Timely access to children’s mental health services depends on accurate identification of service urgency; however, triage practices in Ontario, Canada vary widely, contributing to prolonged wait times and inconsistent pathways to care. This study aimed to develop and validate an empirically based decision-support algorithm to support standardized triaging and prioritization in Ontario based children’s mental health agencies. Data were drawn from 17,564 children and youth aged 4–18 years assessed with the interRAI Child and Youth Mental Health Screener (ChYMH-S) as part of routine clinical practice. Interactive decision tree modelling was used to identify combinations of clinical indicators associated with high service urgency, with age-stratified models for children 7 years and younger, 8–11 years, and 12 years and older. The resulting interRAI Children’s Algorithm for Mental Health and Psychiatric Services (ChAMhPS) classified individuals into seven urgency levels. The algorithm demonstrated good discrimination for services required within seven days (c-statistic = 0.70) and for the urgency of a comprehensive assessment (c-statistic = 0.73), with stable performance across derivation and testing samples. Higher algorithm levels were associated with an increased likelihood of urgent assessment or service need. The ChAMhPS algorithm offers a standardized, empirically derived tool to support clinical decision-making and improve consistency in triage and prioritization of children and youth with urgent mental health needs.
Stewart et al. (Sat,) studied this question.