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Prescription Drug Abuse: Prevalence and Prevention. Robert Pack, PhD, MPH Community Medicine. Outline . Overview Prevalence Prevention What NIDA says Other thoughts Our own research study on predictors Discussion. “Sam” . Close friend Charming, funny, fit, good looking

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prescription drug abuse prevalence and prevention

Prescription Drug Abuse: Prevalence and Prevention

Robert Pack, PhD, MPH

Community Medicine

outline
Outline
  • Overview
  • Prevalence
  • Prevention
    • What NIDA says
    • Other thoughts
    • Our own research study on predictors
  • Discussion
slide3
“Sam”
  • Close friend
  • Charming, funny, fit, good looking
  • In 2004: married father of two; BS in horticulture; worked as a pharmacy tech (10 hrs a week)
  • Addicted for 12 years; starting with Xanax & Soma
sam s addiction
Sam’s addiction
  • Carefully regimented sequence
    • Ate set amounts of food at set times
    • Certain drugs before food and after
  • Slept three hours a night
  • Up to 40-50 Lorcet 10/325’s a day
  • 4 Xanax 2 mg (plus a valium 10, an ativan 2mg and a Clonipin 1mg) and 40-60 Soma (Carisoprodol) at set times during the day; plus all manner of other stuff
  • OD’d twice but was not hospitalized; friends took care of him
  • Day job: prescription drug seeker and a stay-at-home dad to his young daughter
sam the dealer
Sam the dealer
  • Sold Ambien and Xanax to neighborhood housewives
  • Sold Adderall to students and young professionals
  • Sold Vicodin and Lortab to everyone
  • 40-50,000 pills in his garage (on the floor, in tupperware)
  • Half dozen pistols (on the floor, in tupperware)
  • $50,000 in cash (on the floor in a small toy safe)
  • Cameras on every corner of the house that fed into a central security system in the garage (command and control)
  • Attack dogs in the backyard
  • The wrong people were starting to know who he was
  • Claims to have never stolen from the pharmacy
sam s wife
Sam’s wife
  • Caught him once in 2000 and threatened divorce if it happened again
    • Forced counselor visits
  • Stayed away from the command center in the garage “because of the mice”
  • “Naïve” until…
    • Sam fell asleep at dinner and would not wake up
  • More about Sam later….
nhsduh
NHSDUH
  • Household computerized (ACASI) survey of incidence and prevalence of non-medical use of licit drugs and use of illicit drugs
  • Licit (i.e., psychotherapeutic, mind-altering) drugs
    • Pain relievers (opioids)
    • Tranquilizers (barbiturates)
    • Stimulants (amphetamines)
    • Sedatives (benzodiazepines)
  • •Illicit drugs
    • Such as marijuana or hashish, Cocaine, Heroin etc.

SOURCE: Zacny (2004). Trends in abuse of prescription drugs.

http://www.painandchemicaldependency.org

prescription opioids ranked on non medical lifetime use
Prescription Opioids Ranked on Non-Medical Lifetime Use
  • 1,2. Darvon, Darvocet, or Tylenol with Codeine: 19 million people
  • 3. Vicodin, Lorcet, or Lortab: 13 million people
  • 4. Percocet, Percodan, or Tylox: 9.5 million people
  • 5. Demerol: 3 million people
  • 6. Morphine: 2 million people
  • 7. OxyContin: 2 million people
  • 8. Dilaudid: 1 million people

SOURCE: Zacny (2004). Trends in abuse of prescription drugs.

http://www.painandchemicaldependency.org

slide10

More than 6.3 Million Americans Reported Current Use

of Prescription Drugs for Nonmedical Purposes in 2003

dependence nsduh data
Dependence: NSDUH data
  • About 259,000 people are dependent on prescription stimulants
  • About 900,000 people in the US are dependent on opioids
  • About 1,100,000 – cocaine
  • About 8,000,000 – marijuana
  • About 70,000,000 – tobacco
slide12

Annual Numbers of New Nonmedical Users of

Psychotherapeutics: 1965–2001

SOURCE: http://www.oas.samhsa.gov/nhsda/

slide13

Dependence or Abuse of Specific Substances among

Past Year Users of Substances: 2002

SOURCE: http://www.oas.samhsa.gov/nhsda/

slide14

Substances for Which Persons Aged 12 or Older Received

Treatment in the Past Year: 2002

SOURCE: http://www.oas.samhsa.gov/nhsda/

slide15

Past Month Use of Selected Illicit Drugs among Persons Aged

12 or Older: 2002

SOURCE: http://www.oas.samhsa.gov/nhsda/

slide17

Percent of Students Reporting

Past Month Use of Any Illicit Drug

Has Decreased

*

17% Decline 2001 to 2004

Percent

*

P < .05

slide18

Issues of Concern

Percent of 12th Graders Reporting

Nonmedical Use of OxyContin and Vicodin

in the Past Year Remained High

12.0

10.5

9.6

9.3

10.0

8.0

Percent

6.0

5.0

4.5

4.0

4.0

2.0

0.0

OxyContin

Vicodin

2002

2003

2004

No year-to-year differences are statistically significant.

slide19

Past Month Use of Selected Illicit

Drugs Among Youths, by Age: 2003

nida estimates
NIDA estimates
  • Annual abuse of Vicodin was 9.5 percent among 12th-graders in 2005, ranking it among the most commonly abused drugs for 12th-graders in the “annual use” category.
  • From 2002 to 2005, annual prevalence of OxyContin use significantly increased among 12th-graders.
    • Likely due to increased availability during that time
  • Since 2001, there has been a 25 percent increase in annual abuse of sedatives/barbiturates among 12th-graders
2003 monitoring the future
2003 Monitoring the Future
  • Among twelfth graders in the US, annual prevalence of Vicodin use was second only to marijuana use.
  • Young people frequently mix prescription drugs with other drugs of abuse, such as marijuana and alcohol, putting them at risk for drug interactions and overdose.
  • Prescription of methylphenidate and other stimulants to treat attention-deficit hyperactivity disorder (ADHD) has also increased in recent years.
the situation in wv
The situation in WV?
  • No denominator based epidemiologic studies
  • Anecdotes abound in the press in local lore
data based wv indicators
Data-based WV indicators
  • According to West Virginia’s Department of Health and Human Resources (DHHR 2003), in 2000, pharmaceutical-related treatment admissions were more common than admissions for any other drug except for marijuana.
  • The DHHR also reports that West Virginia’s problem is growing over time with the number of prescription treatment admissions increasing by approximately 42 percent between 1998 and 2003 (DHHR 2003).
data based wv indicators24
Data-based WV indicators
  • Specific characteristics in West Virginia.
    • Nationally, only 2.8% of admissions were for treatment of dependence on opiate-like drugs, but in West Virginia they accounted for 12.2% of admissions.
    • Also, on average, West Virginia admissions are younger and more likely to be white and female (SAMHSA 2004).
data based wv indicators25
Data-based WV indicators
  • In terms of crime, in 2002, West Virginia had more arrests for prescription-based opiates than for cocaine (Turley and Hutzel 2003).
  • About half (49.2%) of these arrests were for sales and distribution (more than cocaine, methamphetamine, or marijuana)
gender differences
Gender differences
  • Women are up to 48% more likely to be prescribed an abusable prescription drug
  • However, men and women are about equally likely to abuse
    • Except in 12-17 year olds
      • Females are more likely than males to abuse psychotherapeutic drugs
  • Men and women are also equally likely to become addicted

NIDA Research Report, (2005) Prescription Drugs Abuse and Addiction

college students stimulants
College students & stimulants
  • Cross sectional study of 10,904 college students – across the nation
  • Lifetime prevalence of non-medical prescription stimulant abuse was 6.9%
    • Past year prevalence was 4.1%
    • Past month was 2.1%
  • Predictors:
    • Male, white, Greek affiliated, and lower GPA

Esteban McCabe, Knight, et al ; 2005. Addiction, 99, 96-106.

college students pain meds
College students & pain meds
  • Cross-sectional web-based survey of 9161 college students at one university in the midwest US
    • Men: lifetime: 17.4%; past year: 10.1%
    • Women: lifetime: 15.7%; past year: 8.7%
  • Predictors: previously prescribed pain meds, living in a house or apt., lower GPA

Esteban McCabe, Teter & Boyd (2004) Drug & Alcohol Depend. 77, 37-47.

pda youth in europe
PDA & Youth in Europe
  • Cross-sectional survey of 3,021 youth (12-24 yrs) in Europe
  • Lifetime prevalence of illicit use of PD was 4.5%
  • Young women have higher rates of use
  • Young men have higher rates of abuse

Lieb, Pfister, et al (1998), Eur Addict Res 4, 67-74.

opioids as gateway
Opioids as gateway?
  • Qualitative study of 10 heroin detox pts
  • Oxycontin abuse was linked to experimentation and use of heroin
  • Half of the ten addicts reported abusing prescription opioids, most notably Oxycontin, before initiating heroin use.
  • Most reported that heroin was more readily available and less expensive than Oxycontin and that they would never have tried heroin had they not become addicted to opioids
  • Severe limitations to this study
  • Useful for discussion only

Siegal, et al (2003) American Family Physician 67(5): p. 939

risk perception

Risk perception

Inverse correlation between risk perception and use of illicit substances by youth

youth risk perception for prescription drugs
Youth: Risk Perception for Prescription Drugs
  • Two in five teens (40 percent or 9.4 million) agree that Rx medicines, even if they are not prescribed by a doctor, are “much safer” to use than illegal drugs;
  • Nearly one-third of teens (31 percent or 7.3 million) believe there’s “nothing wrong” with using Rx medicines without a prescription “once in a while;”
  • Nearly three out of 10 teens (29 percent or 6.8 million) believe prescription pain relievers – even if not prescribed by a doctor – are not addictive; and
  • More than half of teens (55 percent or 13 million) don’t agree strongly that using cough medicines to get high is risky.
      • Source: Partnership for a Drug Free America
methods
Methods
  • Identified 30 self-identified prescription drug addicted inpatients at CRH
    • Primary DOC were prescription drugs
    • Nominated by CRH staff
  • Informed consent
  • Took about 9 months in 2004
  • Interviewed with a tape recorder
  • Semi-structured interview
methods cont
Methods (cont.)
  • Transcribed the interviews
  • Coded the transcriptions using a preliminary coding dictionary
  • Modified the dictionary over time
  • Came up with a preliminary model to test in a quantitative study
domains
Domains
  • Physical
  • Cognitive
  • Social
  • Behavioral
physical
Physical
  • Back Pain (Rx)
  • Other Pain (Rx)
  • Accidents (orthopedic injury) (Rx)
  • Headaches
  • Cramping (Rx)
  • Surgeries (Rx)
  • Other forms of illness
  • Other drug craving/addiction
  • Self medication (pill addiction)
    • Something is wrong with me
cognitive
Depression (Rx)

Boredom

Curiosity

Self-loathing

Self-esteem (lack of)

Anxiety (Rx)

Loss and avoidance of

responsibilities

Fear of stepping into life

Entitlement

Fear of Discomfort

Self-Control

Thinking about using drugs

When things get bad

Self-efficacy

Cognitive
social
Peer Influence:

Friends trying to influence you

Your influence on others

Accessibility:

Street

Docs:

Unwitting

Resigned to the fact

“Candyman"

Family:

Childhood environment

Present family life

Education

Pharmacy:

Community

Chain

Community acceptance of problem

Legitimacy rationalization b/c of Rx

Friends

Trade, i.e. sex, money, for drugs

Social compensation for staying sick

Hidden/invisible network

Observational Learning

Social
behavior
Reinforcers:

Really high - a search for a better high

Numbness

Peer acceptance

Maintaining baseline - more consistent high

Clean high

Nurturing by others

Consequences:

Loss of control

Divorce

Job loss

Relationship destruction

Doctor shopping

Full-time occupation

Networking

Withdrawal

Side effects

Behavior
plans for the data
Plans for the data
  • Quantitative study
  • Test prevalence in community
  • Develop prevention programming
present study
Present Study
  • Prevention programming
    • Aimed at 6th grade youth in school
      • Mentored by Health Sciences and Technology Academy (HSTA) youth from the high schools
    • Pre-post design
  • Community focused
  • Parent training
  • Local media and community-supported
          • Funded by WV State Oxycontin settlement dollars
nurses physicians dentists
Nurses, Physicians & Dentists
  • Adequate and appropriate prescription
  • Early detection of abuse
    • Aid in the patient recognizing the problem
  • History & physical screen for substance abuse history
  • Careful notation of increases in quantity
pharmacists
Pharmacists
  • Detection of prescription fraud or diversion by looking for falsified or altered forms
  • Hotlines to other pharmacies
    • Driving is common for addicts
    • Five-state area within two hours of here
  • Electronic systems
sam again61
Sam again:

After the OD his wife convinced him to go to treatment

She filed for divorce while he was in detox (1 wk)

In November Sam fell off his ex-wife’s roof (cleaning the gutters) and shattered his leg

Walks with a cane

Still on some meds for anxiety and pain

finally
Finally
  • CTN-0030: A Two-Phase Randomized Controlled Clinical Trial of Buprenorphine/Naloxone Treatment Plus Individual Drug Counseling for Opioid Analgesic Dependence
  • Enrolling patients now
  • Conducted at Chestnut Ridge Hospital in conjunction with Harvard Medical School
  • If you have patients that meet specific eligibility criteria, contact:
    • James Lyndon McCracken, MA Research and Protocol Manager Department of Behavioral Medicine and Psychiatry WVU School of Medicine Morgantown, WV 26505 Tel: 304-293-5288 Fax: 304-293-8724 [email protected]
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