Excess annual economic burdens from nosocomial infections caused by multi-drug resistant bacteria in Thailand.

Background - Antimicrobial resistance (AMR) is a major health threat worldwide as it brings about poorer outcomes and places economic burdens to society. This study aims to estimate the economic burdens from nosocomial infections (NI) caused by multi-drug resistant (MDR) bacteria in Thailand. Research design and methods - A retrospective cohort study was conducted at a tertiary hospital over 2011-2012. A multivariate log-linear regression model was used to estimate the excess treatment costs of AMR to those non-AMR patients. Results - Switching from a non-AMR case to an AMR infection case, resulted in 42% increase in expected average treatment costs per patient. The annual treatment from hospital perspective and antibiotic costs associated with the management of AMR infections were estimated to be US$ 2.3 billion and US$ 262 million, respectively. The estimated annual benefit from eradicating AMR NI were US$ 4.2 billion from a societal perspective with the annual gains in quality-adjusted life years (QALYs) of 0.6 million due to the absence of 111,295 AMR cases each year. Conclusions - Large amount of money was spent on treatment and antibiotic costs to manage AMR infections. Benefit of eliminating these infections was estimated and it would be highly cost-effective.

Enumerating the economic cost of antimicrobial resistance per antibiotic consumed to inform the evaluation of interventions affecting their use.

Background: Antimicrobial resistance (AMR) poses a colossal threat to global health and incurs high economic costs to society. Economic evaluations of antimicrobials and interventions such as diagnostics and vaccines that affect their consumption rarely include the costs of AMR, resulting in sub-optimal policy recommendations. We estimate the economic cost of AMR per antibiotic consumed, stratified by drug class and national income level. Methods: The model is comprised of three components: correlation coefficients between human antibiotic consumption and subsequent resistance; the economic costs of AMR for five key pathogens; and consumption data for antibiotic classes driving resistance in these organisms. These were used to calculate the economic cost of AMR per antibiotic consumed for different drug classes, using data from Thailand and the United States (US) to represent low/middle and high-income countries. Results: The correlation coefficients between consumption of antibiotics that drive resistance in S. aureus, E. coli, K. pneumoniae, A. baumanii, and P. aeruginosa and resistance rates were 0.37, 0.27, 0.35, 0.45, and 0.52, respectively. The total economic cost of AMR due to resistance in these five pathogens was $0.5 billion and $2.9 billion in Thailand and the US, respectively. The cost of AMR associated with the consumption of one standard unit (SU) of antibiotics ranged from $0.1 for macrolides to $0.7 for quinolones, cephalosporins and broad-spectrum penicillins in the Thai context. In the US context, the cost of AMR per SU of antibiotic consumed ranged from $0.1 for carbapenems to $0.6 for quinolones, cephalosporins and broad spectrum penicillins. Conclusion: The economic costs of AMR per antibiotic consumed were considerable, often exceeding their purchase cost. Differences between Thailand and the US were apparent, corresponding with variation in the overall burden of AMR and relative prevalence of different pathogens. Notwithstanding their limitations, use of these estimates in economic evaluations can make better-informed policy recommendations regarding interventions that affect antimicrobial consumption and those aimed specifically at reducing the burden of AMR.