Risk-standardized sepsis mortality map of the United States

被引:2
|
作者
Hu, Jiun-Ruey [1 ]
Yo, Chia-Hung [2 ]
Lee, Hsin-Ying [3 ]
Su, Chin-Hua [4 ]
Su, Ming-Yang [5 ]
Huang, Amy Huaishiuan [4 ,6 ]
Liu, Ye [7 ]
Hsu, Wan-Ting [8 ]
Lee, Matthew [9 ]
Chen, Yee-Chun [3 ,10 ]
Lee, Chien-Chang [4 ,11 ]
机构
[1] Yale Sch Med, Dept Internal Med, New Haven, CT USA
[2] Far Eastern Mem Hosp, Dept Emergency Med, New Taipei, Taiwan
[3] Natl Taiwan Univ, Coll Med, Dept Med, Taipei, Taiwan
[4] Natl Taiwan Univ Hosp, Dept Emergency Med, Taipei, Taiwan
[5] Chang Gung Mem Hosp, Dept Surg, Taoyuan, Taiwan
[6] Taipei City Hosp, Renai Branch, Dept Internal Med, Taipei, Taiwan
[7] Univ Alabama Birmingham, Sch Publ Hlth, Dept Hlth Care Org & Policy, Birmingham, AL USA
[8] Harvard TH Chan Sch Publ Hlth, Dept Epidemiol, Boston, MA USA
[9] Med Wizdom LLC, Boston, MA USA
[10] Natl Taiwan Univ, Dept Internal Med, Taipei, Taiwan
[11] Natl Taiwan Univ Hosp, Ctr Intelligent Healthcare, Taipei, Taiwan
来源
DIGITAL HEALTH | 2022年 / 8卷
关键词
sepsis; risk standardized mortality rate; machine learning; mortality; healthcare quality; ACUTE MYOCARDIAL-INFARCTION; NATIONAL PATTERNS; EARLY PREDICTION; HEART-FAILURE; OUTCOMES; CARE; IMPLEMENTATION; READMISSION; UPDATE; VOLUME;
D O I
10.1177/20552076211072400
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Objective Sepsis 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. Methods This cross-sectional study included adults from the US Nationwide Inpatient Sample who were hospitalized with sepsis between 1 January 2010 and 30 December 2011. Hospital-level risk-standardized mortality rates were calculated using hierarchical logistic modelling, and were risk-adjusted with predicted mortality derived from (1) the Sepsis Risk Prediction Score, a logistic regression model, and (2) gradient-boosted decision trees, a supervised machine learning (ML) algorithm. Results Among 1,739,033 adults hospitalized with sepsis, 50% were female, and the median age was 71 years (interquartile range: 58-81). The national median risk-standardized mortality rate for sepsis was 18.4% (interquartile range: 17.0, 21.0) by the boosted tree model, which had better discrimination than the Sepsis Risk Prediction Score model (C-statistic 0.87 and 0.78, respectively). The highest risk-standardized mortality rates were found in Wyoming, North Dakota, and Mississippi, while the lowest were found in Arizona, Colorado, and Michigan. Conclusions Wide variation exists in sepsis risk-standardized mortality rates across states, representing opportunities for improvement in sepsis care. This represents the first map of state-level variation of risk-standardized mortality rates in sepsis.
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页数:13
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