Publicly Funded Home and Community-Based Care for Children With Medical Complexity: Protocol for the Analysis of Medicaid Waiver Applications

Background: Children with medical complexity are a group of children with multiple chronic conditions and functional limitations that represent the highest health care utilization and often require a substantial number of home and community-based services (HCBS). In many states, HCBS are offered to target populations through 1915(c) Medicaid waivers. To date, no standard methods or approaches have been established to evaluate or compare 1915 (c) waivers across states in the United States for children. Objective: The purpose of this analysis was to develop a systematic and reproducible approach to evaluate 1915(c) Medicaid waivers for overall coverage of children with medical complexity. Methods: Data elements were extracted from Medicaid 1915(c) approved waiver applications for all included waivers targeting any pediatric age range through October 31, 2018. Normalization criteria were established, and an aggregate overall coverage score was calculated for each waiver. Results: Data extraction occurred in two phases: (1) waivers that were considered nonexpired through December 31, 2017, and (2) the final sample that included nonexpired waivers through October 31, 2018. A total of 142 waivers across 45 states in the United States were included in this analysis. We found that the existing adult HCBS taxonomy may not always be applicable for child and family-based service provision. Although there was uniformity in the Medicaid applications, there was high heterogeneity in how waiver eligibility, transition plans, and wait lists were defined. Study analysis was completed in January 2019, and after analyzing each individual waiver, results were aggregated at the level of the state and for each diagnostic subgroup. The published results are forthcoming. Conclusions: To our knowledge, this is the first study to systematically evaluate 1915 (c) Medicaid waivers targeting children with medical complexity that can be replicated without the threat of missing data.