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

Area of Science:

• Pediatric healthcare research
• Health services research
• Medical informatics

Background:

• Accurate identification of children with medical complexity (CMC) is crucial for effective care coordination.
• Existing definitions lack a gold standard, hindering targeted interventions.
• Pediatric complex care programs aim to serve the highest-risk patients.

Purpose of the Study:

• To describe a point-of-care screening algorithm for identifying CMC with high healthcare utilization.
• To evaluate the feasibility of this algorithm in a clinical setting.
• To inform the targeting of enhanced care coordination services.

Main Methods:

• A medical complexity screening algorithm was implemented at a tertiary care center for hospitalized patients.
• Inpatients were categorized into three groups: CMC, children with special health care needs (CSHCN), and previously healthy (PH) children.
• Inpatient resource use was analyzed for screened children over two fiscal years.

Main Results:

• 2187 inpatients were screened and categorized in FY16.
• Children with medical complexity (CMC) had significantly more complex chronic conditions (median 6) compared to CSHCN (median 1) and PH children (median 0).
• CMC demonstrated higher per-patient and per-encounter hospital resource utilization than CSHCN and PH children.

Conclusions:

• A point-of-care screening algorithm successfully identified hospitalized CMC with high healthcare use.
• The algorithm is feasible for use in pediatric complex care programs.
• This tool can aid in directing care coordination resources to children most likely to benefit.