Clinical trial NCT03883009: Understanding the Drivers of Surgical Site Infection: Investigating and Modeling the Swissnoso Surveillance Data
Official title: Understanding the Drivers of Surgical Site Infection: Investigating and Modeling the Swissnoso Surveillance Data
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Surgical Site Infection
Keywords: Epidemiology
Modeling
Risk factors
Surgical site infections
Lead sponsor: Insel Gruppe AG, University Hospital Bern
Sponsor class: OTHER
Collaborators: name: Swiss Patient Safety Foundation
name: Lucerne University of Applied Sciences and Arts
name: University of Bern
name: Swissnoso National Center for Infection Control
name: Central Institute of Valais Hospitals
name: University Hospital, Basel, Switzerland
name: Swiss National Science Foundation
First posted: 2019-03-20
Enrollment: 318000
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: OTHER
Time perspective: OTHER
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Swissnoso SSI Surveillance: Nationwide surveillance system with 172 participating hospitals collecting data on patients who undergo select surgeries as defined by Swissnoso. Since 2009, information on 318'000 surgical procedures has been captured (database extract February 2017).

Brief 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).

Detailed 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.

Eligibility criteria: Inclusion Criteria:

* All cases included in the Swissnoso SSI Surveillance system are eligible for the analyses.

Exclusion Criteria:

* If a patient opts to withdraw consent to participating in the Swissnoso SSI Surveillance, his/her data is removed from the surveillance dataset.

Primary outcomes:
measure: Surgical site infection rate
timeFrame: During 30 days after surgery (or 12 months after surgery with implants)
Secondary outcomes:
Other outcomes:
Locations:
city: Bern
country: Switzerland
facility: University Hospital Bern
Study officials:
affiliation: University of Bern
name: Jonas Marschall, Prof.Dr.med.
role: PRINCIPAL_INVESTIGATOR
References: