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Predictors of Treatment Completion in an Inpatient Substance Use Treatment Service in India
Abhishek Ghosh1, Nidhi Sharma, Dalton Noble
1From the Department of Psychiatry, Drug De-addiction and Treatment Centre, Postgraduate Institute of Medical Education and Research, Chandigarh, India (AG, DB, BNS, RRP, SK); Department of Computer Science and Engineering, Thapar University, Punjab, India (SK); Department of Psychiatry, Indira Gandhi Medical College, Shimla, Himachal Pradesh, India (NS); Department of Psychiatry, IVY Hospital, Nawanshahr, Punjab, India (DN); and Community Mental Health Clinic, Cumbria Northumberland Tyne and Wear Foundation NHS Trust, Molineux NHS Centre, Newcastle Upon Tyne, United Kingdom (SKM).
Introduction:
Treatment completion is associated with a better outcome in substance use disorders. We examined the rates of treatment completion and its predictors in patients admitted to specialized addiction treatment settings over a 13-year period.
Methods:
Ours was a retrospective cohort study. We included consecutive 2850 patients admitted to the inpatient treatment between January 2007 and December 2019. We divided the patients into 2 groups: completed versus premature discontinuation of treatment. The predictor variables were based on previous research, clinical experience, and availability of the digital record.
Results:
The number of patients who completed and discontinued treatments was 1873 (72.6%) and 707 (27.4%), respectively. The inpatient treatment discontinuation rate varied widely during the study period (18% in 2007 and 41% in 2012). The average rate of treatment discontinuation was 27%. The change-point analysis showed 5 statistically significant change points in the years 2008, 2010, 2012, 2014, and 2016. Patients who were prescribed medications for alcohol and opioid dependence and those who were on opioid agonist treatment had 4.7 and 6.3 higher odds of completing inpatient treatment than those who were not on medication. Patients with physical and psychiatric comorbidities had higher odds of treatment completion. Patients with a primary diagnosis of opioid dependence had lower odds of treatment completion than those with alcohol dependence.
Conclusions:
The rates of discontinuation may vary with concurrent changes in the treatment policies. Awareness of the risk factors and policy measures that may improve treatment completion must aid in informed decision making.
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