A model for estimating economic loss attributable to incorrect microbiological diagnosis of antimicrobial resistance and irrational antimicrobial use

Objective. To develop a quantitative model to assess the economic loss of irrational antimicrobial use and inaccurate antimicrobial resistance diagnosis. Materials and Methods. The model’s parameters were derived from a questionnaire survey designed to elucidate the characteristics of antimicrobial therapy practices and the impact of microbiological findings, including the frequency and consequences of diagnostic errors. The model’s fundamental structure rests upon the relationship between the accuracy of microbiological diagnoses, the likelihood of irrational antimicrobial therapy, and the consequent economic losses. To improve the model’s precision and generalizability, parameters encompassing gross regional product, population demographics, the prevalence of key community-acquired and nosocomial pathogens and their respective phenotypes, and antimicrobial drug prices were integrated. Results. Bacterial infections are prevalent in the practice of over 75% of surveyed specialists. Requests for clinical pharmacology consultation regarding infectious disease management are most frequently driven by multidrug-resistant pathogens and treatment failure. Electronic microbiology reports are accessed by 50,85% of specialists, with 65,62% utilizing in-house laboratory services. However, 36% lack readily available laboratory consultation. An association between interpretation of AST reports and choice of antimicrobial therapy was noted by 82,32% of specialists. In outpatient settings, mild and moderate adverse consequences of inappropriate antimicrobial therapy (IAT), affecting up to 25% of cases, were reported by 25,6% and 79,85% of specialists, respectively. In inpatient settings, moderate and severe adverse consequences of IAT (affecting >25% of cases) were reported by 34,83% and 19,52% of specialists. Based on the developed model, with the specified parameters, a cohort of 1000 patients and a 10% error rate yields direct inpatient costs exceeding 1,7 million rubles, while total loss reaches 18,94 million rubles. Conclusions. The developed model facilitates the estimation of economic consequences associated with irrational antimicrobial therapy, encompassing both direct and indirect costs, and exhibits considerable adaptability across diverse contexts. The findings underscore the need for further investigation to optimize interprofessional collaboration and the development of evidence-based strategies for mitigating the economic burden of antimicrobial resistance.