Risk-standardized sepsis mortality map of the United States. (January 2022)

• Record Type: Journal Article
• Authors: Hu, Jiun-Ruey; Yo, Chia-Hung; Lee, Hsin-Ying; Su, Chin-Hua; Su, Ming-Yang; Huang, Amy Huaishiuan; Liu, Ye; Hsu, Wan-Ting; Lee, Matthew; Chen, Yee-Chun; Lee, Chien-Chang
• Is Part Of: Digital health. Volume 8(2022)
• Publication Date: 2022-01
• Subjects: sepsis -- risk standardized mortality rate -- machine learning -- mortality -- healthcare quality; Medical care -- Data processing -- Periodicals; Medical informatics -- Periodicals; 362.10285
• DOI: 10.1177/20552076211072400
• Languages: English
• ISSNs: 2055-2076

Abstract

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.