Risk-standardized sepsis mortality map of the United States

Author:

Hu Jiun-Ruey1,Yo Chia-Hung2,Lee Hsin-Ying3,Su Chin-Hua4,Su Ming-Yang5,Huang Amy Huaishiuan46,Liu Ye7,Hsu Wan-Ting8,Lee Matthew9,Chen Yee-Chun310,Lee Chien-Chang411ORCID

Affiliation:

1. Department of Internal Medicine, Yale School of Medicine, USA

2. Department of Emergency Medicine, Far Eastern Memorial Hospital, Taiwan

3. Department of Medicine, College of Medicine, National Taiwan University, Taiwan

4. Department of Emergency Medicine, National Taiwan University Hospital, Taiwan

5. Department of Surgery, Chang Gung Memorial Hospital, Taiwan

6. Department of Internal Medicine, Taipei City Hospital, Renai Branch, Taiwan

7. Department of Health Care Organization and Policy, University of Alabama at Birmingham, School of Public Health, USA

8. Department of Epidemiology, Harvard T.H. Chan School of Public Health, USA

9. Medical Wizdom, LLC, USA

10. Department of Internal Medicine,National Taiwan University, Taiwan

11. Center of Intelligent Healthcare, National Taiwan University Hospital, Taiwan

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.

Funder

Taiwan Ministry of Science and Technology

Publisher

SAGE Publications

Subject

Health Information Management,Computer Science Applications,Health Informatics,Health Policy

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