Surgical site infections (SSIs) are consistently identified as the most frequent type of healthcare-associated infection (HAI) in low- and middle-income countries (LMICs; WHO, 2016) and they are associated with considerable morbidity, mortality, and financial burden (Cassini et al, 2016). SSIs have a negative impact on physical and mental health, and may lead to a loss of productivity (Badia et al, 2017). Additionally, in response to the rising incidence of antimicrobial resistance (AMR), antimicrobial stewardship (AMS) strategies are essential to reduce antibiotic overuse within post-operative management.
Preventing SSIs from occurring in the first instance involves pre-, intra-, and post-operative initiatives alongside a robust surveillance system to measure rates of SSI. There is a wealth of evidence to suggest that surveillance is critical to drive good clinical practice and reduce rates of SSI (Wilson, 2013; Sandy-Hodgetts et al, 2020). Moreover, evidence reveals that gaps in care can leave patients feeling disconnected from their healthcare providers, and that engaged patients can benefit from improved clinical outcomes and emotional health, and reduced healthcare utilisation (Sanger et al, 2014).
The UK Health Security Agency (UKHSA) programme has surveillance data on almost 2.5 million operations and more than 50,000 SSIs since its inception in 1997, and recognition of the national service could draw attention and resources to support monitoring and prevention of SSI.
SSI monitoring requires an active patient-focused approach to promote consistency in the patient care journey from surgery to community. Post-discharge data collection is an essential part of SSI monitoring that can be conducted at outpatient clinics or in primary care by surgeons, general practitioners and surveillance teams, or by patients themselves using self-assessment questionnaires (Tanner et al, 2013).
This document focuses on surgical wounds that have been primarily closed, rather than open wounds healing by secondary intention. Obtaining SSI surveillance data that is sufficiently accurate to drive improvement is challenging, as it is a resource-heavy activity involving correct infection identification and recording as per local surveillance systems (Wilson, 2017). Surveillance methods should be used to detect SSI during the post-operative hospital stay and post-discharge. Rates of SSI should be regularly reported to those in the surgical team who can take action to ensure that best practice is achieved to prevent SSI.
The purpose of this Best Practice Statement is to provide multidisciplinary teams with practical tips to help integrate surveillance within routine practice and prevent further infections.
