Factors Associated With In-Hospital Death Among Pneumonia Patients in US Hospitals From 2016~2019

Document Type : Original Article

Authors

1 Department of Health Administration and Management, College of Medical Science, Soonchunhyang University, Asan, Republic of Korea

2 Center for Healthcare Management Science, Soonchunhyang University, Asan, Republic of Korea

3 Department of Software Convergence, Soonchunhyang University, Asan, Republic of Korea

4 School of Pharmacy, University of Texas at El Paso, El Paso, TX, USA

5 Department of Pharmaceutical Sciences, Irma Lerma Rangel School of Pharmacy, Texas A&M University, College Station, TX, USA

Abstract

Background 
Pneumonia is one of the leading causes of hospital admission in the United States with a global health burden of about 6.8 million hospitalizations and 1.1 million deaths in patients over 65 years old in 2015. This study aimed to identify possible patient and hospital-related risk factors for in-hospital pneumonia death across US hospitals.

Methods 
The National Inpatient Sample (NIS) was used to identify nationwide pneumonia patients (n = 374 766, weighted n = 1 873 828) from 2016 to 2019. We examined the characteristics of the study sample and their association with in-hospital death. Multivariate survey logistic regression models were used to identify risk factors.

Results 
During the study periods, in-hospital death rates continuously decreased (2.45% in 2016 to 2.19% in 2019). Descriptive statistics showed that patient and hospital factors had varied in-hospital death rates. Survey logistic regression results suggested that male, very low income, non-Medicare, government hospitals, rural hospitals, and specific hospital regions were associated with higher in-hospital death rates than their reference groups.

Conclusion 
Socioeconomic factors, including income and insurance, are associated with pneumonia mortality. Census region, hospital ownership, and rural location are also related to in-hospital mortality. Such findings in underserved, impoverished, and rural areas to identify possible health disparities.

Keywords

References

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History

  • Receive Date: 13 May 2022
  • Revise Date: 20 April 2023
  • Accept Date: 09 July 2023
  • First Publish Date: 10 July 2023

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