Fighting drug-resistant bacteria requires prescribing fewer antibiotics. VALUE-DX lay out the economic calculations behind decisions to use point-of-care tests
This article is based on a paper that appeared in the Journal BMC Health Economics Review
Each individual doctor differs in their level of uncertainty about whether or not to prescribe an antibiotic. When they feel very certain that a patient’s symptoms are caused by a bacterial infection, an antibiotics prescription is often made promptly and confidently. The problem arises when the level of certainty dips below a certain threshold. In these cases, point-of-care tests are a worthy investment for doctors and wider society: beyond avoiding unnecessary prescriptions, they increase doctors’ confidence in their diagnosis, while also sensitising them to the risks of getting it wrong.
'Internalising' the costs of over-prescription
Those are the conclusions of a study carried out by the IMI project VALUE-DX, as laid out in a paper in Health Economics Review. The authors’ cost-benefit calculations describe the level of uncertainty that would drive a hypothetical subset of physicians to use a point-of-care test, as well as the considerations of a hypothetical manufacturer trying to figure out how much doctors might be willing to pay for the equipment. They created an economic model that frames the dilemma in purely monetary terms, in the hope that they can once and for all demonstrate the real-world value of rapid diagnosis in primary care.
Ultimately, using point-of-care tests cuts down on the absolute number of prescriptions. In addition, doctors who use them, the authors claim, tend to become more cognisant (or, in economic terms, they ‘internalise’) the wider consequences of antibiotic over-prescription.
“The model provides a useful framework for analysing the decision-making processes (patient stratification and treatments) of physicians treating infectious respiratory diseases and the personalisation of treatment. Formally, our analysis is similar to other recent stylised models dealing with personalized medicine.”
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