ArticleNature communications2021
A game theoretic approach reveals that discretizing clinical information can reduce antibiotic misuse.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Self-carrier nanodrugs with dual antibacterial agents to overcome tobramycin resistance in multidrug-resistantBioactive materials · 2026Article
- Empiric treatment and probability estimates before and after a decision support system intervention in a sore throat setting: a scenario-based survey study.BMC infectious diseases · 2025Article
- Barriers to the widespread adoption of diagnostic artificial intelligence for preventing antimicrobial resistance.Scientific reports · 2025Article
- Patterns and Drivers of Antifungal Prescribing in Acute Leukemia: A Retrospective Cohort Study.Open forum infectious diseases · 2024Article
- Game-theoretic analysis of governance and corruption in China's pharmaceutical industry.Frontiers in medicine · 2024Article
- Knowledge, attitudes, and practices among physicians and pharmacists toward antibiotic use in sepsis.Frontiers in medicine · 2024Article
- Prediction of ciprofloxacin resistance in hospitalized patients using machine learning.Communications medicine · 2023Article
- PCL/Gelatin/Graphene Oxide Electrospun Nanofibers: Effect of Surface Functionalization on In Vitro and Antibacterial Response.Nanomaterials (Basel, Switzerland) · 2023Article
- Combining data discretization and missing value imputation for incomplete medical datasets.PloS one · 2023Article
- A game-theoretic model for the classification of selected oil companies' price changes.PeerJ. Computer science · 2023Article
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Authors and funding
7 authors.
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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.
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