Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT03883009 |
Other study ID # |
32003B_179500 |
Secondary ID |
|
Status |
Completed |
Phase |
|
First received |
|
Last updated |
|
Start date |
August 1, 2018 |
Est. completion date |
October 31, 2022 |
Study information
Verified date |
January 2023 |
Source |
University Hospital Inselspital, Berne |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
Surgical site infection (SSI) is the most common healthcare-associated infection,
multifactorial in nature, and a typical preventable harm. Many healthcare systems require
hospitals to determine the corresponding infection rates as a quality indicator and often
stipulate public reporting of these data. Several agencies, among them the World Health
Organization (WHO) and the U.S. Centers for Disease Control and Prevention (CDC), have issued
evidence-based prevention guidelines. Despite efforts in implementing best practice, SSI
continue to be a relevant complication of modern surgical procedures and generate enormous
costs for the healthcare system. Moreover, prevention guidelines acknowledge that the
evidence backing their recommendations is low to moderate in most cases, which is partly due
to the complexity of SSI pathogenesis.
Swissnoso, the Swiss expert group for infection prevention and hospital epidemiology,
oversees the nationwide collection of data on select procedures and the associated SSI. Since
the inception of this dedicated surveillance in 2009, more than 300'000 procedures have been
included and the corresponding patients were followed to ascertain SSIs. Although primarily
conceived as a national surveillance system and then used for public reporting starting in
2014, Swissnoso is a prime data source for better understanding the epidemiology of SSI.
Here, the investigators seek to raise the quality of evidence behind future prevention
guidelines. For this purpose, the investigators will move from a risk factor analysis for SSI
(of which a substantial part occurs after patient discharge from the hospital, rendering
surveillance difficult) to the collection of additional data (in order to better characterize
certain determinants of SSI and their recognition) and, finally, to a mathematical model
(which will simulate the probability of developing SSI so the investigators can test what may
modulate this risk).
Description:
Aim 1: Descriptive epidemiology and risk factors for (post-discharge) SSI: using the
Swissnoso SSI Surveillance data, the investigators will determine patient and institution
level risk factors for SSI in Switzerland (with a focus on those occurring post-discharge),
explore protective factors (such as antimicrobial prophylaxis and its timing), and describe
the epidemiology of SSI in terms of time of occurrence, microbiology, severity, patient
outcome, and variation by procedure type, case-mix, and hospital size.
Aim 2: Determinants of SSI: The investigators will investigate determinants of SSI in the
following three areas:
A) The surveillance system itself and how the thoroughness of the surveillance process
correlates with reported SSI rates; B) The operating room ventilation system and how its
parameters correlate with SSI rates; and C) A healthcare institution's perceived culture of
safety and how it correlates with infection rates.
To do so, the investigators will enhance and complement the Swissnoso data with new
information at the institution level.
Aim 3: A mathematical model of surgical site infection: the investigators will construct a
mathematical model that simulates SSI pathogenesis based on data from Swissnoso and other
sources, and assesses the impact of different preventive measures. Interventions will be
ranked according to the simulated reduction of SSI rates in Switzerland.