1 findings from the pathways to recovery and recovery management checkups (rmc) experiments michael...

1

Findings from the Pathways to Recovery and Recovery Management Checkups

(RMC) Experiments

Michael L. Dennis, Ph.D.& Christy K Scott, Ph.D.

Chestnut Health Systems Bloomington and Chicago, IL

Presentation at the Haymarket Center's 15th Annual Summer Institute On Addictions, Oakbrook Terrace, IL, June 9-11, 2009.. This presentation was supported by funds from NIDA grants no.

R13 DA027269, R01 DA15523, R37-DA11323 and CSAT contract no. 270-07-0191. It is available electronically at www.chestnut.org/li/posters . The opinions are those of the authors

do not reflect official positions of the government. Please address comments or questions to the author at [email protected] or 309-820-3805.

.

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

mailto:[email protected]

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 present

1. Epidemiological data to illustrate the chronic nature of substance disorders and how it relates to a broader understanding of recovery

2. The results of two experiments designed to improve the ways in which recovery is managed across time and multiple episodes of care.

3

Normal

10 days of abstinence

100 days of abstinence

Source: Volkow ND, Hitzemann R, Wang C-I, Fowler IS, Wolf AP, Dewey SL. Long-term frontal brain metabolic changes in cocaine abusers. Synapse 11:184-190, 1992; Volkow ND, Fowler JS, Wang G-J, Hitzemann R, Logan J, Schlyer D, Dewey 5, Wolf AP. Decreased dopamine D2 receptor availability is associated with reduced frontal metabolism in cocaine abusers. Synapse 14:169-177, 1993.

Prolonged Substance Use Injures The Brain:Prolonged Substance Use Injures The Brain:Healing Takes Time Healing Takes Time

Normal levels of brain activity in PET

scans show up in yellow to red

After 100 days of abstinence, we can

see brain activity “starting” to recover

Reduced brain activity after regular

use can be seen even after 10 days

of abstinence

4

Alcohol and Other Drug Abuse, Dependence and Problem Use Peaks at Age 20

Source: 2002 NSDUH and Dennis & Scott, 2007, Neumark et al., 2000

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+Other drug or heavy alcohol use

Alcohol or Drug Use (AOD) Abuse or Dependence

Age

Severity Category

Over 90% of use and

problems start between the ages of

12-20

It takes decades before most recover or die

*2002 U.S. Household Population

estimated to be 235,143,246

People with drug dependence die an

average of 22.5 years sooner than those

without a diagnosis

5

8.9%

21.2%

7.3%

0.5% 1.0% 0.6%0%

5%

10%

15%

20%

25%

12 to 17 18 to 25 26+

Alcohol or Other Drug Abuse or Dependence Any Public or Private Treatment

Treatment Participation Rates Are Low

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

Few Get Treatment: 1 in 17 adolescents,

1 in 22 young adults, 1 in 12 adults

Much of the private funding is limited to 30 days or less and authorized day by day

or week by week

6

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

Half are gone within 8 weeks, less than 25%

stay the 90 days recommended by NIDA

researchers

7

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

8

Multiple Co-occurring Problems are Correlated with Severity and Contribute to Chronicity

0% 20%

40%

60%

80%

100%

Health Distress

Internal Disorders

External Disorders

Crime/Violence

Criminal JusticeSystem

Involvement

Dependent (n=1221)

Abuse/Other (n=385)

0% 20%

40%

60%

80%

100%

Dependent (n=3135)

Abuse/Other (n=2617)

Adolescents Adults

Source: GAIN Coordinating Center Data Set

Adolescents More likely to have externalizing

disorders

Adults more likely to have internalizing

disorders[

9

Nine Year Pathways to Recovery Study (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.

Substance: Cocaine (33%), heroin (31%), alcohol (27%), marijuana (7%).

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 outto 9 years; over 80% completed within +/- 1 week of target date.

Funding: CSAT grant # T100664, contract # 270-97-7011NIDA grant 1R01 DA15523

10

Pathways to Recovery Sample Characteristics

0% 20%

40%

60%

80%

100%

African American

Age 30-49

Female

Current CJ Involved

Past Year Dependence

Prior Treatment

Residential Treatment

Other Mental Disorders

Homeless

Physical Health Problems

The sample is predominately

African American,

Middle Age, Female, With Dependence,

and Prior Treatment

Source: Dennis , Scott, Funk & Foss ( 2005) (n=1,271)

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People Entering Publicly Funded Treatment Generally Use For Decades

Per

cen

t st

ill u

sin

g

Years from first use to 1+ years of abstinence302520151050

Source: Dennis et al., 2005

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

It takes 27 years before half reach 1 or more years of abstinence or die

12

Per

cen

t st

ill u

sin

g

Years from first use to 1+ years of abstinence

under 15

21+

15-20

Age of First Use

302520151050


100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

60% longer

The Younger They Start, The Longer They Use

13

Per

cen

t st

ill u

sin

g

Years from first use to 1+ years of abstinence

Years to first

Treatment Admission

302520151050


100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

20 or more years

0 to 9 years

10 to 19 years

57% shorter

The Sooner They Get The Treatment, The Shorter They Use

14

After Initial Treatment…

• Relapse is common, particularly for those who are: – Younger– Have already been to treatment multiple times – Have more mental health issues or pain

• It takes an average of 3 to 4 treatment admissions over 9 years before half reach a year of abstinence

• Yet over 2/3rds do eventually abstain

• Treatment predicts who starts abstinence

• Self help engagement predicts who stays abstinent

Source: Dennis et al., 2005, Scott et al 2005

15

The Cyclical Course of Relapse, Incarceration, Treatment and Recovery (Adults)

In the Community

Using (53% stable)

In Treatment (21% stable)

In Recovery (58% stable)

Incarcerated(37% stable)

6%

28%

13%

30%

8%

25%

31%

4%

44%7%

29%

7%

Treatment is the most likely path

to recovery

P not the same in both directions

Over half change status annually

Source: Scott, Dennis, & Foss (2005)

16


Predictors of Change Also Vary by Direction

In the Community

Using (53% stable)


28%

29%

Probability of Sustaining Abstinence - times in treatment (0.83) + Female (1.72)- homelessness (0.61) + ASI legal composite (1.19)- number of arrests (0.89) + # of sober friend (1.22)

+ per 77 self help sessions (1.82)

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)

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The Likelihood of Sustaining Abstinence Another Year Grows Over Time

36%

66%

86%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 to 12 months 1 to 3 years 4 to 7 years

Duration of Abstinence

% S

usta

inin

g A

bsti

nenc

eA

noth

er Y

ear

.

After 1 to 3 years of abstinence, 2/3rds will make it another year

After 4 years of abstinence, about 86% will make it

another year

Source: Dennis, Foss & Scott (2007)

Only a third of people with

1 to 12 months of abstinence will

sustain it another year

But even after 7 years of abstinence, about

14% relapse each year

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Source: Dennis, Foss & Scott (2007)

What does recovery look like on average?

Duration of Abstinence1-12 Months 1-3 Years 4-7 Years

• More social and spiritual support• Better mental health • Housing and living situations continue to improve • Dramatic rise in employment and income • Dramatic drop in people living below the poverty line

• Virtual elimination of illegal activity and illegal income • Better housing and living situations • Increasing employment and income

• More clean and sober friends• Less illegal activity and incarceration • Less homelessness, violence and victimization • Less use by others at home, work, and by social peers

19

Sustained Abstinence Also ReducesThe Risk of Death

Source: Scott, Dennis, Simeone & Funk (forthcoming)

-

Users/Early Abstainers more likely

to die in the next 12

months

The Risk of Death goes down with

years of sustained abstinence

It takes 4 or more years of abstinence for

risk to get down to

community levels

(Matched on Gender, Race & Age)

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Other factors related to death rates

• Death is more likely for those who – Are older– Are engaged in illegal activity– Have chronic health conditions– Spend a lot of time in hospitals– Spend a lot of time in and out of substance abuse

treatment

• Death is less common for those who – Have a greater percent of time abstinent– Have longer periods of continuous abstinence– Get back to treatment sooner after relapse

21

False Negative Rates of Self-Reported Past Week Use vs. Urine by Feedback Condition

0%

5%

10%

15%

20%

25%

30%

35%

Any Drug Cocaine Opioids Cannabis

% F

alse

Neg

ativ

e

No Feedback Control (n=207)

Historical & Urine Feedback (n=201)

* Bars connected by a line are not significantly different from each other.


Historical Feedback Only (n=191)

Urine Feedback Only (n=160)

22

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.

• “Recovery” is broader than abstinence and often takes several years after initial abstinence

23

The Early Re-Intervention (ERI) Experiments (Dennis & Scott)

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

Dennis & Scott (in press); Scott & Dennis, (under review)

Funding Source NIDA grant R37-DA11323

24

Sample Characteristics of ERI-1 & -2 Experiments

0% 20%

40%

60%

80%

100%

African American

Age 30-49

Female

Current CJ Involved

Past Year Dependence

Prior Treatment

Residential Treatment

Other Mental Disorders

Homeless

Physical Health Problems

ERI 1 (n=448)

ERI 2 (n=446)

Source: Dennis, Scott & Funk, 2003; Scott & Dennis (under review)

25

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

26

Impact of On-site Urine On False Negative Urines

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

Opiates Marijuana Cocaine Any Drug Tested

ERI 1 ERI 2

At 24 months FN were at

19% for any drug

Introducing the new

protocol in ERI 2

dropped the 24 month FN

rate to 3%

Source: Scott & Dennis (2009)

27

RMC Protocol Adherence Rate by ExperimentRMC Protocol Adherence Rate by Experiment

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Follow-up Interview(93 vs. 96%)

d=0.18

TreatmentNeed

(30 vs. 44%)d=0.31*

Linkage Attendance(75 vs. 99%)

d=1.45*

Agreed to Assessment

(44 vs. 45%)d=0.02

Showed to Assessment

(30 vs. 42%)d=0.26*

Showed to Treatment(25 vs. 30%)

d=0.18*

Treatment Engagement

(39 vs. 58%)

d=0.43*

Range of rates by quarter * P(H: RMC1=RMC2)<.05<-Average->ERI-1 ERI-2

ERI 2 Generally averaged as well or better than ERI 1

ImprovedScreening

Improved Tx

Engagement

Quality assurance and transportation assistance reduced the variance


28

ERI-1 Time to Treatment Re-Entry

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 90 180

270 360

450

540

630

Days to Re-Admission (from 3 month interview)

Percent Readmitted 1+ Times

60% ERI-1 RMC* (n=221)

51% ERI-1 OM (n=224)

*Cohen's d=+0.22 Wilcoxon-Gehen

Statistic (df=1)=5.15, p <.05

630-403 = -200 days

Revisions to the protocol

Source: Dennis, Scott & Funk, 2003; Scott & Dennis (2009)

29

ERI-2 Time to Treatment Re-Entry

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0% 0 90 18

0270 36

0450

540

630

Days to Re-Admission (from 3 month interview)

Percent Readmitted 1+ Times

55% ERI-2 RMC* (n=221)

37% ERI-2 OM (n=224)

*Cohen's d=+0.41 Wilcoxon-Gehen

Statistic (df=1)=16.56, p <.0001

630-246 = -384 days

The size of the effect is growing every quarter


30

ERI-1: Impact on Outcomes

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

of 630 DaysAbstinent (d=0.04)

of 7 SubsequentQuarters in Need

(d= -0.19) *

of 90 DaysAbstinent(d= -0.05)

of 11 Sx ofAbuse/Dependence

(d=-0.02)

Still in need of Tx

(d= -0.21) *

Per

cent

age

OM RMC

* p<.05

79%

33%

80%

21%

44%

79%

27%

79%

21%

34%

RMC Broke the

RunLess Likely to be in Need of Treatment

Months 4-24 Final Interview

No effect on Abstinence/Symptoms

Source: Dennis, Scott, & Funk, 2003; Scott & Dennis (2009)

31

ERI-2: Impact on Outcomes at 45 Months

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Re-enteredTreatment(d=0.22)*

of 14 SubsequentQuarters in Need

(d= 0.26) *

of 1260 DaysAbstinent(d= 0.26)* (d= -0.32)*

Still in need of Tx at Mon 45 (d= -0.22) *

Per

cent

age

OM RMC

* p<.05

55%

41%

67%

50%

56%

38%

Fewer Seq.Quartersin Need

74%

More days of

abstinent

of 180 Daysof Treatment

71%

61%

RMC Increased Treatment Participation

RMC Increased Treatment Participation

47%

Less likely to be in

Need at 45m


32

ERI1&2: Impact Treatment Re-entry by Comorbidity and condition*

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Per

cent

age

OM RMC

* p<.05

47%

53%

33%

Returning to treatment varied

by Comorbidity*

RMC’s Impact on Treatment Participation

was robust across levels of Comorbidity

Source: Rush, Dennis, Scott, Castel, & Funk (2008)

Substance UseDisorder (SUD)

(d=0.23)

Substance Use + Internalizing +Externalizing

Disorders(d=0.31)

Substance Use + Internalizing

Disorders (d=0.38)

62%63%

49%

33

In the Community

Using (71% stable)




3%

18%

8%

15%

9%

16%

27%

4%

33%5%

17%

2%

ERI 1: Impact on Primary Quarterly Pathways to Recovery over 2 years

32% Changed Status in an

Average Quarter

Again the Probability of

Entering Recovery is Higher from

Treatment

Source: Scott et al 2005, Dennis & Scott, 2007

34

18%

In the Community

Using (71% stable)


8%

In Recovery(76% stable)

Source: Scott et al 2005, Dennis & Scott, 2007

ERI 1: Impact on Primary Quarterly Pathways to Recovery over 2 years

Transition to Tx vs. Continued Use- Freq. of Use (0.7)+ Prob. Orient. (1.4)+ Desire for Help (1.6)+ RMC (3.22)

Transition to Recovery vs Continued Use - Freq. of Use (0.7) + Prob. Orient. (1.3)

- Dep/Abs Prob (0.7) + Self Efficacy (1.2) - Recovery Env. (0.8) + Self Help Hist (1.2)

- Access Barriers (0.8) + per 10 wks Tx (1.2)

8%

35

In the Community

Using (75% stable)




4%

10%

10%

23%

8%

13%

35%

7%

25%6%

24%

3%

ERI 2: Average Quarterly Transitions over 3 years

34% Changed Status in an

Average Quarter

Again the Probability of

Entering Recovery is Higher from

Treatment

Source: Riley, Scott & Dennis, 2008

36

In the Community

Using (75% stable)



10% 35% 25%

Source: Riley, Scott & Dennis, 2008

ERI 2: Average Quarterly Transitions over 3 years

Transition to Tx (vs use)- Tx Resistance (0.93) + Freq. of Use (25.30)+ Desire for Help (1.23)+ Wks of Self Help (1.51)+ Self Help Act. (1.37)+ Prior Wks of Tx (1.07)+ RMC (2.08)

Transition Tx to Recovery (vs. relapse) - Freq. of Use (0.01) + Self Help Act. (1.31) - Tx Resistance (0.79) + Wks Self Help (1.39)

37

Positive Consequences of Early ReAdmission

• Checkups and Early Readmission to Treatment were associated with: – Less substance use and problems– Shorter periods of time using in the community– More days of abstinence– Longer periods of abstinence– More attendance and engagement in self help

activities• Above were associated with:

– Fewer HIV risk behaviours– Less illegal activity, arrests, and time incarcerated– Fewer mental health problems– Less health care utilization– Less costs to society


38

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 identification, showing to treatment, and engagement for at least 14 days upon readmission helped to improve outcomes

• ERI 2 also demonstrated the value of on-site proactive urine testing versus the traditional practice of sending off urine for post interview testing

39

Source: French et al., 2008; Chandler et al., 2009; Capriccioso, 2004

Cost of Substance Abuse Treatment Episode

$407

$1,249$1,132$1,384$2,486$2,907

$4,277$14,818

$0

$1

0,0

00

$2

0,0

00

$3

0,0

00

$4

0,0

00

$5

0,0

00

$6

0,0

00

$7

0,0

00

Screening & Brief Inter.(1-2 days)In-prison Therap. Com. (28 weeks)

Outpatient (18 weeks)Intensive Outpatient (12 weeks)

Treatment Drug Court (46 weeks)Residential (13 weeks)

Methadone Maintenance (87 weeks)Therapeutic Community (33 weeks)

$22,000 / year to incarcerate

an adult

$30,000/ child-year in foster care

$70,000/year to keep a child in

detention

• $750 per night in Detox• $1,115 per night in hospital • $13,000 per week in intensive care for premature baby• $27,000 per robbery• $67,000 per assault

40

Investing in Treatment has a Positive Annual Return on Investment (ROI)

• Substance abuse treatment has been shown to have a ROI of between $1.28 to $7.26 per dollar invested

• Treatment drug courts have an average ROI of $2.14 to $2.71 per dollar invested

Source: Bhati et al., (2008); Ettner et al., (2006)

41

Summary Points

• Addiction is a chronic condition that can last for decades • Recovery is likely • Identifying and treating addiction early gets people to

recovery faster• Monitoring for relapse and early re-intervention reduces

use and increases abstinence• Getting and staying well from addiction is associated

with:– Improved housing, jobs, income, mental and

physical health– Reductions in HIV risk behaviors, illegal activity,

legal problems, incarceration and death– Reduced costs to society

42

Implications for Health Care Reform

• Financing for addiction care should ideally be modeled after financing for other chronic conditions

• This means being more assertive in finding and getting people into treatment initially

• Expanded treatment capacity to reduce demand

• Improved step down and continuing care

• Better linkage to self help and recovery services

• Several years of post treatment monitoring

• Teaching self management and monitoring

• Assertive early re-intervention when people relapse

43

References• Bhati et al. (2008) To Treat or Not To Treat: Evidence on the Prospects of Expanding Treatment to Drug-Involved Offenders. Washington, DC: Urban Institute.

• Capriccioso, R. (2004). Foster care: No cure for mental illness. Connect for Kids. Accessed on 6/3/09 from http://www.connectforkids.org/node/571

• Chandler, R.K., Fletcher, B.W., Volkow, N.D. (2009). Treating drug abuse and addiction in the criminal justice system: Improving public health and safety. Journal American Medical Association, 301(2), 183-190

• Dennis, M.L., Foss, M.A., & Scott, C.K (2007). An eight-year perspective on the relationship between the duration of abstinence and other aspects of recovery. Evaluation Review, 31(6), 585-612

• Dennis, M. L., Scott, C. K. (2007). Managing Addiction as a Chronic Condition. Addiction Science & Clinical Practice , 4(1), 45-55.

• 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.

• 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.

• Ettner, S.L., Huang, D., Evans, E., Ash, D.R., Hardy, M., Jourabchi, M., & Hser, Y.I. (2006). Benefit Cost in the California Treatment Outcome Project: Does Substance Abuse Treatment Pay for Itself?. Health Services Research, 41(1), 192-213.

• 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.

• French, M.T., Popovici, I., & Tapsell, L. (2008). The economic costs of substance abuse treatment: Updated estimates of cost bands for program assessment and reimbursement. Journal of Substance Abuse Treatment, 35, 462-469

• Neumark, Y.D., Van Etten, M.L., & Anthony, J.C. (2000). Drug dependence and death: Survival analysis of theBaltimore ECA sample from 1981 to 1995. Substance Use and Misuse, 35, 313-327.

• 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)

• Office of Applied Studies (2006). Results from the 2005 National Survey on Drug Use and Health: National Findings Rockville, MD: Substance Abuse and Mental Health Services Administration. http://www.oas.samhsa.gov/NSDUH/2k5NSDUH/2k5results.htm#7.3.1

http://www.connectforkids.org/node/571

http://www.drugabusestatistics.samhsa.gov/

http://www.drugabusestatistics.samhsa.gov/

http://webapp.icpsr.umich.edu/cocoon/ICPSR-SERIES/00064.xml

http://www.oas.samhsa.gov/NSDUH/2k5NSDUH/2k5results.htm#7.3.1

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References• Riley, B.B.,, Scott, C.K, & Dennis, M.L. (2008). The effect of recovery management checkups on transitions from substance use to

substance abuse treatment and from treatment to recovery. Poster presented at the UCLA Center for Advancing Longitudinal Drug Abuse Research Annual Conference, August 13-15, 2008, Los Angles, CA. www.caldar.org .

• Rush, B., Dennis, M.L., Scott, C.K, Castel, S., & Funk, R.R. (2008). The Interaction of Co-Occurring Mental Disorders and Recovery Management Checkusp on Treatment Participation and Recovery.

• Scott, C. K., & Dennis, M. L. (in press). Results from Two Randomized Clinical Trials evaluating the impact of Quarterly Recovery Management Checkups with Adult Chronic Substance Users. Addiction.

• Scott, C. K., Dennis, M. L., & Funk, R.R. (2008). Predicting the relative risk of death over 9 years based on treatment completion and duration of abstinence . Poster 119 at the College of Problems on Drug Dependence (CPDD) Annual Meeting, San Juan, PR, June 16, 2008. Available at www.chestnut.org/li/posters .

• Scott, C. K., Dennis, M. L., Simeone, R., & Funk R. (forthcoming). Predicting the likelihood of death of substance users over 9 years based on baseline risk, treatment and duration of abstinence. Chicago, IL: Chestnut Health Systems.

• 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.

• Volkow N.D., Fowler J.S., Wang G-J., Hitzemann R., Logan J., Schlyer D., Dewey 5., Wolf A.P. (1993). Decreased dopamine D2 receptor availability is associated with reduced frontal metabolism in cocaine abusers. Synapse 14:169-177.

• Volkow, N.D., Hitzemann R., Wang C-I., Fowler I.S., Wolf A.P., Dewey S.L. (1992). Long-term frontal brain metabolic changes in cocaine abusers. Synapse 11:184-190.

http://www.caldar.org/

1 findings from the pathways to recovery and recovery management checkups (rmc) experiments michael...

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