Using point-of-care diagnostic testing for improved antibiotic prescription: an economic model

Area of Science:

• Health economics
• Infectious disease management
• Diagnostic technology

Background:

• Antibiotic overuse drives antimicrobial resistance, necessitating improved prescription strategies.
• Personalized medicine approaches, including point-of-care diagnostic testing (POCT), aim to enhance antibiotic prescription quality.
• Reducing antimicrobial resistance is a critical global health objective.

Purpose of the Study:

• To theoretically evaluate the economic benefits of using POCT versus empiric antibiotic prescription.
• To analyze physician prescribing decisions and diagnostic firm pricing strategies under varying uncertainty levels.
• To determine conditions under which POCT adoption is economically advantageous.

Main Methods:

• Development of a theoretical economic model simulating physician-firm interactions.
• Inclusion of physician uncertainty in treatment decisions and internalization of antimicrobial resistance costs.
• Analysis of diagnostic test pricing and physician prescription behavior.

Main Results:

• POCT adoption leads to a reduction in overall antibiotic prescriptions.
• The reduction in prescriptions is amplified when physicians account for antimicrobial resistance costs.
• Physicians with higher diagnostic uncertainty are more inclined to utilize POCT.

Conclusions:

• POCT can enhance antibiotic prescription quality and decrease prescription rates.
• The decision to use POCT versus empiric therapy depends on the level of physician uncertainty.
• Empiric therapy may remain preferable in low-uncertainty clinical scenarios.