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Receipt of Medication Treatment after Nonfatal Overdose Among Emerging Adults Sarah M. Bagley, MD, MSc Assistant Professor of Medicine and Pediatrics,

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Presentation on theme: "Receipt of Medication Treatment after Nonfatal Overdose Among Emerging Adults Sarah M. Bagley, MD, MSc Assistant Professor of Medicine and Pediatrics,"— Presentation transcript:

1 Receipt of Medication Treatment after Nonfatal Overdose Among Emerging Adults
Sarah M. Bagley, MD, MSc Assistant Professor of Medicine and Pediatrics, BU SOM Director, CATALYST Program, Boston Medical Center AMERSA November 4, 2017

2 Emerging Adults Are Different
Emerging adulthood (18-25 years) is a distinct development stage Characterized by determining autonomy, figuring out self Emerging adults have high rates of alcohol and other drug use Emerging adults respond differently to attempts at treatment than adolescents and older adults

3 Heroin Use Is Significantly Increasing Among Emerging Adults
Jones CM, et al. MMWR Morb Mortal Wkly Rep, 2015;64(26):

4 Fatal Opioid Overdose Also Increasing Among Emerging Adults
Rudd RA, et al. MMWR Morb Mortal Wkly Rep, 2016;64(50-51):

5 How are emerging adults experiencing the opioid overdose epidemic differently than older adults?
Describe characteristics of emerging adults (18-25 years) who experience a nonfatal opioid overdose in MA. Is there variation in receipt of medication treatment after nonfatal overdose based on age? Compare the time to addiction treatment and rates of receipt of treatment between emerging adults and older adults after nonfatal opioid overdose.

6 Methods Design. Retrospective cohort study of emerging adults who had a nonfatal overdose in Massachusetts between Study cohort. Individuals (ages 18-45) who had a nonfatal overdose between Entry was staggered and occurred when an individual had a nonfatal overdose. A nonfatal overdose was identified 2 ways 1) having an ambulance ride related to an overdose or 2) ED or hospital stay related to overdose.

7 Chapter 55 Authority This work was mandated by law, and conducted by a public health authority. All parties conducting and participating in this work did so on behalf of the Commonwealth of Massachusetts and the Massachusetts Department of Public Health.

8 Chapter 55: Phase 2 Data Structure
Chapter 55 Data Structure System Attributes… Linkage at individual level Longitudinal (5 year history) Data encrypted in transit & at rest Limited data sets unlinked at rest Linking and analytics “on the fly” No residual files after query completed Analysts can’t see data Automatic cell suppression MATRIS (EMS) APCD Spine Hospital and ED BSAS Treatment Medical Claims PDMP

9 Methods Primary outcome: time to addiction treatment (methadone, buprenorphine, or naltrexone) after first nonfatal overdose Other variables: age, gender, past year incarceration, past year involuntary commitment, psychiatric diagnoses, and past year medication treatment for opioid use disorder

10 Analysis Aim 1: Calculate summary statistics and chi-square analyses to describe characteristics of emerging adults who experience a nonfatal opioid-related overdose compared older adults Aim 2: Estimate Kaplan-Meier survival curves for emerging adults with a nonfatal overdose for time to treatment and fit Cox Proportional Hazards models to determine rates of treatment receipt

11 Results: Baseline Characteristics of Nonfatal Overdose Among MA Residents ages years (N=15,281) Variable 18-21 y.o. % (n) N=1209 22-25 y.o. N=3059 26-35 y.o. N=11013 36-45 y.o. N=7030 Female 43.8% (530) 38.4% (1174) 32.0% (2299) 36.3% (1393) Homeless 10.7% (129) 13.7% (418) 18.2% (1306) 18.6% (712) Civil commitment 7.5% (91) 8.2% (250) 5.3% (382) 2.2% (85) Anxiety 15.9% (192) 15.6% (477) 19.4% (1392) 22.2% (850) Depression 17.7% (214) 17.5% (535) 21.9% (1572) 26.0% (997) Buprenorphine* 9.8% (118) 13.4% (411) 15.1% (1085) 12.8% (492) Naltrexone* 7.2% (87) 7.6% (234) 5.7% (407) 3.7% (140) Methadone* 3.6% (43) 8.5% (261) 13.4% (961) 12.4% (476) Detox* 21.9% (265) 30.9% (946) 32.1% (2307) 22.6% (866) Residential * 9% (109) 11.4% (349) 11.3% (809) 6.9% (265) *Receipt in prior 12 months

12 Receipt of Medication in the 12 months following a nonfatal overdose (%)

13 Adjusted* hazard for receipt of ANY medication after nonfatal overdose compared to 18-21 yo
Less likely More likely 26-35 years old 0.63 (0.61, 0.76) 36-45 years old 0.87 (0.77, 0.98) 0.1 0.5 1 2 3 4 5 Hazard Ratio * Adjusted for: age, sex, depression dx, anxiety dx, incarceration, involuntary commitment

14 Adjusted* hazard for receipt of ANY medication after nonfatal overdose compared to 22-25 yo
Less likely More likely 26-35 years old 0.93 (0.86, 0.99) 36-45 years old 1.18 (1.01, 1.28) 0.1 0.5 1 2 3 4 5 Hazard Ratio * Adjusted for: age, sex, depression dx, anxiety dx, incarceration, involuntary commitment

15 Adjusted* hazard for receipt of buprenorphine after nonfatal overdose compared to 18-21 yo
Less likely More likely 26-35 years old 0.75 (0.64, 0.87) 36-45 years old 0.83 (0.71, 0.96) 0.1 0.5 1 2 3 4 5 Hazard Ratio * Adjusted for: age, sex, depression dx, anxiety dx, incarceration, involuntary commitment

16 Adjusted* hazard for receipt of buprenorphine after nonfatal overdose compared to 22-25 yo
Less likely More likely 26-35 years old 0.96 (0.87, 1.05) 36-45 years old 1.07 (0.96, 1.19) 0.1 0.5 1 2 3 4 5 Hazard Ratio * Adjusted for: age, sex, depression dx, anxiety dx, incarceration, involuntary commitment

17 Adjusted* hazard for receipt of methadone after nonfatal overdose compared to 18-21 yo
Less likely More likely 26-35 years old 0.42 (0.36, 0.53) 36-45 years old 0.52 (0.41, 0.66) 0.1 0.5 1 2 3 4 5 Hazard Ratio * Adjusted for: age, sex, depression dx, anxiety dx, incarceration, involuntary commitment

18 Adjusted* hazard for receipt of methadone after nonfatal overdose compared to 22-25 yo
Less likely More likely 26-35 years old 0.79 (0.70, 0.89) 36-45 years old 0.99 (0.86, 1.13) 0.1 0.5 1 2 3 4 5 Hazard Ratio * Adjusted for: age, sex, depression dx, anxiety dx, incarceration, involuntary commitment

19 Adjusted* hazard for receipt of naltrexone after nonfatal overdose compared to 18-21 yo
Less likely More likely 26-25 years old 1.28 (1.05, 1.55) 36-45 years old 2.22 (1.77, 2.79) 0.1 0.5 1 2 3 4 5 Hazard Ratio * Adjusted for: age, sex, depression dx, anxiety dx, incarceration, involuntary commitment

20 Adjusted* hazard for receipt of naltrexone after nonfatal overdose compared to 22-25 yo
Less likely More likely 26-35 years old 1.20 (1.05, 1.38) 36-45 years old 2.09 (1.74, 2.52) 0.1 0.5 1 2 3 4 5 Hazard Ratio * Adjusted for: age, sex, depression dx, anxiety dx, incarceration, involuntary commitment

21 Less likely More likely Adjusted* hazard for receipt of medication after nonfatal overdose comparing yo to yo ANY medication 0.74 (0.65, 0.83) Methadone 0.53 (0.42, 0.67) Buprenorphine 0.78 (0.66, 0.95) 1.06 (0.86, 1.31) Naltrexone 0.1 0.5 1 2 3 4 5 Hazard Ratio * Adjusted for: age, sex, depression dx, anxiety dx, incarceration, and detoxification treatment, and monthly receipt of opioid or benzodiazepine

22 Limitations Individuals who experience overdose outside of health care system are not captured in these data. Only generalizable to MA

23 Conclusions Emerging adults represented nearly 1 in 5 non-fatal opioid-related overdoses among year olds in Massachusetts between Variation exists in receipt of medication by type of medication in 12 months following a nonfatal overdose 18-21 year olds are less likely to receive medication treatment including buprenorphine and methadone compered to older adults Emerging adults more likely to receive naltrexone than older adults Overall small proportions of individuals who experience a nonfatal overdose receive medication treatment in the following 12 month

24 Implications Future work should focus on outcomes (mortality, retention in treatment, and relapse) based on age and medication type There is a need for a better understanding of how (and why) emerging adults and providers make choices about medication treatment Post-overdose interventions to engage individuals in treatment after nonfatal overdose are urgently needed

25 Acknowledgments Collaborators
BMC/BU: Alex Walley, Marc LaRochelle, Jeffrey Samet, Ziming Xuan, Na Wang, and Scott Hadland Massachusetts Department of Public Health: Tom Land, Dana Bernson This work was supported by a through a grant from NIDA 1K23DA It does not represent the

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