Pediatric Complex Chronic Conditions Classification System Version 2: Updated for ICD-10 and Complex Medical Technology Dependence and Transplantation

An ICD-10 update of the pediatric complex chronic conditions (CCC) classification system from 2000. The system includes diagnostic and procedural codes that incorporate a new neonatal CCC category as well as domains of complexity arising from technology dependence or organ transplantation. Linked electronic supplementary material provides SAS and Stata code, plus tabular information on codes.

Feudtner 2014 (BMC Pediatrics) | PubMed 25102958 | Author Search

Ways to Identify Children with Medical Complexity and the Importance of Why

Comparison of 4 examples of diagnosis classification systems that have been used to identify the health problems in children with medical complexity: (1) Complex chronic conditions (CCCs), an open-source set of childhood conditions that are strongly associated with mortality, morbidity, functional limitations, high health resource utilization, and use of a complex care clinical program; (2) Clinical risk groups (CRGs), a proprietary system of hierarchical pediatric diagnosis groups ranging from healthy children without a chronic condition to unhealthy children with a catastrophic chronic condition that is associated with high morbidity and mortality; (3) Chronic condition indicators (CCIs), developed by the Agency for Healthcare Research and Quality, an open source diagnosis classification system that dichotomizes ∼14 000 ICD9 and ∼68 000 ICD10 diagnosis codes into chronic and non chronic conditions; and Patient medical complexity algorithm (PMCA), developed by Seattle Children’s Hospital, an open source, pediatric-specific, diagnosis classification system that uses ICD9 codes to group children into 1 of 3 categories: complex, chronic disease; noncomplex, chronic disease; and nonchronic disease.

Berry 2015 (J. Pediatrics) | PubMed 26028285 | Author Search

Predictive Analytics In Healthcare: Medications as a Predictor of Medical Complexity

A white paper from Health IT Outcomes describing an analysis at Seattle Children’s Hospital showing a good correlation between the numbers of inpatient and outpatient medications and complex-care status. Many variables based on counts of medications, use of individual medications, and use of combinations of medications were considered, resulting in a simple model based on three different counts of medications: outpatient and inpatient drug classes and individual inpatient drug names.

Higdon 2013 (Link)