Preventing Prescription Opioid Overdoses:
Changing patients’ risky opioid use behavior.
Amy Bohnert, PhD
Disclosures
• Affiliations
– University of Michigan
– VA Center for Clinical Management Research
• Funding
– NIH (NIDA)
– ...
Colleagues
• Mark Ilgen
• Fred Blow
• Matt Bair
• Erin Bonar
• Steve Chermack
• Rebecca Cunningham
• Mark Greenwald
• Kris...
A behavioral intervention to
reduce overdose risk behaviors
Support: CDC R49 CE002099
Objective
• To describe a pilot randomized controlled
trial of a brief intervention (BI) to address
overdose risk in Emerg...
Rationale
Why the Emergency Department?
• 1/3 of patients in the ED get an opioid
• Non-medical use of opioids common
• Se...
Rationale (con’t)
Why a Behavioral Intervention?
• Existing data on brief motivational
interventions for substance use
• N...
Setting
• Location: University of Michigan Emergency Department (ED)
Protocol
• Research staff approached patients while waiting for care once in
private rooms
• Consent and screen via comput...
Eligibility Criteria
• Past 3 month prescription opioid misuse
• Positive screen on 8 items of Current Opioid Misuse
Measu...
Intervention
• Brief Motivational Enhancement (ME)
Interventions
– Non-judgmental, empathetic
– Focused on increasing self...
Intervention Delivery
 Master’s level trained therapists
 Computer aid to enhance fidelity
and provide prompts as needed...
Intervention Content Outline
 EXPLORE
• Introduction and Agenda Setting
• Personal Strengths and Values
• Goals
• Review ...
Witnessing Overdoses
Purpose: provide psychoeducation about responding to someone else’s overdose
Therapist Strategies: Ac...
Responding to Overdoses
 Check for consciousness/pulse
 Call 911 or take them to the ER
 Roll the person on their side ...
What are your concerns about what might happen to you if you were to
witness an overdose?
Health
• I could be or become de...
Sample Demographics
• N=204 completed baseline and
randomized, 177 (87%) followed at 6
months
• 64% female
• Age: mean 37 ...
Opioid Use and Pain in the Sample
• 75% had an overdose/serious drug event history
• 56% had a chronic pain diagnosis
• 69...
Examining Outcomes: regression models based on
outcome measure distribution
• Independent Variable of interest a group ind...
Outcomes
6 Month Outcomes:
Overdose Risk Behavior
Overdose Risk Behavior Items
1. How often have you used opioid pain medications w...
Poisson regression
• The intervention group had lower ORB scores at 6 months
compared to EUC.
• The percent decrease in av...
Secondary Outcome: Non-Medical
Opioid Use
Current Opioid Misuse Measure Items
1. How often have you had to go to someone o...
Poisson regression
• Lower levels of non-medical opioid use over the six months of
follow-up in Intervention compared to E...
Conclusions
• BI is feasible and highly acceptable to
patients who are at risk for overdose.
• Positive findings for behav...
• Not a definitive trials – not powered to detect clinical
outcomes, relatively small sample size
• Not possible to valida...
• Challenges to proposed chain-referral/snowball
sampling
• Challenges to assess some important risk behaviors like
total ...
• Trials in other settings
• NIDA R34 – Three session intervention for overdose and HIV risk
behaviors during residential ...
• Full-scale trial to measure health outcomes
• mHealth strategies to increase dissemination potential
• Combining with na...
Amy Bohnert
amybohne@med.umich.edu
Comments and Unanswered
Questions?
Supplementary Slides
Detailed Sample Description
Characteristic
Overall
n=204
Intervention
n=102
EUC only
n=102
p-value a
Mean (SD) Mean (SD) M...
Key Element Description Therapist Goals and MI Strategies
EXPLORE
Introduction: Agenda
Setting
 Thank for participation
...
All Models
Primary Outcomes
Model 1: Overdose Risk Behaviors, n=172
IRR SE 95% CI
Intervention Group vs. EUC only 0.72 0.0...
Response options were on a scale of 1 (“Not Likely”) to 10 “Very Likely”). Sum score range 3-30.
Outcome 2 – Behavioral In...
Poisson regression
• No difference between groups.
• Note: higher levels indicate less intention to reduce overdose risk.
...
Outcome 3 - Knowledge
Overdose Knowledge d
Risk Factors: For each item, please check “Yes” for the items that you believe ...
Poisson and Linear Regression models
• No difference between groups.
• Note: overdose risk knowledge reverse coded.
Analys...
Preventing Prescription Opioid Overdoses: Changing Patients' Risky Opioid Use Behavior by Amy Bohnert, PhD
Preventing Prescription Opioid Overdoses: Changing Patients' Risky Opioid Use Behavior by Amy Bohnert, PhD
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Preventing Prescription Opioid Overdoses: Changing Patients' Risky Opioid Use Behavior by Amy Bohnert, PhD

Presentation delivered at the University of Michigan Injury Center Opioid Overdose Summit, Ann Arbor, MI, December 1, 2015
Published on: Mar 4, 2016
Published in: Health & Medicine      
Source: www.slideshare.net


Transcripts - Preventing Prescription Opioid Overdoses: Changing Patients' Risky Opioid Use Behavior by Amy Bohnert, PhD

  • 1. Preventing Prescription Opioid Overdoses: Changing patients’ risky opioid use behavior. Amy Bohnert, PhD
  • 2. Disclosures • Affiliations – University of Michigan – VA Center for Clinical Management Research • Funding – NIH (NIDA) – CDC (UM Injury Research Center) – VA (HSR&D, QUERI) • Conflicts of Interest – None to report
  • 3. Colleagues • Mark Ilgen • Fred Blow • Matt Bair • Erin Bonar • Steve Chermack • Rebecca Cunningham • Mark Greenwald • Kris Haenchen • Maureen Walton Project Staff • Carrie Bourque • Anna Eisenberg • Mary Jannausch • Lynn Massey • Phil Nulph • Laura Thomas • Jing Wang • Emily Yeagley • Lisa Zbizek-Nulph Acknowledgements
  • 4. A behavioral intervention to reduce overdose risk behaviors Support: CDC R49 CE002099
  • 5. Objective • To describe a pilot randomized controlled trial of a brief intervention (BI) to address overdose risk in Emergency Department (ED) patients.
  • 6. Rationale Why the Emergency Department? • 1/3 of patients in the ED get an opioid • Non-medical use of opioids common • Setting of acute treatment for overdoses
  • 7. Rationale (con’t) Why a Behavioral Intervention? • Existing data on brief motivational interventions for substance use • Not all overdose risk well-suited to naloxone as a prevention approach; maximizing potential of conversation accompanying naloxone dispensing • Potentially low cost
  • 8. Setting • Location: University of Michigan Emergency Department (ED)
  • 9. Protocol • Research staff approached patients while waiting for care once in private rooms • Consent and screen via computer tablet (Part 1) • Those eligible recruited and consented for a baseline survey via computer tablet (Part 2) • Computer randomized to intervention or enhanced usual care
  • 10. Eligibility Criteria • Past 3 month prescription opioid misuse • Positive screen on 8 items of Current Opioid Misuse Measure (COMM) • Age 18-60 • Able to provide informed consent • English speaking • Oversampled individuals with prior overdose • Exclusion criteria: being treated for suicidality or sexual assault, active psychosis, medically unstable, altered mental status, unable to give contact information for follow-up
  • 11. Intervention • Brief Motivational Enhancement (ME) Interventions – Non-judgmental, empathetic – Focused on increasing self-efficacy, setting goals, overcoming barriers to change • Behavioral targets 1. Reducing risky overdose-related behaviors and opioid misuse 2. Improve response when witnessing an overdose 3. Outreach to at-risk friends
  • 12. Intervention Delivery  Master’s level trained therapists  Computer aid to enhance fidelity and provide prompts as needed  Enhanced Usual Care: pamphlets
  • 13. Intervention Content Outline  EXPLORE • Introduction and Agenda Setting • Personal Strengths and Values • Goals • Review Behavioral History • Review Overdose History • Review Witnessed Overdoses  GUIDE • Benefits to Changing  CHOOSE • Strategies to Handle Risky Situations • Selecting Change Goals • Tools • Strategic Summary
  • 14. Witnessing Overdoses Purpose: provide psychoeducation about responding to someone else’s overdose Therapist Strategies: Active listening (perception of use), open-ended questions, normalize fears/concerns about responding 1. Review history of witnessing overdoses 2. Elicit participant knowledge of how to respond to an overdose • “What have you heard/seen about responding to an overdose?” • “What concerns would you have about responding?” 3. Provide information of overdose responses as needed Key factors: checking for consciousness, calling 911, placing in recovery position/on side, CPR if possible 4. Elicit participant’s response to new information 5. Review concerns about witnessed overdoses (for people I care about, for myself if I responded) NEXT: Responding, Concerns about Overdosing Prompt
  • 15. Responding to Overdoses  Check for consciousness/pulse  Call 911 or take them to the ER  Roll the person on their side (recovery position) to prevent choking if they vomit  If you know CPR, do it  Cause pain safely to try to wake them up  Sternum Rub  Naloxone
  • 16. What are your concerns about what might happen to you if you were to witness an overdose? Health • I could be or become depressed • I would have contact with others Work, School, or Financial • Legal problems for me, getting into trouble • May need to help them with finances Family and Friends • Could lose someone I care about Other • Please specify: • Please specify: Health • They could feel really bad for a couple of days • They could be or become depressed • They could die • They could have long-lasting health effects from an overdose Work, School, or Financial • They could have legal problems • They could lose housing Family and Friends • They could get angry with me Other • Please specify: • Please specify: What are your concerns about what might happen to your friend or family member if they were to have an overdose?
  • 17. Sample Demographics • N=204 completed baseline and randomized, 177 (87%) followed at 6 months • 64% female • Age: mean 37 (SD=11) • Race: 20% Black, 75% White, 5% Other
  • 18. Opioid Use and Pain in the Sample • 75% had an overdose/serious drug event history • 56% had a chronic pain diagnosis • 69% had been prescribed opioids in the prior 6 months • 48% had moderate or high risk prescription opioid involvement, per ASSIST
  • 19. Examining Outcomes: regression models based on outcome measure distribution • Independent Variable of interest a group indicator (1= intervention, 0=EUC only) • Models adjusted for baseline level of the outcome • Two-sided p < 0.05 Analysis Strategy
  • 20. Outcomes
  • 21. 6 Month Outcomes: Overdose Risk Behavior Overdose Risk Behavior Items 1. How often have you used opioid pain medications when nobody else was around? 2. How often have you used opioid pain medications in a place where you don’t usually use them? 3. How often did you drink alcohol within 2 hours before or after using opioid pain medications? 4. How often did you take sedatives (such as Xanax) within 2 hours before or after using opioid pain medications? 5. How often did you use heroin within 2 hours before or after using opioid pain medications? 6. How often did you use uppers (such as crack, cocaine, crystal/meth) within 2 hours before or after using opioid pain medications? 7. How often have you increased the amount of opioid pain medications you used to more than you usually use? 8. How often have you snorted any drugs? 9. How often have you injected any drugs? Reponses options were “never (0),” “rarely (1),” “sometimes (2),” “often (3),” and “very often (4),” except for #6, which was “never (0),” “once (1),” or “more than once (2).” Sum score range: 0-32.
  • 22. Poisson regression • The intervention group had lower ORB scores at 6 months compared to EUC. • The percent decrease in average overdose risk behavior frequency was 40.5% in intervention participants and 14.7% in EUC only participants. Analysis of the Overdose Risk Behavior outcome Model 1: Overdose Risk Behaviors, n=172 IRR SE 95% CI Intervention Group vs. EUC only 0.72 0.07 0.59, 0.87 Baseline Level of Overdose Risk Behaviors 1.07 0.01 1.06, 1.08
  • 23. Secondary Outcome: Non-Medical Opioid Use Current Opioid Misuse Measure Items 1. How often have you had to go to someone other than your prescribing physician to get sufficient pain relief from opioid pain medications? (i.e., another doctor, the Emergency Room, friends, street sources) 2. How often have you taken your opioid pain medications differently from how they are prescribed? 3. How much of your time was spent thinking about opioid pain medications (having enough, taking them, dosing schedule, etc.)? 4. How often have you needed to take opioid pain medications belonging to someone else? 5. How often have you been worried about how you’re handling your opioid pain medications? 6. How often have you had to take more of your opioid pain medication than prescribed? 7. How often have you borrowed opioid pain medication from someone else? 8. How often have you used your opioid pain medicine for symptoms other than for pain (e.g., to help you sleep, improve your mood, or relieve stress)? Response options were “never (0),” “rarely (1),” “sometimes (3),” “often (4),” and “very often (5);” points based on Butler et al. Sum score range: 0-40.
  • 24. Poisson regression • Lower levels of non-medical opioid use over the six months of follow-up in Intervention compared to EUC participants. • Percent decrease in average COMM score was 50.0% in intervention participants and 39.5% in EUC participants. Analysis of the Non-Medical Opioid Use Outcome Model 5: Non-Medical Opioid Use, n=163 IRR SE 95% CI Intervention Group vs. EUC only 0.81 0.06 0.70, 0.92 Baseline Level of Non-Medical Opioid Use 1.04 0.003 1.03, 1.05
  • 25. Conclusions • BI is feasible and highly acceptable to patients who are at risk for overdose. • Positive findings for behavioral outcomes.
  • 26. • Not a definitive trials – not powered to detect clinical outcomes, relatively small sample size • Not possible to validate outcomes with urine drug screens • Does not overcome barriers to staffing in the ED Limitations
  • 27. • Challenges to proposed chain-referral/snowball sampling • Challenges to assess some important risk behaviors like total dose and breaks in use, and for assessment in the absence of well-validated outcomes • Potential for using motivational interviewing for harm reduction messaging Lessons Learned
  • 28. • Trials in other settings • NIDA R34 – Three session intervention for overdose and HIV risk behaviors during residential addictions treatment • VA IIR – Pragmatic trial of brief intervention overlaid on opioid informed consent, compared to equal attention control and delivered by PC-MHI clinicians Next Steps
  • 29. • Full-scale trial to measure health outcomes • mHealth strategies to increase dissemination potential • Combining with naloxone dispensing Next Steps
  • 30. Amy Bohnert amybohne@med.umich.edu Comments and Unanswered Questions?
  • 31. Supplementary Slides
  • 32. Detailed Sample Description Characteristic Overall n=204 Intervention n=102 EUC only n=102 p-value a Mean (SD) Mean (SD) Mean (SD) Age 36.8 (11.1) 37.5 (11.4) 36.1 (10.9) 0.38 n (%) n n Female 130 (64) 61 (60) 69 (68) 0.24 Race: White b 153 (75) 73 (72) 80 (78) 0.26 Black 40 (20) 24 (24) 16 (16) 0.16 Other/Missing 12 (6) 10 (10) 2 (2) 0.03 Education: High School Degree or Less 51 (25) 27 (26) 24 (24) 0.80 Some College 91 (45) 46 (45) 45 (44) Competed College 62 (30) 29 (28) 33 (32) Employment Status: Disabled 75 (37) 40 (39) 35 (35) 0.31 Full- or Part-Time Employment 93 (46) 42 (41) 51 (51) Unemployed 31 (15) 19 (19) 12 (12) Retired 4 (2) 1 (1) 3 (3) Prior Overdose (any) 153 (75) 77 (75) 76 (75) 0.87 Number of past year ED visits: 0 25 (12) 12 (12) 13 (13) 0.06 1-2 76 (37) 32 (31) 44 (43) 3-5 57 (28) 37 (36) 20 (20) 6+ 46 (23) 21 (21) 25 (25) Past 3 Month Substance Use Any Alcohol Use 124 (61) 54 (53) 70 (69) 0.02 Use Frequency: Weekly or Greater 51 (25) 21 (21) 30 (29) 0.15 Any Marijuana Use 77 (38) 39 (38) 38 (37) 0.89 Use Frequency: Weekly or Greater 45 (22) 22 (22) 23 (23) 0.87 Any Cocaine Use 19 (9) 9 (9) 10 (10) 1.00 Use Frequency: Weekly or Greater 9 (4) 4 (4) 5 (5) 1.00 Any Non-Medical Sedative Use 44 (22) 26 (26) 18 (18) 0.17 Use Frequency: Weekly or Greater 18 (9) 9 (9) 9 (9) 1.00 Chronic Pain Diagnosis, Lifetime c 115 (56) 57 (56) 58 (57) 0.89 Prescribed Opioids in Prior 6 Months, Self-Reported 0.13 None 64 (31) 32 (31) 32 (31) For Acute Pain Only 37 (18) 19 (19) 18 (18) For Chronic Pain Only 38 (19) 13 (13) 25 (25) For Acute and Chronic Pain 65 (32) 38 (37) 27 (26) Prescription Opioid Involvement, ASSIST 0.85 Low Risk 106 (52) 51 (50) 55 (54) Moderate Risk 80 (39) 42 (41) 38 (37)
  • 33. Key Element Description Therapist Goals and MI Strategies EXPLORE Introduction: Agenda Setting  Thank for participation  Set agenda and discuss autonomy  Answer client questions  Develop rapport and set plan  Affirm participation Personal Strengths and Values  Identify personal strengths in the domains of health, work, school, financial, family and social connections, and other  Affirm strengths  Remember later for strategic summary and other tools Goals  Identify personal goals in the domains of health, work, school, financial, family and social connections, and other  Establish goals  Active listening, identifying discrepancies, open-ended questions, reflect and affirm goals, summarize Review Behavioral History  Review prescription opioid use frequency and reasons for use, concurrent use of other medications, alcohol use, and other drug use  Identify personal risky opioid use behaviors  Open-ended prompts  Active listening  Role with resistance Review Overdose History  Discuss prior overdose experience(s)  Elicit concerns about overdose in the future for self and others  Identify personal history of overdose  Open-ended prompts  Active listening  Role with resistance  Establish discrepancy between values/goals and behavior Review Witnessed Overdoses  Review history of witnessed overdoses  Elicit participant knowledge of overdose response actions  Provide information as needed  Review concerns about witnessed overdose for self and victim  Open-ended prompts  Active listening  Normalize fears/concerns GUIDE Benefits of Changing  Elicit potential benefits to making changes to opioid use and overdose risk  Eliciting and elaborating change talk, clarify ambivalence  Repeat steps for reducing personal overdose risk and outreach to others  Open-ended prompts  Reflections and affirmations  Confidence and importance rulers CHOOSE Risky Situations  Elicit current strategies to reduce risk  Provide information on additional strategies  Elicit reaction to potential new strategies  Open-ended prompts  Active listening  Roll with resistance  Transition to concerns, impact of use, future use Selecting Change Goals  Select goals for reducing personal overdose risk, response to witnessed overdose, and outreach to others about overdose  Open-ended prompts  Active listening  Reflections and affirmations Tools  Elicit tools to help deal with challenges  Review menu of options for risk reduction  Confidence rulers  Reflections and explore change talk, affirmations  Recall strengths Summary  Address readiness to change  Strategic summary of session  Readiness rulers  Affirmations
  • 34. All Models Primary Outcomes Model 1: Overdose Risk Behaviors, n=172 IRR SE 95% CI Intervention Group vs. EUC only 0.72 0.07 0.59, 0.87 Baseline Level of Overdose Risk Behaviors 1.07 0.01 1.06, 1.08 Model 2: Behavioral Intentions, n=169 IRR SE 95% CI Intervention Group vs. EUC only 0.94 0.05 0.85, 1.04 Baseline Level of Behavioral Intentions 1.04 0.004 1.03, 1.05 Model 3: Overdose Risk Knowledge, n=169 IRR SE 95% CI Intervention Group vs. EUC only 1.19 0.12 0.97, 1.45 Baseline Level of Overdose Risk Knowledge 1.05 0.03 1.01, 1.10 Model 4: Overdose Symptom Knowledge, n=172 B SE 95% CI Intervention Group vs. EUC only 0.10 0.15 -0.20, 0.40 Baseline Level of Overdose Risk Knowledge 0.22 0.08 0.08, 0.37 Secondary Outcome Model 5: Non-Medical Opioid Use, n=163 IRR SE 95% CI Intervention Group vs. EUC only 0.81 0.06 0.70, 0.92 Baseline Level of Non-Medical Opioid Use 1.04 0.003 1.03, 1.05
  • 35. Response options were on a scale of 1 (“Not Likely”) to 10 “Very Likely”). Sum score range 3-30. Outcome 2 – Behavioral Intentions Behavioral Intentions 1. If you receive an opioid prescription, how likely it is that you would use prescription opioids as prescribed by a medical professional? 2. How likely is it that you will reduce or avoid using alcohol, drugs, and/or medications (recreationally)? 3. How likely is it that you will avoid combining alcohol, drugs, and/or medications?
  • 36. Poisson regression • No difference between groups. • Note: higher levels indicate less intention to reduce overdose risk. Analysis of the Behavioral Intentions Outcome Model 2: Behavioral Intentions, n=169 IRR SE 95% CI Intervention Group vs. EUC only 0.94 0.05 0.85, 1.04 Baseline Level of Behavioral Intentions 1.04 0.004 1.03, 1.05
  • 37. Outcome 3 - Knowledge Overdose Knowledge d Risk Factors: For each item, please check “Yes” for the items that you believe can lead to an overdose or “No” if you believe it cannot cause an overdose. (1) Taking more alcohol, drugs, and/or medications than usual (2) Taking less alcohol, drugs, or medications than usual* (3) Having an illness (4) Drug impurities (5) Drugs, alcohol and/or medications stronger than expected (6) Injecting drugs (7) Using drugs at a young age* (8) Combining drugs (9) Combining different medications (10) Drinking alcohol with drugs and/or medications (11) Combining drugs and medications (12) Low tolerance (13) Emotional problems or life difficulties (14) Suicide attempt. Symptoms: For each item below, please check “Yes” for the items that you believe to be a symptom of an overdose or “No” if you believe it is not a symptom of overdose: (1) Shallow breathing (2) Turning blue (3) Bloodshot eyes* (4) Loss of consciousness (5) Deep snoring (6) Pinpoint pupils (7) (7) Blurred vision* * Denotes intentionally incorrect item that was reverse coded for scoring. Sum score range 0-14 for risk factors and 0-7 for symptoms.
  • 38. Poisson and Linear Regression models • No difference between groups. • Note: overdose risk knowledge reverse coded. Analysis of the Knowledge Outcomes Model 3: Overdose Risk Knowledge, n=169 IRR SE 95% CI Intervention Group vs. EUC only 1.19 0.12 0.97, 1.45 Baseline Level of Overdose Risk Knowledge 1.05 0.03 1.01, 1.10 Model 4: Overdose Symptom Knowledge, n=172 B SE 95% CI Intervention Group vs. EUC only 0.10 0.15 -0.20, 0.40 Baseline Level of Overdose Risk Knowledge 0.22 0.08 0.08, 0.37

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