Decision support-tools for early detection of infection in older people (aged> 65 years): a scoping review.

BACKGROUND: Infection is more frequent, and serious in people aged > 65 as they experience non-specific signs and symptoms delaying diagnosis and prompt treatment. Monitoring signs and symptoms using decision support tools (DST) is one approach that could help improve early detection ensuring timely treatment and effective care. OBJECTIVE: To identify and analyse decision support tools available to support detection of infection in older people (> 65 years). METHODS: A scoping review of the literature 2010-2021 following Arksey and O'Malley (2005) framework and PRISMA-ScR guidelines. A search of MEDLINE, Cochrane, EMBASE, PubMed, CINAHL, Scopus and PsycINFO using terms to identify decision support tools for detection of infection in people > 65 years was conducted, supplemented with manual searches. RESULTS: Seventeen papers, reporting varying stages of development of different DSTs were analysed. DSTs largely focussed on specific types of infection i.e. urine, respiratory, sepsis and were frequently hospital based (n = 9) for use by physicians. Four DSTs had been developed in nursing homes and one a care home, two of which explored detection of non- specific infection. CONCLUSIONS: DSTs provide an opportunity to ensure a consistent approach to early detection of infection supporting prompt action and treatment, thus avoiding emergency hospital admissions. A lack of consideration regarding their implementation in practice means that any attempt to create an optimal validated and tested DST for infection detection will be impeded. This absence may ultimately affect the ability of the workforce to provide more effective and timely care, particularly during the current covid-19 pandemic.

Improving early detection of infection in nursing home residents in South Africa.

This paper sets out key challenges related to detection and management of infection in nursing home residents, and then explores the situation in South Africa, and use of decision support tools as a mechanism to improve this area of practice. In line with global trends, concerns have been raised about the rapidly increasing aging population in South Africa and the ability of the current healthcare system to keep pace with patient demand, particularly nursing home residents. Nursing home residents, who often exhibit atypical signs and symptoms, are at increased risk of infection and unplanned admissions, which account for 65% of all bed days, and cost the US healthcare economy more than a trillion dollars a year. Evidence suggests that the current workforce in South Africa receive limited training in this area and are largely unprepared to meet the demands of the aging population. Building the capacity and skills of the workforce in South Africa is one approach that could help to improve the early detection of infection and assist the nursing home workforce to provide more effective and timely care, particularly during the current COVID-19 pandemic. Decision support tools, such as the Early Detection of Infection Scale, can help ensure consistency and ensure more timely treatment, minimising unplanned admissions and healthcare expenditure. However, the potential benefits or indeed how easily this could be integrated in to nursing homes in South Africa is unknown. An important first step, as in other parts of the world, is therefore to explore views and opinions of how infections are detected and managed in practice by nurses, care workers and managers in nursing homes.