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, Uri Obolski

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Article number1148
Pages (from-to)1148
JournalNature Communications
Issue number1
StatePublished - 1 Dec 2021


  • Anti-Bacterial Agents/therapeutic use
  • Bacterial Infections/drug therapy
  • Computational Biology
  • Drug Resistance, Bacterial
  • Drug Resistance, Microbial
  • Drug Resistance, Viral
  • Game Theory
  • Humans
  • Preventive Medicine/methods
  • Virus Diseases

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Biochemistry,Genetics and Molecular Biology
  • General Physics and Astronomy


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