Title

A Predictive Model of Days from Infection to Discharge in Patients with Healthcare Associated Urinary Tract Infections (HAUTI): A Structural Equation Modelling Approach

Document Type

Article

Publication Date

8-2017

Publication Details

This article was originally published as:

Mitchell, B. G., Anderson, M., & Ferguson, J. K. (2017). A predictive model of days from infection to discharge in patients with healthcare associated urinary tract infections (HAUTI): A structural equation modelling approach. Journal of Hospital Infection, doi: 10.1016/j.jhin.2017.08.006.

ISSN: 0195-6701

Reportable Items

C1

Abstract

Objectives

To test the relationships between the size of hospital, age and patient co-morbidity on days from admission to infection and days from infection to discharge in patients with a healthcare-associated urinary tract infection (HAUTI), using structural equation modelling (SEM).

Methods

A noncurrent cohort study in eight hospitals in New South Wales, Australia. All patients admitted to the hospital for more than 48 hours and who acquired a HAUTI were included.

Results

From the 162,503 eligible patient admissions, 2,8 21 (1.73%) acquired a HAUTI. SEM showed that the proposed model had acceptable fit indices for the combined sample (GFI = 1.00; AGFI = 1.00; NFI = 1.00 CFI = 1.00 and RMSEA = 0.000). The main findings showed age of patient had a direct association with days from admission to infection and days from infection to discharge respectively. Patient co-morbidity had direct links to the variables days from admission to infection and days from infection to discharge. Multigroup analysis indicated that the age of male patients was more influential on the factor days from admission to infection when compared to female patients. Furthermore, the number of co-morbidities was significantly more influential on days from admission to infection in male patients than female patients.

Conclusion

As the first reported paper to use SEM to explore a healthcare-associated infection and the predictors of days from infection to discharge in hospital, we can confirm that accounting for the timing of infection during hospitalisation is important and that patient co-morbidity influences the timing of infection

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