Healthcare-associated infections (HAIs) are among the most common and significant patient safety issues posing great threats to public health. One in every 25 inpatients in the United States experiences a HAI. Because they have continuously been a major reason for increased morbidity and mortality in healthcare facilities, increased attention to understanding the spread of HAIs is an urgently needed. Therefore, the purpose of this dissertation, was to examine the risk factors for two of the most common HAIs (surgical site infection [SSI] and Clostridioides difficile infection [CDI]), using multiple methodological approaches.
Chapter 1 provides an overview of HAIs, the risk factors identified from the previous literature, and the necessity of different methodological approaches to identify the risk of HAIs. Chapter 2 is an integrative review synthesizing the findings from seven published studies examining the association between the development of pocket hematoma and the risk of wound infection in individuals with cardiovascular implantable electronic devices. Chapter 3 is a summary of a retrospective cohort study using machine learning techniques—logistic regression, decision tree, and support vector machine approaches—to build predictive models of SSI among individuals with permanent pacemakers, followed by a comparison of the predictive abilities of the three algorithms. Chapter 4 describes a retrospective matched case-control study to examine (1) temporal changes in the incidence of community or hospital-acquired CDI, (2) the risk factors for hospital-acquired CDI including individual-host factors and pharmacological-related factors, and (3) temporal changes in the risk factors for hospital-acquired CDI. Lastly, Chapter 5 summarizes and synthesizes the findings of the studies included in this dissertation, the strengths and limitations of the studies, implications for public health and clinical practice, advanced studies on methodology, and future research. In conclusion, this dissertation adds comprehensive knowledge regarding the associations between risk factors and HAIs by identifying reliable risk factors measured in various ways and applying various methodological approaches.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-q1kg-sw48 |
| Date | January 2020 |
| Creators | Song, Jiyoun |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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