Health care-associated infections (HAIs) are a major cause of morbidity and mortality, but little is known about whether structural factors impacting race and rurality are associated with HAI and subsequent outcomes. To evaluate the association of race and rurality, which are proxies for structural disadvantage, with HAI and subsequent outcomes. This cohort study was conducted at 3 US urban and suburban hospitals. Participants were adults aged 18 years or older admitted for 48 hours or longer from January 1, 2017, to August 31, 2020. Statistical analysis was performed from November 2022 to April 2024. Patient race and rurality status were defined as the combination of race (Black or White) and residence (urban or rural per patient zip code). HAI was defined as a positive culture from a urine, blood, or respiratory specimen obtained 48 hours or longer after admission. To determine the association of race and rurality with HAIs, multivariable generalized estimating equations models were used to account for clustering of admissions by patient. Among patients with HAI admissions, similar models examined post-HAI intensive care unit admission and in-hospital death. Among 214 955 patients admitted to the hospital (median [IQR] age, 63 [51-73] years; 108 679 female patients [50.6%]; 72 490 Black patients [33.7%]; 142 465 White patients [66.3%]), recognized HAIs occurred during 6699 (3.1%). Compared with White urban patients, Black urban patients had a decreased risk of HAI (adjusted relative risk [aRR], 0.81; 95% CI, 0.75-0.87), White rural patients had an increased risk of HAI (aRR, 1.12; 95% CI, 1.05-1.20), and Black rural patients (aRR, 1.08; 95% CI, 0.81-1.44) had a similar risk of HAI. Among patients with HAI admissions, Black rural patients had an increased risk of intensive care unit admission (aRR, 1.92; 95% CI, 1.16-3.17) and in-hospital death (aRR, 1.78; 95% CI, 1.26-2.50). White rural and Black urban patients had outcomes similar to those of White urban patients. This cohort study of hospitalized adults identified inequities related to race and rurality in HAIs and adverse outcomes from HAIs. These findings suggest that factors such as structural racism and disinvestment in rural communities may be associated with individual HAI risk and post-HAI outcomes. Future work to further understand the reasons underpinning these disparities and methods to address structural factors through policy and process changes are critical to eliminate health inequities.
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