Predicting and responding to change: Perceived environmental uncertainty among substance use disorder treatment...

Substance use disorder (SUD) treatment programs offering addiction health services (AHS) must be prepared to adapt to change in their operating environment. These environmental uncertainties may have implications for service delivery, and ultimately patient outcomes. To adapt to a multitude of environmental uncertainties, treatment programs must be prepared to predict and respond to change. Yet, research on treatment programs preparedness for change is sparse. We examined reported difficulties in predicting and responding to changes in the AHS system, and factors associated with these outcomes.

Cross-sectional surveys of SUD treatment programs in the United States in 2014 and 2017. We used linear and ordered logistic regression to examine associations between key independent variables (e.g., program, staff, and client characteristics) and four outcomes, (1) reported difficulties in predicting change, (2) predicting effect of change on organization, (3) responding to change, and (4) predicting changes to make to respond to environmental uncertainties. Data were collected through telephone surveys.

The proportion of SUD treatment programs reporting difficulty predicting and responding to changes in the AHS system decreased from 2014 to 2017. However, a considerable proportion still reported difficulty in 2017. We identified that different organizational characteristics are associated with their reported ability to predict or respond to environmental uncertainty. Findings show that predicting change is significantly associated with program characteristics only, while predicting effect of change on organizations is associated with program and staff characteristics. Deciding how to respond to change is associated with program, staff, and client characteristics, while predicting changes to make to respond is associated with staff characteristics only.

Although treatment programs reported decreased difficulty predicting and responding to changes, our findings identify program characteristics and attributes that could better position programs with the foresight to more effectively predict and respond to uncertainties. Given resource constraints at multiple levels in treatment programs, this knowledge might help identify and optimize aspects of programs to intervene upon to enhance their adaptability to change. These efforts may positively influences processes or care delivery, and ultimately translate into improvements in patient outcomes.