The development of a method to estimate the cost of antimicrobial resistance (AMR) resulting from antimicrobial compounds will allow for more rigorous economic evaluations of proposed solutions to AMR. Hence, the work of Shrestha et al.1 will lead to more informed and effective health policy decision making in this period of rising antimicrobial resistance and contracting healthcare spending.
In the past decades, antimicrobial resistance (AMR) has become a major health concern, claiming many 100's of the thousands of lives across the globe and incurring very significant economic and social costs2. AMR renders typical antimicrobial treatments ineffective, forcing use of less effective, more toxic and expensive 'second line drugs' as well as increased hospitalization times2. In the worst cases, AMR pathogens will kill their host, resulting in a major economic costs associated with premature loss of economic productivity. However, the colossal danger posed by AMR has not gone unnoticed by many policy makers, with groups such as the UN organizing high level assembly meetings and passing resolutions to develop policy and products to counter AMR3.
Despite these actions, there remains the major issue of quantifying the impact of proposals e.g. increased vaccine use, with many economic evaluations completely omitting the effect of changes in antimicrobial usage4. This is an important effect to capture as antimicrobials constitute a major part of the treatment costs but can also contribute towards the development of AMR4. This creates a warped image of the overall cost-efficacy of these proposals, potentially leading to the unwarranted rejection of cost effective proposals. This inaccuracy is particularly dire, not only because of the rising AMR crisis, but also because of the increasing cost efficacy demands from payers5, resulting in increased stringency of healthcare spending. This inadequacy has been signaled as early as 19964 but has yet to be systematically addressed, with many publications exploring AMR cost as a whole6, but not specifically the AMR cost brought about by use of AMR-developing antimicrobials. A small amount of studies have looked at this specific cost, but usually within the context of very limited geographical zones (single hospital7) or for very specific diseases8. The publication by Shrestha et al. presented in this News and Views article aims to address this issue by providing a solid foundation for quantifying the link between the use of antimicrobials and AMR associated costs.
To achieve this end, Shrestha et al. devised a method for calculating the resulting AMR cost per standard unit of antimicrobial used (AC/AM), which can be used to evaluate the aspects of proposals that reduce antimicrobial consumption . Furthermore, this method was developed to allow for calculation for specific pathogens or antimicrobial compounds and could be limited to specific geographical zones. This method relies on the use of three key variables enumerated and explained in Figure \ref{954452}, and since this is a purely empirical method, naturally it relies on the availability of the relevant cost and AMR data.