Two billion catheters are placed annually worldwide. Of all the people requiring vascular access, nearly a quarter have Difficult Intravenous access (DIVA), a source of multiple punctures. The increased risk of haematomas, haemorrhages, infection, pain and associated trauma is responsible for increased human costs and economic impact.
To limit the risks posed by the DIVA, practitioners have solutions such as the per-bone line, other types of lines, and placement of peripheral venous catheter with ultrasound or transluminescence. However, these solutions are not always applicable, depending on the care situation (non-substitutable venous access, fragile patient, etc.) or on the technical platform (available personnel and training, configuration of the premises, available equipment). Moreover, these actions are often taken after failures, in a non-anticipated and non-consensual manner.
In order to assess the risk of DIVA, F.Van Loon et al developed in 2016, and then modified in 2018, a DIVA Scale (the A-DIVA Scale) which allows a rapid scoring upstream of peripheral venous catheter placement to classify patients according to the risk of DIVA.
Composed of five items (non-palpable and non-visible vein, diameter \< 3mm, history of DIVA, operator experience) worth one point each, the score allows three categories to be established: "low risk", "moderate risk", "high risk". The study showed that the proportion of first puncture failures increased with the risk of the patients (defined according to the categorized score).
The use of a tool such as the A-DIVA Scale is of interest if it allows the definition of actions to be taken in relation to the risk it identifies. In view of this, it appears essential to optimize the management of peripheral venous catheters, particularly for patients with DIVAs. The aim of this study is to develop a graduate and specific response to the issue of multiple punctures. Our project is to create and evaluate a specific algorithm, consisting of a risk assessment (the A-DIVA Scale) and a co-construct decision-making tree (the A-DIVA Tool). Built on the basis of objective clinical data collection and adapted to the possibilities and competencies, this new tool would bring real benefits to the patient in terms of safety (reduction of risks) and comfort (reduction of pain and duration of management), as well as a medico-economic benefit for the institutions. To date, such an algorithm does not exist and its beneficial effects have not been evaluated.