Analyzing national and state opioid abuse treatment completion with multilevel modeling

Huitong Pan, Sally Gao, Kennan Grant, Wendy Novicoff, Hyojung Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The misuse of opioids has become a national public health emergency in the United States. Successfully completing a program of treatment at a substance abuse treatment facility is associated with better long-term outcomes, but a significant portion of opioid use patients are discharged without successfully completing treatment. The objective of this study is to evaluate factors associated with treatment success. We used the Treatment Episodes Datasets: Discharges (TEDS-D) dataset, a national sample of discharges from substance abuse treatment centers, and the National Survey of Substance Abuse Treatment Services (N-SSATS) dataset, an annual survey of all known substance use treatment facilities, for the years 2013 and 2014. A random slope, random intercept multilevel model was used to estimate the effects of patient- and state-level variables on treatment completion. We find that a patient is more likely to complete treatment if that patient is older, employed, has private insurance, waited less time before entering treatment, is not receiving medication-assisted treatment, and is in residential care. In addition, we find that patients living in with states with higher levels of Vivitrol adoption are more likely to complete treatment. Our findings could encourage policymakers and treatment facilities to consider prioritizing Vivitrol adoption. At the same time, our results demonstrate substantial variation of predictors across states and suggest the need for further research into the relationship between state contexts and the predictors of successful opioid use treatment.

Original languageEnglish (US)
Title of host publication2018 Systems and Information Engineering Design Symposium, SIEDS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages123-128
Number of pages6
ISBN (Electronic)9781538663431
DOIs
StatePublished - Jun 6 2018
Externally publishedYes
Event2018 Systems and Information Engineering Design Symposium, SIEDS 2018 - Charlottesville, United States
Duration: Apr 27 2018 → …

Publication series

Name2018 Systems and Information Engineering Design Symposium, SIEDS 2018

Conference

Conference2018 Systems and Information Engineering Design Symposium, SIEDS 2018
Country/TerritoryUnited States
CityCharlottesville
Period4/27/18 → …

Keywords

  • Multilevel logistic regression modeling
  • Opioid use disorder
  • Treatment Episode Datasets-Discharge
  • Treatment outcomes

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Analyzing national and state opioid abuse treatment completion with multilevel modeling'. Together they form a unique fingerprint.

Cite this