Healthcare-associated infections (HAIs) are used as a measure for federal value-based payment programs. Using data for 2015, the Centers for Disease Control and Prevention (CDC) developed newer risk adjustment models to calculate the standardized infection ratio (SIR) for various infections occurring in hospitals. New national baselines were set to compare performance among medical facilities and states. Despite adjustments for various facility-level factors that contribute to HAI risk, there are ongoing concerns that SIR calculations do not adequately account for non-hospital risk factors that have been linked to clinical outcomes. This explanatory study evaluates state-level data using simple linear regression to determine relationships between the standardized infection ratio (SIR) for methicillin-resistant Staphylococcus aureus (MRSA) bacteremia and several socioeconomic and geographic factors. Bivariate analysis produced significant correlation between SIR and high school education, with states exhibiting lower SIR relative to the percent of adults who completed high school. Higher SIRs were found relative to the percent of state populations subjected to poverty, obesity, and diagnosis of diabetes. Percent of nonprofit hospitals, adults with bachelor’s degrees, and rural residents were not significantly correlated with state measures of MRSA bacteremia. These findings can help guide efforts to reduce HAIs, improve safety of care, and advance population health efforts. The results from this study reinforce the notion that non-hospital factors may have significant effects on the incidence of MRSA bacteremia events occurring in hospitalized patients. Current risk adjustment models that predict MRSA bacteremia events for quality reporting purposes may not adequately account for these risk factors. The present study highlights some ways that hospitals, patients, and policymakers can work together to address social risk factors as a strategy for promoting better and safer care, and healthier communities. This study investigates aspects of the bigger picture of health care quality, performance measurement, and population health. This “feel for the whole” underscores the implications on state performance in infection prevention in the context of socioeconomic and medical vulnerabilities. The study emphasizes the need for greater multidisciplinary collaboration to address community health needs and reduce social and medical disparities.