Lessons learned from a multiagency community mental health centre quality improvement learning collaborative in New Hampshire

Academic Article

Abstract

  • Background/Aims Community mental health centres in the US often struggle to implement the evidenced-based metrics and measurement processes required for quality reporting initiatives. Through the co-design and facilitation of a learning collaborative, all 10 community mental health centres in New Hampshire agreed on the goal of demonstrating measurement alignment and improvement across three behavioural health metrics related to depression and suicide risk, aiming for a screening rate of at least 85% in a year. Methods The learning system framework and Lean Six Sigma define, measure, analyse, improve and control methodologies were used to increase participation and improve quality reporting. Teams were asked to participate in both a group learning collaborative and individual centre facilitation sessions, working with a quality improvement specialist. Reported measures were compared with subsets of the population data and between centres. Outliers were identified for potential reporting inaccuracies and opportunities for improvement. Results All 10 community mental health centres were able to accurately report screening results on all three measures. After 12 months, 70% of the teams were able to reach the group-determined goal of at least 85% of eligible patients being screened in one measure, 40% of the teams met the benchmark in two measures and 20% of the teams were able to meet the benchmark in all three measures. Conclusions Early investment by community mental health centre leadership through the development of a shared aim and project outcomes is essential to support learning and achieve positive outcomes. Quality improvement specialists are vital for facilitation of shared learning and practice across organisations.
  • Authors

  • Doyle, Marcy
  • Watts, Delitha
  • Umana, Molly
  • Thomas, Janet
  • Ryer, Jeanne
  • Status

    Publication Date

  • September 2, 2023
  • Digital Object Identifier (doi)

    Start Page

  • 234
  • End Page

  • 247
  • Volume

  • 29
  • Issue

  • 9