Hu, Jiun-RueyJiun-RueyHuYo, Chia-HungChia-HungYoLee, Hsin-YingHsin-YingLeeSu, Chin-HuaChin-HuaSuSu, Ming-YangMing-YangSuHuang, Amy HuaishiuanAmy HuaishiuanHuangLiu, YeYeLiuHsu, Wan-TingWan-TingHsuLee, MatthewMatthewLeeYEE-CHUN CHENCHIEN-CHANG LEE2022-03-032022-03-0320222055-2076https://scholars.lib.ntu.edu.tw/handle/123456789/596089Sepsis is the leading cause of in-hospital mortality in the United States (US). Quality improvement initiatives for improving sepsis care depend on accurate estimates of sepsis mortality. While hospital 30-day risk-standardized mortality rates have been published for patients hospitalized with acute myocardial infarction, heart failure, and pneumonia, risk-standardized mortality rates for sepsis have not been well characterized. We aimed to construct a sepsis risk-standardized mortality rate map for the United States, to illustrate disparities in sepsis care across the country.enhealthcare quality; machine learning; mortality; risk standardized mortality rate; sepsis[SDGs]SDG3journal article10.1177/20552076211072400350964092-s2.0-85123351701WOS:000748560900001https://api.elsevier.com/content/abstract/scopus_id/85123351701