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Treatment strategies that target host entry factors have proven an effective means of impeding viral entry in HIV and may be more robust to viral evolution than drugs targeting viral proteins directly. High-throughput functional screens provide an unbiased means of identifying genes that influence the infection of host cells, while retrospective cohort analysis can measure the real-world, clinical potential of repurposing existing therapeutics as antiviral treatments. Here, we combine these two powerful methods to identify drugs that alter the clinical course of COVID-19 by targeting host entry factors. We demonstrate that integrative analysis of genome-wide CRISPR screening datasets enables network-based prioritization of drugs modulating viral entry, and we identify three common medications (spironolactone, quetiapine, and carvedilol) based on their network proximity to putative host factors. To understand the drugs' real-world impact, we perform a propensity-score-matched, retrospective cohort study of 64,349 COVID-19 patients and show that spironolactone use is associated with improved clinical prognosis, measured by both ICU admission and mechanical ventilation rates. Finally, we show that spironolactone exerts a dose-dependent inhibitory effect on viral entry in a human lung epithelial cell line. Our results suggest that spironolactone may improve clinical outcomes in COVID-19 through tissue-dependent inhibition of viral entry. Our work further provides a potential approach to integrate functional genomics with real-world evidence for drug repurposing.