Establishing benchmarks to understand hospital utilization following Medicaid expansion under the Affordable Care Act
Data and Methods. We obtained hospital use data from the Healthcare Cost and Utilization Project (HCUP) 2010 State Inpatient Databases (SID) and State Emergency Department Databases (SEDD). We obtained state-level data on Medicaid program characteristics and population demographics and health status from Centers for Medicare & Medicaid Services (CMS) Medicaid statistics, American Community Survey, and Behavioral Risk Factor Surveillance Survey. We first examined whether hospital utilization rates differed based on states’ stance on Medicaid expansion. We standardized the hospital use metrics by computing separate index values for the Medicaid and uninsured population metrics relative to the national mean so that all measures had similar scale. We then examined which state-level Medicaid program, demographic, and health status characteristics were related to the states’ expansion stance. For each specific characteristic found to be strongly related to states’ likelihood to expand, we then separated states into terciles —based on values for each characteristic — in order to estimate the relationship of that characteristic to hospital utilization. We estimated current Medicaid and uninsured utilization rates for each tercile of these characteristics.
Principal Findings. We found that several state health system infrastructure characteristics were strongly related to both expansion likelihood and hospital utilization. In particular, in states highly likely to adopt Medicaid expansion in 2014, we observed higher levels of Medicaid managed care organization (MMCO) penetration, a lower primary care physician (PCP) supply challenge, a lower level of primary care case management (PCCM), and a smaller expansion population size relative to the current Medicaid population. We also found that in those states that are currently committed to Medicaid expansion had substantially lower hospital inpatient and emergency department (ED) use among Medicaid-covered patients compared to states that have not committed to expand. For example, the states that are already committed can expect a post-expansion ED visit rate between 316 and 607 per 1,000 Medicaid enrollees, while the states currently leaning against expansion could expect a post-expansion ED visit rate between 541 and 991 per 1,000 Medicaid enrollees, given the characteristics of the current Medicaid programs and Medicaid and uninsured populations in those states.
Conclusions. Our results revealed a lower impact of Medicaid expansion on hospital utilization among states that have elected to expand than among states currently unlikely to expand. This suggests that states with a certain infrastructure may be better able to accommodate Medicaid expansion and will experience less impact to their hospital system.