Learning your ABDs: Variation in health care utilization across Kansas Medicaid disability groups.

Abstract Background State Medicaid programs provide critical health care access for persons with disabilities and older adults. Aged, Blind and Disabled (ABD) programs consist of important disability subgroups that Medicaid programs are not able to readily distinguish. Objective/hypothesis The purpose of this project was to create an algorithm based principally on eligibility and claims data to distinguish disability subgroups and characterize differences in demographic characteristics, disease burden, and health care expenditures. Methods We created an algorithm to distinguish Kansas Medicaid enrollees as adults with intellectual or developmental delays (IDD), physical disabilities (PD), severe mental illness (SMI), and older age. Results For fiscal year 2009, our algorithm separated 101,464 ABD enrollees into the following disability subgroups: persons with IDD (19.6%), persons with PD (21.0%), older adults (19.7%), persons with SMI (32.8%), and persons not otherwise classified (6.9%). The disease burden present in the IDD, PD, and SMI subgroups was higher than for older adults. Home- and community-based services expenditures were common and highest for persons with IDD and PD. Older adults and persons with SMI had their highest expenditures for long-term care. Mean Medicaid expenditures were consistently higher for adults with IDD followed by adults with PD. Conclusions There are substantial differences between disability subgroups in the Kansas Medicaid ABD population with respect to demographics, disease burden, and health care expenditures. Through this algorithm, state Medicaid programs have the opportunity to collaborate with the most closely aligned service providers reflecting needed services for each disability subgroup