Comorbid Substance Use Disorder Profiles and Receipt of Substance Use Disorder Treatment Services: A National Study.
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2021-03
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Abstract
Objective
Those with comorbid substance use disorders (SUDs) are a particularly vulnerable group. Information regarding the nature of these comorbidities and how they relate to receipt of substance use treatment could reduce the treatment gap that exists among those with comorbid SUDs.Method
Public-use data from the 2015-2017 National Surveys on Drug Use and Health was used to analyze past-year SUD comorbidity combinations among 12 substances and the relationship between these combinations with past-year treatment in adults (N = 128,740).Results
In all, 7.9% of adults had at least one SUD in the past year (6.7% had one SUD, 0.9% had two SUDs, and 0.3% had three or more). Conditioning on specific SUDs, the prevalence of having additional SUDs ranged from 14.9% (alcohol) to 85.1% (hallucinogens). The four most common SUD combinations all included alcohol use disorder. Alcohol and marijuana use disorder was the most common comorbidity combination and had the lowest receipt of treatment. Compared to those with one SUD, adjusted odds of receiving treatment were almost two times greater for those with two SUDs, and more than four times greater for those with three or more SUDs. Treatment prevalence was lower for those who had higher family income and education, were not employed full time, were married, were younger than age 26 years or older than age 50 years, and were Asian.Conclusions
Even though the treatment gap is reduced among those with multiple SUDs, it remains large. The most common and undertreated comorbid SUD combinations, in conjunction with the most underserved groups, could be targeted to facilitate treatment uptake.Type
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Von Gunten, Curtis D, and Li-Tzy Wu (2021). Comorbid Substance Use Disorder Profiles and Receipt of Substance Use Disorder Treatment Services: A National Study. Journal of studies on alcohol and drugs, 82(2). pp. 246–256. 10.15288/jsad.2021.82.246 Retrieved from https://hdl.handle.net/10161/22726.
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Scholars@Duke
Li-Tzy Wu
Education/Training: Pre- and post-doctoral training in mental health service research, psychiatric epidemiology (NIMH T32), and addiction epidemiology (NIDA T32) from Johns Hopkins University School of Public Health (Maryland); Fellow of the NIH Summer Institute on the Design and Conduct of Randomized Clinical Trials.
Director: Duke Community Based Substance Use Disorder Research Program.
Research interests: COVID-19, Opioid misuse, Opioid overdose, Opioid use disorder, Opioid addiction prevention and treatment, Pain and addiction, Chronic diseases and substance use disorders, diabetes, pharmacy-based care models and services, medication treatment for opioid use disorder (MOUD), Drug overdose, Polysubstance use and disorders, cannabis, alcohol, tobacco, hallucinogens, stimulants, e-cigarette, SBIRT (substance use Screening, Brief Intervention, Referral to Treatment), EHR-based research and intervention, data science, psychometric analysis (IRT), epidemiology of addictions and comorbidity, behavioral health care integration, health services research (mental health disorders, substance use disorders, chronic diseases), nosology, research design, HIV risk behavior.
FUNDED Research projects (Principal Investigator [PI], Site PI, or Sub-award PI):
R03: Substance use/dependence (PI).
R21: Treatment use for alcohol use disorders (PI).
R21: Inhalant use & disorders (PI).
R01: MDMA/hallucinogen use/disorders (PI).
R01: Prescription pain reliever (opioids) misuse and use disorders (PI).
R01: Substance use disorders in adolescents (PI).
R21: CTN Substance use diagnoses & treatment (PI).
R33: CTN Substance use diagnoses & treatment (PI).
R01: Evolution of Psychopathology in the Population (ECA Duke site PI).
R01: Substance use disorders and treatment use among Asian Americans and Pacific Islanders (PI).
UG1: SBIRT in Primary Care (NIDA, PI).
UG1: TAPS Tool, Substance use screening tool validation in primary care (NIDA, PI).
UG1: NIDA CTN Mid-Southern Node (Clinical Trials Network, PI).
UG1: EHR Data Element Study (NIDA, PI).
UG1: Buprenorphine Physician-Pharmacist Collaboration in the Management of Patients With Opioid Use Disorder (NIDA, PI).
PCORI: INSPIRE-Integrated Health Services to Reduce Opioid Use While Managing Chronic Pain (Site PI).
CDC R01: Evaluation of state-mandated acute and post-surgical pain-specific CDC opioid prescribing (Site PI).
Pilot: Measuring Opioid Use Disorders in Secondary Electronic Health Records Data (Carolinas Collaborative Grant: Duke PI).
R21: Developing a prevention model of alcohol use disorder for Pacific Islander young adults (Subaward PI, Investigator).
UG1: Subthreshold Opioid Use Disorder Prevention Trial (NIH HEAL Initiative) (NIDA supplement, CTN-0101, Investigator).
NIDA: A Pilot Study to Permit Opioid Treatment Program Physicians to Prescribe Methadone through Community Pharmacies for their Stable Methadone Patients (NIDA/FRI: Study PI).
UG1: Integrating pharmacy-based prevention and treatment of opioid and other substance use disorders: A survey of pharmacists and stakeholder (NIH HEAL Initiative, NIDA, PI).
UG1: NorthStar Node of the Clinical Trials Network (NIDA, Site PI).
R34: Intervention Development and Pilot Study to Reduce Untreated Native Hawaiian and Pacific Islander Opioid Use Disorders (Subaward PI, Investigator).
UG1: Optimal Policies to Improve Methadone Maintenance Adherence Longterm (OPTIMMAL Study) (NIDA, Site PI).
R01: Increasing access to opioid use disorder treatment by opening pharmacy-based medication units of opioid treatment programs (NIDA, PI)
R01: Preventing Alcohol Use Disorders and Alcohol-Related Harms in Pacific Islander Young Adults (Subaward PI, Investigator).
R01: Understanding the short- and long-term effects of the COVID-19 pandemic on the overdose crisis (Subaward PI, Investigator).
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