The overuse of blood cultures in emergency departments leads to low yields and high numbers of contaminated cultures, which is associated with
increased diagnostics, unnecessary antibiotic usage and prolonged hospitalization. We hypothesize that using our blood culture prediction tool is noninferior
to current practice, can reduce (unnecessary) blood cultures by at least 30%, and can reduce the harmful effects to patients due to false positive
results of blood cultures (e.g., lowering unnecessary antibiotics, other diagnostic tests and the length of hospital stays).
We developed a blood culture prediction tool. This tool is a machine learning model to predict the outcome of blood cultures in the ED, and this model is
retrospectively and prospectively validated in various settings. The ABC study will test this tool in a non-inferiority randomized controlled trial. In the intervention group, the physician will follow the advice of our blood culture prediction tool. If the chance of a positive blood culture is < 5%, no blood culture analysis will be performed. If the chance of a positive blood culture is > 5%, the blood culture analysis will be performed as usual. In the control group, all patients will undergo a blood culture analysis.