The role of staff turnover in the implementation of evidence-based practices in mental health care

Psychiatr Serv. 2008 Jul;59(7):732-7. doi: 10.1176/ps.2008.59.7.732.

Abstract

Objectives: This study examined turnover rates of teams implementing psychosocial evidence-based practices in public-sector mental health settings. It also explored the relationship between turnover and implementation outcomes in an effort to understand whether practitioner perspectives on turnover are related to implementation outcomes.

Methods: Team turnover was measured for 42 implementing teams participating in a national demonstration project examining implementation of five evidence-based practices between 2002 and 2005. Regression techniques were used to analyze the effects of team turnover on penetration and fidelity. Qualitative data collected throughout the project were blended with the quantitative data to examine the significance of team turnover to those attempting to implement the practices.

Results: High team turnover was common (M+/-SD=81%+/-46%) and did not vary by practice. The 24-month turnover rate was inversely related to fidelity scores at 24 months (N=40, beta=-.005, p=.01). A negative trend was observed for penetration. Further analysis indicated that 71% of teams noted that turnover was a relevant factor in implementation.

Conclusions: The behavioral health workforce remains in flux. High turnover most often had a negative impact on implementation, although some teams were able to use strategies to improve implementation through turnover. Implementation models must consider turbulent behavioral health workforce conditions.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Behavioral Medicine*
  • Community Mental Health Services* / standards
  • Cooperative Behavior
  • Diffusion of Innovation
  • Empirical Research
  • Evidence-Based Medicine / organization & administration*
  • Health Plan Implementation
  • Humans
  • Linear Models
  • Logistic Models
  • Outcome and Process Assessment, Health Care / organization & administration
  • Personnel Turnover / statistics & numerical data*
  • Public Sector
  • United States
  • Workforce