Association Between Clinician-Level Factors and Patient Outcomes in Virtual and In-Person Outpatient Treatment for Substance Use Disorders: Multilevel Analysis

JMIR Hum Factors. 2023 Nov 3:10:e48701. doi: 10.2196/48701.

Abstract

Background: The use of virtual treatment services increased dramatically during the COVID-19 pandemic. Unfortunately, large-scale research on virtual treatment for substance use disorder (SUD), including factors that may influence outcomes, has not advanced with the rapidly changing landscape.

Objective: This study aims to evaluate the link between clinician-level factors and patient outcomes in populations receiving virtual and in-person intensive outpatient services.

Methods: Data came from patients (n=1410) treated in a virtual intensive outpatient program (VIOP) and an in-person intensive outpatient program (IOP), who were discharged between January 2020 and March 2021 from a national treatment organization. Patient data were nested by treatment providers (n=58) examining associations with no-shows and discharge with staff approval. Empathy, comfort with technology, perceived stress, resistance to change, and demographic covariates were examined at the clinician level.

Results: The VIOP (β=-5.71; P=.03) and the personal distress subscale measure (β=-6.31; P=.003) were negatively associated with the percentage of no-shows. The VIOP was positively associated with discharges with staff approval (odds ratio [OR] 2.38, 95% CI 1.50-3.76). Clinician scores on perspective taking (β=-9.22; P=.02), personal distress (β=-9.44; P=.02), and male clinician gender (β=-6.43; P=.04) were negatively associated with in-person no-shows. Patient load was positively associated with discharge with staff approval (OR 1.04, 95% CI 1.02-1.06).

Conclusions: Overall, patients in the VIOP had fewer no-shows and a higher rate of successful discharge. Few clinician-level characteristics were significantly associated with patient outcomes. Further research is necessary to understand the relationships among factors such as clinician gender, patient load, personal distress, and patient retention.

Keywords: EHR; clinician characteristics; data collection; electronic health record; health care; in-person treatment; intensive outpatient program; patient outcomes; substance use; substance use treatment; telehealth; treatment; virtual reality; virtual treatment.

MeSH terms

  • Ambulatory Care
  • Humans
  • Male
  • Multilevel Analysis
  • Outpatients*
  • Pandemics
  • Substance-Related Disorders* / therapy