A game theoretic approach reveals that discretizing clinical information can reduce antibiotic misuse

Maya Diamant, Shoham Baruch, Eias Kassem, Khitam Muhsen, Dov Samet, Moshe Leshno and Uri Obolski ()
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Maya Diamant: Tel Aviv University
Shoham Baruch: Tel Aviv University
Eias Kassem: Hillel Yaffe Medical Center
Khitam Muhsen: Tel Aviv University
Moshe Leshno: Tel Aviv University
Uri Obolski: Tel Aviv University

Nature Communications, 2021, vol. 12, issue 1, 1-13

Abstract: Abstract The overuse of antibiotics is exacerbating the antibiotic resistance crisis. Since this problem is a classic common-goods dilemma, it naturally lends itself to a game-theoretic analysis. Hence, we designed a model wherein physicians weigh whether antibiotics should be prescribed, given that antibiotic usage depletes its future effectiveness. The physicians’ decisions rely on the probability of a bacterial infection before definitive laboratory results are available. We show that the physicians’ equilibrium decision rule of antibiotic prescription is not socially optimal. However, we prove that discretizing the information provided to physicians can mitigate the gap between their equilibrium decisions and the social optimum of antibiotic prescription. Despite this problem’s complexity, the effectiveness of the discretization solely depends on the type of information available to the physician to determine the nature of infection. This is demonstrated on theoretic distributions and a clinical dataset. Our results provide a game-theory based guide for optimal output of current and future decision support systems of antibiotic prescription.

Date: 2021
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DOI: 10.1038/s41467-021-21088-5

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