Predictors of premature treatment termination in a large residential addiction medicine program.


Journal

Journal of substance abuse treatment
ISSN: 1873-6483
Titre abrégé: J Subst Abuse Treat
Pays: United States
ID NLM: 8500909

Informations de publication

Date de publication:
10 2020
Historique:
received: 04 04 2020
revised: 03 06 2020
accepted: 06 07 2020
entrez: 20 8 2020
pubmed: 20 8 2020
medline: 29 7 2021
Statut: ppublish

Résumé

While inpatient programs are a common setting for addiction treatment, patients' premature termination is a major concern. Predicting premature treatment termination has the potential to substantially improve patient outcomes by identifying high-risk profiles and suggesting care paths that might reduce dropout. The current study examined the predictors of premature termination from an inpatient addiction medicine service. In 1082 patients admitted to a large inpatient addiction medicine service, we used intake assessments of severity of alcohol use disorder, illicit drug use disorder, post-traumatic stress disorder (PTSD), anxiety disorders, and major depressive disorder to predict planned termination (n = 922) or premature termination (n = 160). We used two complementary analytic approaches-traditional binary logistic regression and a data-driven latent profile analysis (LPA). Binary logistic regression revealed that alcohol use severity, illicit drug use severity, and PTSD severity significantly predicted termination status, although alcohol use severity notably exhibited an inverse relationship. The LPA revealed four distinct profiles, with one profile exhibiting a significantly higher rate of premature termination and another exhibiting a significantly lower rate of premature termination. The high-risk profile was characterized by high drug severity, high comorbid psychopathology (PTSD, depression, and anxiety symptoms), but low alcohol severity. The low-risk profile was characterized by high alcohol severity, but low drug use and low comorbid psychopathology. These results provide converging evidence that illicit drug severity and psychiatric severity, and particularly PTSD, were associated with premature termination. Moreover, the LPA revealed distinct latent subgroups of patients with meaningfully higher and lower risk of premature termination, suggesting that addiction services should develop strategies for identifying high-risk individuals or develop care paths for high-risk symptom clusters. Approaches that are trauma-informed or otherwise focus on the management of comorbid psychiatric conditions may be particularly appropriate for reducing premature termination.

Sections du résumé

BACKGROUND
While inpatient programs are a common setting for addiction treatment, patients' premature termination is a major concern. Predicting premature treatment termination has the potential to substantially improve patient outcomes by identifying high-risk profiles and suggesting care paths that might reduce dropout. The current study examined the predictors of premature termination from an inpatient addiction medicine service.
METHODS
In 1082 patients admitted to a large inpatient addiction medicine service, we used intake assessments of severity of alcohol use disorder, illicit drug use disorder, post-traumatic stress disorder (PTSD), anxiety disorders, and major depressive disorder to predict planned termination (n = 922) or premature termination (n = 160). We used two complementary analytic approaches-traditional binary logistic regression and a data-driven latent profile analysis (LPA).
RESULTS
Binary logistic regression revealed that alcohol use severity, illicit drug use severity, and PTSD severity significantly predicted termination status, although alcohol use severity notably exhibited an inverse relationship. The LPA revealed four distinct profiles, with one profile exhibiting a significantly higher rate of premature termination and another exhibiting a significantly lower rate of premature termination. The high-risk profile was characterized by high drug severity, high comorbid psychopathology (PTSD, depression, and anxiety symptoms), but low alcohol severity. The low-risk profile was characterized by high alcohol severity, but low drug use and low comorbid psychopathology.
CONCLUSIONS
These results provide converging evidence that illicit drug severity and psychiatric severity, and particularly PTSD, were associated with premature termination. Moreover, the LPA revealed distinct latent subgroups of patients with meaningfully higher and lower risk of premature termination, suggesting that addiction services should develop strategies for identifying high-risk individuals or develop care paths for high-risk symptom clusters. Approaches that are trauma-informed or otherwise focus on the management of comorbid psychiatric conditions may be particularly appropriate for reducing premature termination.

Identifiants

pubmed: 32811634
pii: S0740-5472(20)30333-0
doi: 10.1016/j.jsat.2020.108077
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

108077

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Auteurs

Sabrina K Syan (SK)

Peter Boris Centre for Addictions Research, McMaster University & St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.

Meenu Minhas (M)

Peter Boris Centre for Addictions Research, McMaster University & St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.

Assaf Oshri (A)

Department of Human Development and Family Sciences, University of Georgia, Athens, GA, USA.

Jean Costello (J)

Homewood Research Institute, Guelph, ON, Canada.

Sarah Sousa (S)

Homewood Research Institute, Guelph, ON, Canada.

Andriy V Samokhvalov (AV)

Homewood Research Institute, Guelph, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada.

Brian Rush (B)

Homewood Research Institute, Guelph, ON, Canada; Centre for Addiction and Mental Health, Toronto, ON, Canada.

James MacKillop (J)

Peter Boris Centre for Addictions Research, McMaster University & St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada; Homewood Research Institute, Guelph, ON, Canada. Electronic address: jmackill@mcmaster.ca.

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