Economic benefits of safety-engineered sharp devices in Belgium - a budget impact model

Measures to protect healthcare workers where there is risk of injury or infection from medical sharps became mandatory in the European Union (EU) from May 2013. Our research objective was to estimate the net budget impact of introducing safety-engineered devices (SEDs) for prevention of needlestick injuries (NSIs) in a Belgian hospital.

A 5-year incidence-based budget impact model was developed from the hospital inpatient perspective, comparing costs and outcomes with SEDs and prior-used conventional (non-safety) devices. The model accounts for device acquisition costs and costs of NSI management in 4 areas of application where SEDs are currently used: blood collection, infusion, injection and diabetes insulin administration. Model input data were sourced from the Institut National d'Assurance Maladie-Invalidité, published studies, clinical guidelines and market research. Costs are discounted at 3%.

For a 420-bed hospital, 100% substitution of conventional devices by SEDs is estimated to decrease the cumulative 5-year incidence of NSIs from 310 to 75, and those associated with exposure to blood-borne viral diseases from 60 to 15. Cost savings from managing fewer NSIs more than offset increased device acquisition costs, yielding estimated 5-year overall savings of €51,710. The direction of these results is robust to a range of sensitivity and model scenario analyses. The model was most sensitive to variation in the acquisition costs of SEDs, rates of NSI associated with conventional devices, and the acquisition costs of conventional devices.

NSIs are a significant potential risk with the use of sharp devices. The incidence of NSIs and the costs associated with their management can be reduced through the adoption of safer work practices, including investment in SEDs. For a Belgian hospital, the budget impact model reports that the incremental acquisition costs of SEDs are offset by the savings from fewer NSIs. The availability of more robust data for NSI reduction rates, and broadening the scope of the model to include ancillary measures for hospital conversion to SED usage, outpatient and paramedic device use, and transmission of other blood-borne diseases, would strengthen the model.