Predictors of substance use treatment initiation and engagement among adult and adolescent Medicaid recipients

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Abstract

Background: It is important to understand patterns and predictors of initiation and engagement in treatment for Medicaid-covered individuals with substance use disorders because Medicaid is a major source of payment for addiction treatment in the United States. Our analysis examined similarities and differences in predictors between adults and adolescents. Methods: An analysis of Oregon Medicaid claims data for the time period January 2010 through June 2015 assessed rates of substance use and of treatment initiation and engagement using the Healthcare Effectiveness Data and Information Set (HEDIS) definitions. The analysis included individuals aged 13–64 with a new alcohol and other drug dependence diagnosis who met the HEDIS enrollment criteria and did not have cancer. We created 4 logistic regression models to assess treatment initiation and engagement, separately for adults (ages 18–64) and adolescents (ages 13–17). Independent predictors included age, gender, race, the interaction of gender and race, urban/rural residence, presence of any chronic disease, a psychiatric diagnosis, or a pain diagnosis. Results: Among adults, odds of initiation were lower in white males than in nonwhite males, white females, and nonwhite females. Conversely, among adolescents, odds of initiation were higher in white males than in the other gender/race groups. Predictors of initiation also went in opposite directions for presence of a psychiatric diagnosis (negative in adults, positive in adolescents) and urban residence (positive in adults, negative in adolescents). We found similar patterns in models of engagement, although for engagement those with a psychiatric diagnosis had lower odds of engagement in both adults and adolescents. Conclusions: Predictors of treatment initiation and engagement for alcohol and drug use disorders differed between adults and adolescents on Medicaid. A better understanding of these differences will enable development of targeted treatment programs that are effective within age groups.

Original languageEnglish (US)
JournalSubstance Abuse
DOIs
StatePublished - Jan 1 2019

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Medicaid
Mental Disorders
Substance-Related Disorders
Therapeutics
Logistic Models
Alcohols
Delivery of Health Care
Chronic Disease
Age Groups
Pain
Neoplasms

Keywords

  • Medicaid
  • performance measures
  • Substance use disorder
  • substance use disorder treatment

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Psychiatry and Mental health

Cite this

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title = "Predictors of substance use treatment initiation and engagement among adult and adolescent Medicaid recipients",
abstract = "Background: It is important to understand patterns and predictors of initiation and engagement in treatment for Medicaid-covered individuals with substance use disorders because Medicaid is a major source of payment for addiction treatment in the United States. Our analysis examined similarities and differences in predictors between adults and adolescents. Methods: An analysis of Oregon Medicaid claims data for the time period January 2010 through June 2015 assessed rates of substance use and of treatment initiation and engagement using the Healthcare Effectiveness Data and Information Set (HEDIS) definitions. The analysis included individuals aged 13–64 with a new alcohol and other drug dependence diagnosis who met the HEDIS enrollment criteria and did not have cancer. We created 4 logistic regression models to assess treatment initiation and engagement, separately for adults (ages 18–64) and adolescents (ages 13–17). Independent predictors included age, gender, race, the interaction of gender and race, urban/rural residence, presence of any chronic disease, a psychiatric diagnosis, or a pain diagnosis. Results: Among adults, odds of initiation were lower in white males than in nonwhite males, white females, and nonwhite females. Conversely, among adolescents, odds of initiation were higher in white males than in the other gender/race groups. Predictors of initiation also went in opposite directions for presence of a psychiatric diagnosis (negative in adults, positive in adolescents) and urban residence (positive in adults, negative in adolescents). We found similar patterns in models of engagement, although for engagement those with a psychiatric diagnosis had lower odds of engagement in both adults and adolescents. Conclusions: Predictors of treatment initiation and engagement for alcohol and drug use disorders differed between adults and adolescents on Medicaid. A better understanding of these differences will enable development of targeted treatment programs that are effective within age groups.",
keywords = "Medicaid, performance measures, Substance use disorder, substance use disorder treatment",
author = "Bonnie Lind and Dennis McCarty and Yifan Gu and Robin Baker and McConnell, {Kenneth (John)}",
year = "2019",
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doi = "10.1080/08897077.2018.1550467",
language = "English (US)",
journal = "Substance Abuse",
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AU - Lind, Bonnie

AU - McCarty, Dennis

AU - Gu, Yifan

AU - Baker, Robin

AU - McConnell, Kenneth (John)

PY - 2019/1/1

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N2 - Background: It is important to understand patterns and predictors of initiation and engagement in treatment for Medicaid-covered individuals with substance use disorders because Medicaid is a major source of payment for addiction treatment in the United States. Our analysis examined similarities and differences in predictors between adults and adolescents. Methods: An analysis of Oregon Medicaid claims data for the time period January 2010 through June 2015 assessed rates of substance use and of treatment initiation and engagement using the Healthcare Effectiveness Data and Information Set (HEDIS) definitions. The analysis included individuals aged 13–64 with a new alcohol and other drug dependence diagnosis who met the HEDIS enrollment criteria and did not have cancer. We created 4 logistic regression models to assess treatment initiation and engagement, separately for adults (ages 18–64) and adolescents (ages 13–17). Independent predictors included age, gender, race, the interaction of gender and race, urban/rural residence, presence of any chronic disease, a psychiatric diagnosis, or a pain diagnosis. Results: Among adults, odds of initiation were lower in white males than in nonwhite males, white females, and nonwhite females. Conversely, among adolescents, odds of initiation were higher in white males than in the other gender/race groups. Predictors of initiation also went in opposite directions for presence of a psychiatric diagnosis (negative in adults, positive in adolescents) and urban residence (positive in adults, negative in adolescents). We found similar patterns in models of engagement, although for engagement those with a psychiatric diagnosis had lower odds of engagement in both adults and adolescents. Conclusions: Predictors of treatment initiation and engagement for alcohol and drug use disorders differed between adults and adolescents on Medicaid. A better understanding of these differences will enable development of targeted treatment programs that are effective within age groups.

AB - Background: It is important to understand patterns and predictors of initiation and engagement in treatment for Medicaid-covered individuals with substance use disorders because Medicaid is a major source of payment for addiction treatment in the United States. Our analysis examined similarities and differences in predictors between adults and adolescents. Methods: An analysis of Oregon Medicaid claims data for the time period January 2010 through June 2015 assessed rates of substance use and of treatment initiation and engagement using the Healthcare Effectiveness Data and Information Set (HEDIS) definitions. The analysis included individuals aged 13–64 with a new alcohol and other drug dependence diagnosis who met the HEDIS enrollment criteria and did not have cancer. We created 4 logistic regression models to assess treatment initiation and engagement, separately for adults (ages 18–64) and adolescents (ages 13–17). Independent predictors included age, gender, race, the interaction of gender and race, urban/rural residence, presence of any chronic disease, a psychiatric diagnosis, or a pain diagnosis. Results: Among adults, odds of initiation were lower in white males than in nonwhite males, white females, and nonwhite females. Conversely, among adolescents, odds of initiation were higher in white males than in the other gender/race groups. Predictors of initiation also went in opposite directions for presence of a psychiatric diagnosis (negative in adults, positive in adolescents) and urban residence (positive in adults, negative in adolescents). We found similar patterns in models of engagement, although for engagement those with a psychiatric diagnosis had lower odds of engagement in both adults and adolescents. Conclusions: Predictors of treatment initiation and engagement for alcohol and drug use disorders differed between adults and adolescents on Medicaid. A better understanding of these differences will enable development of targeted treatment programs that are effective within age groups.

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