In-Person Versus Telehealth Setting for the Delivery of Substance Use Disorder Treatment: Ecologically Valid Comparison Study (Preprint)
Authors: Ngo Quyen M , Braughton Jacqueline E , Gliske Kate , Waller Lance A , Sitar Siara , Kretman Danielle N , Cooper Hannah L F , Welsh Justine W 
Published: November 2021

BACKGROUND

The COVID-19 pandemic has profoundly transformed substance use disorder (SUD) treatment in the United States, with many web-based treatment services being used for this purpose. However, little is known about the long-term treatment effectiveness of SUD interventions delivered through digital technologies compared with in-person treatment, and even less is known about how patients, clinicians, and clinical characteristics may predict treatment outcomes.

OBJECTIVE

This study aims to analyze baseline differences in patient demographics and clinical characteristics across traditional and telehealth settings in a sample of participants (N=3642) who received intensive outpatient program (IOP) substance use treatment from January 2020 to March 2021.

METHODS

The <i>virtual IOP (VIOP) study</i> is a prospective longitudinal cohort design that follows adult (aged ≥18 years) patients who were discharged from IOP care for alcohol and substance use–related treatment at a large national SUD treatment provider between January 2020 and March 2021. Data were collected at baseline and up to 1 year after discharge from both in-person and VIOP services through phone- and web-based surveys to assess recent substance use and general functioning across several domains.

RESULTS

Initial baseline descriptive data were collected on patient demographics and clinical inventories. No differences in IOP setting were detected by race (<i>χ<sup>2</sup><sub>2</sub></i>=0.1; <i>P</i>=.96), ethnicity (<i>χ<sup>2</sup><sub>2</sub></i>=0.8; <i>P</i>=.66), employment status (<i>χ<sup>2</sup><sub>2</sub></i>=2.5; <i>P</i>=.29), education level (<i>χ<sup>2</sup><sub>4</sub></i>=7.9; <i>P</i>=.10), or whether participants presented with multiple SUDs (<i>χ<sup>2</sup><sub>8</sub></i>=11.4; <i>P</i>=.18). Significant differences emerged for biological sex (<i>χ<sup>2</sup><sub>2</sub></i>=8.5; <i>P</i>=.05), age (<i>χ</i><sup>2</sup><sub>6</sub>=26.8; <i>P</i>&lt;.001), marital status (<i>χ</i><sup>2</sup><sub>4</sub>=20.5; <i>P</i>&lt;.001), length of stay (<i>F</i><sub>2,3639</sub>=148.67; <i>P</i>&lt;.001), and discharge against staff advice (<i>χ</i><sup>2</sup><sub>2</sub>=10.6; <i>P</i>&lt;.01). More differences emerged by developmental stage, with emerging adults more likely to be women (<i>χ</i><sup>2</sup><sub>3</sub>=40.5; <i>P</i>&lt;.001), non-White (<i>χ</i><sup>2</sup><sub>3</sub>=15.8; <i>P</i>&lt;.001), have multiple SUDs (<i>χ</i><sup>2</sup><sub>3</sub>=453.6; <i>P</i>&lt;.001), have longer lengths of stay (<i>F</i><sub>3,3638</sub>=13.51; <i>P</i>&lt;.001), and more likely to be discharged against staff advice (<i>χ</i><sup>2</sup><sub>3</sub>=13.3; <i>P</i>&lt;.01).

CONCLUSIONS

The findings aim to deepen our understanding of SUD treatment efficacy across traditional and telehealth settings and its associated correlates and predictors of patient-centered outcomes. The results of this study will inform the effective development of data-driven benchmarks and protocols for routine outcome data practices in treatment settings.