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Updated: Jun 6, 2025

Antimicrobial Synergy Testing by the Inkjet Printer-assisted Automated Checkerboard Array and the Manual Time-kill Method
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Complementarities between algorithmic and human decision-making: The case of antibiotic prescribing.

Michael Allan Ribers1, Hannes Ullrich1,2

  • 1Department of Economics, University of Copenhagen, Copenhagen, Denmark.

Quantitative Marketing and Economics
|November 25, 2024
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Summary

Full automation of artificial intelligence (AI) in prescribing antibiotics is ineffective. Optimal delegation of decisions to physicians, leveraging their private information, reduces antibiotic overprescribing by 20.3%.

Keywords:
Antibiotic prescribingAntibiotic resistanceHuman-machine complementarityMachine learning

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Area of Science:

  • Medical Informatics
  • Health Economics
  • Clinical Decision Support

Background:

  • Artificial intelligence (AI) shows promise for enhancing human decision-making in complex fields.
  • However, AI effectiveness is constrained when human experts possess private, context-specific information.
  • Physician decision-making in antibiotic prescribing is a critical area for potential AI integration.

Purpose of the Study:

  • To evaluate the impact of AI on antibiotic prescribing decisions for urinary tract infections.
  • To determine the optimal balance between AI automation and physician judgment.
  • To quantify the reduction in antibiotic overprescribing through combined decision-making.

Main Methods:

  • Empirical analysis using antibiotic prescribing data for urinary tract infections.
  • Comparison of fully automated AI prescribing versus physician-led prescribing.
  • Modeling of hybrid approaches combining AI and physician decisions based on information complementarity.

Main Results:

  • Full automation of antibiotic prescribing by AI did not outperform physician decisions.
  • Delegating a portion of prescribing decisions to physicians, utilizing their private diagnostic information, proved effective.
  • A combined physician-AI approach achieved a 20.3% reduction in inefficient antibiotic overprescribing.

Conclusions:

  • Hybrid models that leverage the complementarity of human and algorithmic decision-making are superior to full AI automation.
  • Optimal delegation strategies are crucial for maximizing the benefits of AI in clinical practice.
  • Integrating AI with physician expertise can significantly improve antibiotic stewardship and reduce overprescribing.