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Getting the latest healthcare news for you
A new EHR-based algorithm is making it easier to identify children with medical complexity (CMC) who need specialized care. Developed at Toronto's SickKids hospital, the tool achieved a positive predictive value of up to 89.1%, dramatically cutting down on manual chart reviews. It could streamline recruitment into complex care programs and ease the transition from pediatric to adult services.
Researchers at Toronto's Hospital for Sick Children (SickKids) have developed an algorithm — called CMC-ID — that uses electronic health record (EHR) data to automatically identify children and youth with medical complexity (CMC). The tool was initially built to flag adolescents aged 17–18 for referral to a program helping them transition to adult care, and was later tested on a broader pediatric cohort aged 1–17.
The algorithm went through six iterations, with version 6 emerging as the top performer. It correctly identified medically complex patients with high accuracy in both age groups, far outpacing earlier versions that flagged far more false positives. Researchers say the tool could meaningfully reduce the burden of manual chart screening while improving access to targeted care programs.
By the Numbers
Why it matters: Identifying medically complex children early and accurately is critical for connecting them to the right programs — especially as they age out of pediatric care. This algorithm won't replace clinician judgment, but it could serve as a powerful screening tool to ensure high-needs kids don't fall through the cracks.
