Point-of-Care Complexity Screening Algorithm to Identify Children With Medical Complexity.

OBJECTIVES: For pediatric complex care programs to target enhanced care coordination services to the highest-risk patients, it is critical to accurately identify children with medical complexity (CMC); however, no gold standard definition exists. The aim of this study is to describe a point-of-care screening algorithm to identify CMC with high health care use, a group that may benefit the most from improved care coordination. METHODS: From July 1, 2015, to June 30, 2016 (fiscal year 2016 [FY16]), a medical complexity screening algorithm was implemented by a pediatric complex care program at a single tertiary care center for hospitalized patients at the time of admission. Using the screening algorithm, we categorized inpatients into 1 of 3 groups: CMC, children with special health care needs (CSHCN), or previously healthy (PH) children. Inpatient resource use for FY16 and FY17 encounters was extracted for children screened in FY16. RESULTS: We categorized 2187 inpatients in FY16 into the 3 complexity groups (CMC = 77; CSHCN = 1437; PH children = 673). CMC had more complex chronic conditions (median = 6; interquartile range [IQR] 4-11) than CSHCN (median = 1; IQR 0-2) and PH children (median = 0; IQR 0-0). CMC had greater per-patient and per-encounter hospital use than CSHCN and PH children. CMC and children with ≥4 complex chronic conditions had comparable levels of resource use. CONCLUSIONS: By implementation of a point-of-care screening algorithm, we identified CMC with high health care use. By using this algorithm, it was feasible to identify hospitalized CMC that could benefit from care coordination by a pediatric complex care program.

Duke Scholars

Author David Yung Ming Pediatrics, Hospital Medicine

Author Victoria Marie Parente Pediatrics, Hospital Medicine