Health Complexity Indicators to Guide and Inform Policy, System- and Practice-Level Efforts: Supporting and Learning from Efforts in Oregon

A novel methodology combining medical complexity (using the Pediatric Medical Complexity Algorithm) and social complexity (using available family social factors known to impact a child’s health and healthcare use) was used to create a new health complexity model at both the population-level and individual-level. Findings from the article demonstrate that a large number of Medicaid/CHIP-insured children could benefit from targeted care coordination and differential resource allocation that aligns with their health complexity.

This brief applies health complexity, a concept that considers both a child’s medical and social complexity, to address health disparities. It includes recommendations on how state agencies and health systems can develop and use health complexity data to ensure the most vulnerable children are at the center of health system redesign.

Health complexity is a concept that considers both a child’s medical and social complexity. For health systems, identifying and supporting children with health complexity directly aligns with efforts to eliminate health disparities. This webinar described how health systems can identify children with health complexity and provided actionable strategies and models to use this information to improve services and supports for families. Presenters shared real world examples and recommendations based on technical assistance provided to State Medicaid and Children’s Health Insurance Program (CHIP) agencies and health systems over the last five years. Additionally, a panel of health system leaders who have received technical assistance shared their reflections and learnings.

This opinion piece from Oregon Pediatric Improvement Partnership (OPIP) highlights a model of health complexity they developed and offers recommendations for how to strategically use data to begin eliminating health disparities.