Effective management of publicly funded services matches the provision of needed services with cost-efficient payment methods. Payment systems that recognize differences in care needs (eg, case-mix systems) allow for greater proportions of available funds to be directed to providers supporting individuals with more needs. We describe a new way to allocate funds spent on adults with intellectual disabilities (ID) as part of a system-wide Medicaid payment reform initiative in Arkansas. Analyses were based on population-level data for persons living at home, collected using the interRAI ID assessment system, which were linked to paid service claims. We used automatic interactions detection to sort individuals into unique groups and provide a standardized relative measure of the cost of the services provided to each group. The final case-mix system has 33 distinct final groups and explains 26% of the variance in costs, which is similar to other systems in health and social services sectors. The results indicate that this system could be the foundation for a future case-mix approach to reimbursement and stand the test of “fairness” when examined by stakeholders, including parents, advocates, providers, and political entities.
Limited funding across health and social service programs presents a challenge regarding how to best match resources to the needs of the population. There is increasing consensus that differences in individual characteristics and care needs should be reflected in variations in service costs, which has led to the development of case-mix systems. The present study sought to develop a new approach to allocate resources among children and youth with intellectual and developmental disabilities (IDD) as part of a system-wide Medicaid payment reform initiative in Arkansas. To develop the system, assessment data collected using the interRAI Child and Youth Mental Health-Developmental Disability instrument was matched to paid service claims. The sample consisted of 346 children and youth with developmental disabilities in the home setting. Using automatic interactions detection, individuals were sorted into unique, clinically relevant groups (ie, based on similar resource use) and a standardized relative measure of the cost of services provided to each group was calculated. The resulting case-mix system has 8 distinct, final groups and explains 30% of the variance in per diem costs. Our analyses indicate that this case-mix classification system could provide the foundation for a future prospective payment system that is centered around stability and equitability in the allocation of limited resources within this vulnerable population.
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