Assessing Impact of Affordable Care Act Implementation on Routine Vaccination Rates

The 2014 Affordable Care Act (ACA) was a pioneering movement towards federally financed expansion of state Medicaid programs. Based on the interplay of state and federal departments, the ACA-based expansion of Medicaid programs witnessed a staggered roll out with several states as early and late implementers. Given that the goals of this program was to encourage preventative care and decrease preventable morbidity, the policy impact on vaccination provides an insight into behavior changes. Through using data from 2010-2020 Behavioral Risk Factor Surveillance System (BRFSS) published by the Centers for Disease Control and Prevention (CDC), the impact of ACA implementation on routine vaccination (Influenza, Shingles, Pneumonia, HPV, Tetanus) may be discerned. The data was analyzed using the staggered difference in differences model introduced by Callaway and Sant'Anna using the not yet treated group as the control to narrow in on the effect of ACA implementation. The analysis revealed mixed results in terms of the impact of ACA implementation. Influenza, Pneumonia, Tetanus immunizations showed a significant increase after ACA implementation (p<0.05). On the other hand, HPV and Shingles immunizations displayed a statistically significant decrease following the ACA expansion. The data suggested that early ACA expansion groups saw a greater positive effect as compared to the 2014 and late implementers. This may be due to the delay in effect realization following ACA expansion, which may have led to the ACA vaccination improvements to not appear in the observation period. The results from this study exemplify the complexities involved with increasing adherence to recommended health guidelines. The prior literature on the ACA impact generally saw an increase in preventative care measures alongside an increase in primary care coverage. However, this study qualifies the benefits through suggesting an unequal impact based on vaccination type. This may be due to the increasing prevalence of misinformation, provider choice, and patient personal choice. The implications from this study may be useful to inform public health marketing guidelines that may disproportionately improve vaccination rates.