Surgical site infection
Preventing SSIs: the butterfly effect
Dedicated to reducing the risk of surgical site infections (SSIs), OneTogether recently hosted a conference at the National Conference Centre, Birmingham. High on the agenda was the potential of AI in predicting risk, the role of care bundles in SSI prevention, and the evidence-based resources available that can help guide clinical practice. Louise Frampton reports.
“There is no single solution to solve the problem of surgical site infection”, was a key message of OneTogether’s recent conference. The OneTogether programme was initiated as a quality improvement collaborative with the aim of supporting the adoption of best practice throughout the patient’s surgical journey. The poignant symbol of this initiative is the butterfly. With the ‘butterfly effect’, small changes can lead to much larger changes and this is the founding principle behind the programme. Everyone can play their part and collective action can make a difference. In this way, small, individual actions can become “amplified to global proportions”. Experts in infection prevention and
perioperative practice gathered at the conference to discuss the challenges and share best practices around prevention. Hot topics ranged from: ‘The power of prediction’, ‘Facilitators and barriers to the implementation of care bundles’, ‘Rituals and behaviours in the operating theatre guidelines’, ‘How the National Wound Care Strategy programme is addressing
intelligence. He pointed out that SSIs remain a burden, globally, in terms of morbidity and mortality for patients, as well as in terms of the financial impact on healthcare organisations. This is in addition to the reputational repercussions for healthcare providers. He asked the question, why do SSIs continue
surgical wound complications’, ‘Developments in incision wound care management’, and much more... Providing the opening address, Bill Kilvington,
Patient Safety Lead, from The College of Operating Department Practitioners, explained that OneTogether is a partnership between leading professional organisations with an interest in the prevention of SSI – these include: the Infection Prevention Society, the Association for Perioperative Practice, the Central Sterilising Club, the College of Operating Department Practitioners, and the Royal College of Nursing, with sponsorship provided by 3M. Dr. James Price, Senior Lecturer in Infection,
Brighton and Sussex Medical School, discussed the ‘power of prediction’ and the role of artificial
to occur despite broad evidence-based infection prevention measures that we put in place? “Bacteria that cause disease continue to
evolve and we see antimicrobial resistance starting to confound how we manage infections; we see that our patients are changing and acquiring new risk factors for developing infections; we see our surgical techniques are changing, and we all have our own challenges with built environments... It is probably a combination of all these factors. Part of the challenge is for us to keep up, understand, implement and utilise these new potential factors in order to optimise and target our Infection Prevention and Control (IPC) approaches,” he commented. He added that we are starting to see
new technologies that may help to support prediction in a more meaningful way. “We use prediction all the time in our daily
practice – it is not a new thing,” he pointed out. Dr. Price added that we already consider patient factors and try to mitigate risk by optimising blood pressure and blood glucose, for example, as well as by identifying and suppressing resistant organisms – such as MRSA. These actions all help to reduce SSIs, but may fail to identify and address all risks. To address this, various approaches to risk scoring have been developed to better understand and support SSI prevention. Dr. Price pointed out that there are challenges associated with these, including the use of retrospective data. Often, data has to be manually inputted, which can also be time consuming. These approaches do not take into account new risk
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