520151050
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Source: Dennis et al 2005 (n=1,271)
under 15*
21+
15-20*
Age
of
1st U
se G
rou
ps
* p<.05 (different from 21+)
14
Substance Use Careers are Shorter the Sooner People get to Treatment
Per
cen
t in
Rec
over
y
Years from first use to 1+ years abstinence
302520151050
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Source: Dennis et al 2005 (n=1,271)
20+
0-9*
10-19*
Yea
rs t
o 1st
Tx
Gro
up
s
* p<.05 (different from 20+)
15
It Takes Decades and Multiple Episodes of Treatment
Years from first Tx to 1+ years abstinence
2520151050
Median duration of 9 years
(IQR: 3 to 23) and 3 to 4
episodes of care
Per
cen
t in
Rec
over
y
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Source: Dennis et al 2005 (n=1,271)
16
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Over 55% Continued to Changed Status Between Annual Follow-up Interviews (83% over 3 years)
In thecommunityIn Recovery
In TreatmentIncarcerated
In thecommunityusing
In the Community Using(57%)
Inc.(6%)
Recovery(26%)
In Tx.(12%)
Status at 24 months
Status at 36 months
17
The Cyclical Course of Relapse, Incarceration, Treatment and Recovery
In the Community
Using (53% stable)
In Treatment (21% stable)
In Recovery (58% stable)
Incarcerated(37% stable)
6%
13%
28%
30%
8%
25%
31%
4%
44%7%
29%
7%
Treatment is the most likely path
to recovery
P not the same in both directions
Source: Scott et al 2005
18Source: Scott et al 2005
Predictors of Change Also Vary by Direction
In the Community
Using (53% stable)
In Recovery (58% stable)
13%
29%
Probability of Relapsing from Abstinence + times in treatment (1.21) - female (0.58) + homelessness (1.64) - number of arrests (1.12)
- ASI legal composite (0.84)- # of sober friend (0.82)- per 77 self help sessions (1.41)
Probability of Transitioning from Using to Abstinence - mental distress (0.88) + older at first use (1.12) -ASI legal composite (0.84) + homelessness (1.27)
+ # of sober friend (1.23)+ per 8 weeks in treatment (1.14)
19
Post Script on the Pathways Study
• There is clearly a subset of people for whom substance use disorders are a chronic condition that last for many years
• Rather than a single transition, most people cycle through abstinence, relapse, incarceration and treatment 3 to 4 times before reaching a sustained recovery.
• It is possible to predict the likelihood risk of when people will transition
• Treatment predicts who transitions from use to recovery and self help group participation predicts who stays in recovery.
20
Treatment Participation
• Only 1 in 5 people with dependence or abuse in the U.S. receive any kind of treatment, and about half of those access it through publicly-funded substance abuse treatment (Epstein, 2002)
• People presenting to publicly funded treatment with dependence (vs. others with abuse, intoxication, primarily other psychiatric diagnoses) are more likely to have been – in treatment before one or more times (57% vs. 39%, OR=1.46, p<.05), – in treatment 3 or more times (16% vs. 9%, OR=1.79, p<.05),– assigned to intensive outpatient (15% vs. 6%, OR=2.52, p<.05) – assigned to residential treatment (16% vs. 5%, OR=3.17, p<.05)
(OAS, 2002 on line data at http://webapp.icpsr.umich.edu/cocoon/ICPSR-SERIES/00056.xml)
• People with 3 or more diagnoses were significantly more likely than those with just 1 diagnosis to enter treatment (34% vs. 7%) (Kessler, et al., 1996).
21
The Majority Stay in Tx Less than 90 days
Source: Data received through August 4, 2004 from 23 States (CA, CO, GA, HI, IA, IL, KS, MA, MD, ME, MI, MN, MO, MT, NE, NJ, OH, OK, RI, SC, TX, UT, WY) as reported in Office of Applied Studies (OAS; 2005). Treatment Episode Data Set (TEDS): 2002. Discharges from Substance Abuse Treatment Services, DASIS Series: S-25, DHHS Publication No. (SMA) 04-3967, Rockville, MD: Substance Abuse and Mental Health Services Administration. Retrieved from http://wwwdasis.samhsa.gov/teds02/2002_teds_rpt_d.pdf .
52
42
20
33
0
30
60
90
Outpatient IntensiveOutpatient
Short TermResidential
Long TermResidential
Level of Care
Med
ian
Len
gth
of S
tay
in D
ays
22
Less Than Half Are Positively Discharged
Source: Data received through August 4, 2004 from 23 States (CA, CO, GA, HI, IA, IL, KS, MA, MD, ME, MI, MN, MO, MT, NE, NJ, OH, OK, RI, SC, TX, UT, WY) as reported in Office of Applied Studies (OAS; 2005). Treatment Episode Data Set (TEDS): 2002. Discharges from Substance Abuse Treatment Services, DASIS Series: S-25, DHHS Publication No. (SMA) 04-3967, Rockville, MD: Substance Abuse and Mental Health Services Administration. Retrieved from http://wwwdasis.samhsa.gov/teds02/2002_teds_rpt_d.pdf .
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Outpatient IntensiveOutpatient
Short TermResidential
Long TermResidential
Level of Care
Dis
char
ge S
tatu
s
Other
Terminated
Dropped out
Completed
Transferred
Less than 10% are transferred
23
Number of GAIN Sites
Adolescent and Adult Treatment Program GAIN Clinical Collaborators
30 to 6010 to 292 to 91
One or more state or county wide systems uses the GAIN
One or more state or county wide systems considering using the GAIN
07/05
24
Multiple Co-occurring Problems Contribute to Chronicity
0% 20%
40%
60%
80%
100%
Health Distress
Internal Disorders
External Disorders
Crime/Violence
Criminal JusticeSystem
Involvement
Dependent (n=1221)
Other (n=385)
0% 20%
40%
60%
80%
100%
Dependent (n=3135)
Other (n=2617)
Adolescents Adults
Source: GAIN Coordinating Center Data Set
Exception
25
Treatment Outcomes by Level of Care: Recovery*
* Recovery defined as no past month use, abuse, or dependence symptoms while living in the community. Percentages in parentheses are the treatment outcome (intake to 12 month change) and the stability of the outcomes (3months to 12 month change) Source: CSAT Adolescent Treatment Outcome Data Set (n-9,276)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Pre-Intake Mon 1-3 Mon 4-6 Mon 7-9 Mon 10-12
Per
cent
in P
ast
Mon
th R
ecov
ery* Outpatient (+79%, -1%)
Residential(+143%, +17%)
Post Corr/Res (+220%, +18%)
OP & Resid
Similar
CC better
26
Findings from the Assertive Continuing Care (ACC) Experiment
• 183 adolescents admitted to residential substance abuse treatment
• Treated for 30-90 days inpatient, then discharged to outpatient treatment
• Random assignment to usual continuing care (UCC) or “assertive continuing care” (ACC)
• Over 90% follow-up 3, 6, & 9 months post discharge
Source: Godley et al 2002, in press
27
Time to Enter Continuing Care and Relapse after Residential Treatment (Age 12-17)
Source: Godley et al., 2004 for relapse and 2000 Statewide Illinois DARTS data for CC admissions
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0 10 20 30 40 50 60 70 80 90
Days after Residential (capped at 90)
Per
cen
t of
Clie
nts
Cont.CareAdmis.
Relapse
28
ACC Enhancements
• Continue to participate in UCC
• Home Visits
• Sessions for adolescent, parents, and together
• Sessions based on ACRA manual (Godley, Meyers et al., 2001)
• Case Management based on ACC manual (Godley et al, 2001) to assist with other issues (e.g., job finding, medication evaluation)
29
Assertive Continuing Care (ACC)Hypotheses
Assertive Continuin
g Care
General Continuin
g Care Adherence
Relative to UCC, ACC will increase General Continuing Care Adherence (GCCA)
Early Abstinence
GCCA (whether due to UCC or ACC) will be associated with higher rates of early abstinence
Sustained Abstinence
Early abstinence will be associated with higher rates of long term abstinence.
30
ACC Improved Adherence
Source: Godley et al 2002, forthcoming
0% 10%
20%
30%
40%
50%
60%
70%
80%
Weekly Tx Weekly 12 step meetings
Regular urine tests
Contact w/probation/school
Follow up on referrals*
ACC * p<.05
90%
100%
Relapse prevention*
Communication skills training*
Problem solving component*
Meet with parents 1-2x month*
Weekly telephone contact*
Referrals to other services*
Discuss probation/school compliance*
Adherence: Meets 7/12 criteria*
UCC
31
GCCA Improved Early (0-3 mon.) Abstinence
Source: Godley et al 2002, forthcoming
24%
36% 38%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Any AOD (OR=2.16*) Alcohol (OR=1.94*) Marijuana (OR=1.98*)
Low (0-6/12) GCCA
43%
55% 55%
High (7-12/12) GCCA * p<.05
32
Early (0-3 mon.) Abstinence Improved Sustained (4-9 mon.) Abstinence
Source: Godley et al 2002, forthcoming
19% 22% 22%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Any AOD (OR=11.16*) Alcohol (OR=5.47*) Marijuana (OR=11.15*)
Early(0-3 mon.) Relapse
69%
59%
73%
Early (0-3 mon.) Abstainer * p<.05
33
Post script on ACC
• The ACC intervention improved adolescent adherence to the continuing care expectations of both residential and outpatient staff; doing so improved the rates of short term abstinence and, consequently, long term abstinence.
• Despite these gains, many adolescents in ACC (and more in UCC) did not adhere to continuing care plans.
• The ACC preliminary findings are published and the main findings are currently under review.
• Several CSAT grantees are also seeking to replicate ACC as part of the Adolescent Residential Treatment (ART) and Assertive Adolescent Family Therapy (AAFT) programs.
• A second ACC experiment is currently under way to evaluate whether providing contingency management will further improve outcomes.
• The ACC manual is being distributed via the website and the CD you have been provided.
34
The Early Re-Intervention (ERI) Experiments
ERI 1 ERI 2Recruitment Recruited 448 from
Community Based Treatment in Chicago in 2000 (84% of eligible recruited)
Recruited 446 from Community Based Treatment in Chicago in 2004 (93% of eligible recruited)
Design Random assignment to Recovery Management Checkups (RMC) or control
Random assignment to Recovery Management Checkups (RMC) or control
Follow-Up Quarterly for 2 years (95-97% per wave)
Quarterly for 4 years (95 to 97% per wave)
Data Sources GAIN, CEST, Urine, Salvia
Staff logs
GAIN, CEST, CAI, Neo, CRI, Urine, Staff logs
Publication Dennis, Scott & Funk 2003; Scott, Dennis & Foss, 2005
Scott & Dennis, under review (12 month findings)
Funding Source NIDA grant R37-DA11323
35
Sample Characteristics of ERI 1 & 2 Experiments
0% 20%
40%
60%
80%
100%
African American
Age 30-49
Female
Employed
Dependence
Prior Treatment
Residential Treatment
Other Mental Disorders
Homeless
Physical Health Problems
ERI 1 (n=448)
ERI 2 (n=446)
36
Need For Treatment Re-Intervention
• Eligibility: Not already in treatment or incarcerated and living in the community
• Need: Yes to at least one of the following…(a) During the past 90 days, have you used alcohol,
marijuana, cocaine, or other drugs on 13 or more days?(b) During the past 90 days, have you gotten drunk or been
high for most of 1 or more days?(c) During the past 90 days, has your alcohol or drug use
caused you not to meet your responsibilities at work/school/home on 1 or more days?
(d) During the past week, had withdrawal symptoms when you tried to stop, cut down, or control your use?
(e) Do you feel that you need to return to treatment?(f) During the past month, has your substance use caused you
any problems?
37
Recovery Management Checkups (RMC) in both ERI 1 & 2 included:
• Quarterly Screening to determining “Eligibility” and “Need”
• Linkage meeting/motivational interviewing to:– provide personalized feedback to participants about their
substance use and related problems, – help the participant recognize the problem and consider
returning to treatment, – address existing barriers to treatment, and – schedule an assessment.
• Linkage assistance– reminder calls and rescheduling– Transportation and being escorted as needed
38
720630540450360270180900
1.0
.9
.8
.7
.6
.5
.4
.3
.2
.1
0.0
H1: RMC Clients will return to treatment sooner
Control (51% readmitted)
Days to Readmission
Percent to be R
eadmitted
OR: 1.34X2
(1)=6.8, p<.01
RMC(64% readmitted)
Median of 376 vs. 600 days,
Wald=5.2, p<.05
Median of 376 vs. 600 days,
Wald=5.2, p<.05
39
H2: RMC clients will receive more treatment
Days % with 90+ Days
50
0
10
20
30
40
50
60
70
Control RMC
Mea
n D
ays
of S
ubse
quen
t Tre
atm
ent
(m
onth
s 4-
24)
t(390)=2.65, p<.05
17%
6225%
0%
5%
10%
15%
20%
25%
30%
Control RMC
% w
ith
90+
day
s of
Sub
sequ
ent
Tre
atm
ent (
mon
ths
4-24
)
OR 1.61, X2(1)=4.1, p<.05
40
H3: RMC clients will be less likely to use at 24m
43%
56%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Control (n=244) RMC (n=224)
X2(1) = 7.7, p<.01
41
However, 32% of individuals change status between the beginning and end of the quarter (82% over two years)
In thecommunityIn Recovery
In Treatment
IncarceratedIn thecommunityusing
In the Community Using(41%)
Inc.(5%)
Recovery(42%)
In Tx.(12%)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100% End of Quarter
Beginning of Quarter(3,136 quarterly transition
Observations on 448 unique people)Status at beginning of Quarter
Status at the end of Quarter
42
Source: ERI experiments (Scott, Dennis, & Foss, 2005)
Impact on Primary Pathways to Recovery(incarceration not shown)
In the Communityy
Using (71% stable)
In Treatment (35% stable)
In Recovery (76% stable)
27%
5%
8%
33%
18%
17%
Transition to Tx - Freq. of Use (0.7)
+ Prob. Orient. (1.4)+ Desire for Help (1.6)
+ RMC (3.22)
Again the Probability of
Entering Recovery is Higher from
Treatment
Transition to Recov. - Freq. of Use (0.7)
- Dep/Abs Prob (0.7)- Recovery Env. (0.8)- Access Barriers (0.8)+ Prob. Orient. (1.3)+ Self Efficacy (1.2)
+ Self Help Hist (1.2)+ per 10 wks Tx (1.2)
43
Other Variables That Lost Significance in Multivariate Model
• Problem Recognition, External Pressure, Internal Motivation, Treatment Resistance
• Current Withdrawal, Number of Diagnosis, Emotional Problems, Illegal Activity, Homelessness
• Coming from a controlled environment• Involvement with the Criminal Justice System,
Mental Health, Health, or Training/School Systems
• Lifetime number of prior treatment, arrests• Gender, Race, Age, Employment
44
Modifications to RMC for ERI -2 included:
• Switch to on-site urine monitoring with immediate feedback to improve detection
• Transportation assistance for everyone to improve the show rates for assessment and treatment
• Improved Quality Assurance/Adherence• Engagement assistance to improve the rates of staying at
least 14 days– Daily contact (mostly face to face)– Acting as an ombudsman– Agreement from provider not to administratively
discharge from treatment without contacting us first
45
0%
20%
40%
60%
80%
100%F
ollo
w-u
p(9
6% a
vg)
Nee
ded
Tx
(45%
avg
)
Atte
nded
Lin
kage
(99%
avg
)
Agr
eed
to T
xA
sses
smen
t(4
8% a
vg)
Sho
wed
to T
xA
sses
smen
t(4
2% a
vg)
Sho
wed
to T
x(3
5% a
vg)
Sta
yed
in T
x 14
+ d
ays
(60%
avg
)
ERI 1MaxAvgMin
Adherence to Recovery Management Checkup (RMC) Protocol in ERI 1 vs. 2
Source: ERI experiments (Dennis, Scott, & Funk 2003; Scott, Dennis, & Funk, 2005; Scott & Dennis, forthcoming)
Generally averaged as well or better
Quality assurance and transportation assistance reduced the variance
ImprovedScreening
ERI 2
Improved Retention
46
% Readmitted (Months 4-12)
Relative to Control clients, RMC clients were more likely to return to treatment
Source: ERI experiments (Dennis, Scott, & Funk 2003; Scott, Dennis, & Funk, 2005; Scot & Dennis, forthcoming
30%38%
22%
36%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
ERI 1 (d=+.17)T ERI-2 (d=+.30)*
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
*p<.05ERI 1 RMC ERI 2 Control ERI 2 RMCERI 1 Control
47
Mean Days of Treatment Received (months 4-12)
20
28
17
30
0
10
20
30
40
50
ERI 1 (d=+.16) ERI-2 (d=+.28)*
0
10
20
30
40
50
ERI 1 OM ERI 1 RMC ERI 2 OM ERI 2 RMC *p<.05
RMC clients received more Total Days of Treatment
Source: ERI experiments (Dennis, Scott, & Funk 2003; Scott, Dennis, & Funk, 2005; Scott & Dennis forthcoming)
ERI 1 RMC ERI 2 Control ERI 2 RMCERI 1 Control
48
% with any successive quarters in need of treatment
42% 42%
63%
54%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
ERI 1 (d= -.00) ERI-2 (d= -.23)*
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
ERI 1 OM ERI 1 RMC ERI 2 OM ERI 2 RMC *p<.05
RMC clients were less likely to haveSuccessive Quarters in Need of Treatment
Source: ERI experiments (Dennis, Scott, & Funk 2003; Scott, Dennis, & Funk, 2005; Scott & Dennis forthcoming)
ERI 1 RMC ERI 2 Control ERI 2 RMCERI 1 Control
49
In Need of Tx (using in community) at 12 months
52% 50%
60%
47%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
ERI 1 (d= -.07) ERI-2 (d= -.32)*
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
ERI 1 OM ERI 1 RMC ERI 2 OM ERI 2 RMC *p<.05
RMC clients were less likely to be in need of treatment at the end of 12 months
Source: ERI experiments (Dennis, Scott, & Funk 2003; Scott, Dennis, & Funk, 2005; Scott & Dennis forthcoming)
Every Quarter this difference has been growing; Hence our plans to go out 4 years
ERI 1 RMC ERI 2 Control ERI 2 RMCERI 1 Control
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Post Script on ERI experiments
• Again, severity was inversely related to returning to treatment on your own and treatment was the key predictor of transitioning to recovery
• The ERI experiments demonstrate that the cycle of relapse, treatment re-entry and recovery can be shortened through more proactive intervention
• Working to ensure engagement for at least 14 days upon readmission helped to improve outcomes
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Other Emerging Recovery Support Initiatives
• Interactive phone and web based monitoring and recovery support
• Self help groups
• Recovery homes
• Recovery High Schools & Colleges
• Well-briety movement in Indian Country
• Recovery advocacy movement
• Network for the Improvement of Addiction Treatment (NIATx; http://www.pathstorecovery.org/
• Washington Circle Group (http://www.washingtoncircle.org/) and other efforts to introduce performance monitoring
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Reprise
• These studies provide converging evidence demonstrating that substance use disorders commonly present with a wide range of co-occurring problems that are likely to interfere with recovery.
• They show that the majority of people accessing publicly funded substance abuse treatment have been in treatment before, are likely to return, and may need several additional episodes of care before they reach a point of stable recovery.
• Yet over half do make it to recovery• The three experiments demonstrated that it is feasible to
alter the substance use trajectories and treatment careers.
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We need to..• Educate policy makers, staff and clients to have more realistic expectations• Redefine the continuum of care to include monitoring and other proactive
interventions between primary episodes of care. • Shift our focus from intake matching to on-going monitoring, matching over
time, and strategies that take the cycle into account• Identify other venues (e.g., jails, emergency rooms) where recovery
management can be initiated• Evaluate the costs and determine generalizability to other populations
through replication• Explore changes in funding, licensure and accreditation to accommodate and
encourage above
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Sources and Related Work• American Psychiatric Association. (1994). American Psychiatric Association diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: American
Psychiatric Association.• American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (DSM-IV-TR) (4th - text revision ed.). Washington, DC: American
Psychiatric Association. • Epstein, J. F. (2002). Substance dependence, abuse and treatment: Findings from the 2000 National Household Survey on Drug Abuse (NHSDA Series A-16, DHHS
Publication No. SMA 02-3642). Rockville, MD: Substance Abuse and Mental Health Services Administration, Office of Applied Studies. Retrieved from http://www.DrugAbuseStatistics.SAMHSA.gov.
• GAIN Coordinating Center Data Set (2005). Bloomington, IL: Chestnut Health Systems. See www.chestnut.org/li/gain .• Kessler, R. C., Nelson, G. B., McGonagle, K. A., Edlund, M. J., Frank, R. G., & Leaf, P. J. (1996). The epidemiology of co-occurring mental disorders and substance use
disorders in the national comorbidity survey: Implications for prevention and services utilization. Journal of Orthopsychiatry, 66, 17-31.• Dennis, M. L., Scott, C. K. (under review). Managing substance use disorders (SUD) as a chronic condition. NIDA Science and Perspectives.• Dennis, M. L., Scott, C. K., Funk, R., & Foss, M. A. (2005). The duration and correlates of addiction and treatment careers. Journal of Substance Abuse Treatment, 28, S51-
S62.• Dennis, M. L., Scott, C. K., & Funk, R. (2003). An experimental evaluation of recovery management checkups (RMC) for people with chronic substance use disorders.
Evaluation and Program Planning, 26(3), 339-352.• Godley, M. D., Godley, S. H., Dennis, M. L., Funk, R., & Passetti, L. (2002). Preliminary outcomes from the assertive continuing care experiment for adolescents discharged
from residential treatment. Journal of Substance Abuse Treatment, 23, 21-32.• Office Applied Studies (2002). Analysis of the 2002 National Survey on Drug Use and Health (NSDUH) on line at
http://webapp.icpsr.umich.edu/cocoon/ICPSR-SERIES/00064.xml . • Office Applied Studies (2002). Analysis of the 2002 Treatment Episode Data Set (TEDS) on line data at http://webapp.icpsr.umich.edu/cocoon/ICPSR-SERIES/00056.xml) • Scott, C. K., & Dennis, M. L. (forthcoming). A Replicable Model for Managing Addiction as a Chronic Condition using Quarterly Recovery Management Check-ups
(RMC). Manuscript under review.• Scott, C. K., Dennis, M. L., & Foss, M. A. (2005). Utilizing recovery management checkups to shorten the cycle of relapse, treatment re-entry, and recovery. Drug and
Alcohol Dependence, 78, 325-338.• Scott, C. K., Foss, M. A., & Dennis, M. L. (2005). Pathways in the relapse, treatment, and recovery cycle over three years. Journal of Substance Abuse Treatment, 28, S61-
S70.• World Health Organization (WHO). (1999). The International Statistical Classification of Diseases and Related Health Problems, tenth revision (ICD-10). Geneva,
Switzerland: World Health Organization. Retrieved from www.who.int/whosis/icd10/index.html.
