Predictors of Dropout from an Outpatient Treatment Program for Substance Use Disorders in India: a Retrospective Cohort
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Predictors of Dropout from an Outpatient Treatment Program for Substance Use Disorders in India: a Retrospective Cohort Study of Patients Registered over a 10-Year Period (2009–2018) Abhishek Ghosh 1 & Nidhi Sharma 2 & B. N. Subodh 1 & Debasish Basu 1 & Surendra Kumar Mattoo 1 & Renjith R. Pillai 1 Accepted: 16 October 2020/ # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
This was a retrospective cohort study to determine the predictors of dropout in the first year from an out-patient treatment program for substance use disorders. Study period was from January 1, 2009, to December 31, 2018. Patients registered for detailed evaluation in the outpatient treatment program and followed up at least once were included. The primary end-point was dropout from treatment, defined as no follow-up at four timepoints. We used Cox proportional hazard regression model to determine the predictors of dropout. Dropout rate at the end of 12 months: 80.37%. Dispensing free medicines (hazard ratio [HR]: 1.271), and self-treatment referral (HR: 1.116) increased risk of dropout. Dual diagnosis (HR: 0.906) and prescription of maintenance medication (HR: 0.734) reduced the risks of dropout. A priori knowledge of predictors could guide clinicians, service planners, and policymakers to provide tailor-made treatment and reorganize service delivery. Keywords Substance use disorder . Dropout . Treatment . Outpatient . Cox proportional hazard Completion of substance abuse treatment is one of the most consistent and significant factors associated with a favorable outcome (Basu et al. 2017; Majumder et al. 2016; Brorson et al. 2013; Dalsbo et al. 2010). Patients with a longer duration in substance abuse treatments are associated with improved outcomes (Beynon et al. 2008). Treatment retention was associated with higher rates of abstinence, lower crime rates, and higher employment, whereas premature * Debasish Basu [email protected]
1
Drug De-addiction & Treatment Centre (DDTC), Department of Psychiatry, Postgraduate Institute of Medical Education & Research (PGIMER), Chandigarh, India
2
Department of Psychiatry, Indira Gandhi Medical College & Hospital (IGMC), Shimla, Himachal Pradesh, India
International Journal of Mental Health and Addiction
dropout has been linked to increased risk of relapse, financial and legal problems, poor physical health, and readmission (Brorson et al. 2013; Brewer et al. 1998; Alterman et al. 1996; Moos et al. 1995; Stark 1992). Nevertheless, rates of dropout from addiction treatment ranges from 25–70%, across various treatment settings (Lappan et al. 2019; Brorson et al. 2013; McHugh et al. 2005; Santonja-Gómez et al. 2010). Predictors of dropout could be clientrelated or treatment and service-related. Client’s age, level of education, presence of comorbid psychiatric disorders, and motivation to seek treatment have been variably demonstrated as predictors of dropout (Preti et al. 2015; Brorson et al. 2013; López-Goñi et al. 2012; Astals et al. 2009; Cahill et al. 2003; Mertens
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