# The Development of Quality Indicators to Assess Family Wellbeing Outcomes Following Engagement with Children’s Mental Health Services in Ontario, Canada

## TL;DR

This paper introduces new quality indicators to assess how well children's mental health services in Ontario support family wellbeing, accounting for differences in client complexity.

## Contribution

The study develops and validates six risk-adjusted quality indicators focused on family outcomes in children's mental health care.

## Key findings

- Six quality indicators were developed to measure changes in parenting strengths, caregiver distress, and family functioning.
- The risk adjustment method successfully accounted for client complexity in calculating the indicators.
- The indicators are independent enough to capture distinct aspects of family wellbeing.

## Abstract

(1) Background: Caregivers and families of children involved with mental health services face unique challenges. In Ontario, there is a dearth of information on outcomes for families following a child’s involvement with mental health services. Metrics known as Quality Indicators (QIs) offer a way to better understand these outcomes. Importantly, QIs can be risk adjusted to account for the influence of client complexity to allow for fair inter-agency comparisons. This study developed a set of risk-adjusted caregiver/family outcome QIs for children’s mental healthcare agencies. (2) Methods: Archival data from widely implemented interRAI child and youth assessment instruments was used. Previous methodology for QI calculation and risk adjustment was adapted and tested. (3) Results: Utilizing the interRAI suite of child and youth assessment instruments, a set of six QIs focusing on improvement or decline in parenting strengths, caregiver distress, and family functioning were developed. (4) Conclusions: The QIs established were sufficiently independent to represent different aspects of family wellbeing while the risk adjustment strategy developed was useful in removing client complexity from QI calculation. Implications for future directions, including the use of QIs at a systems level to more accurately direct resources and set performance benchmarks, are discussed.