Valuation of the economic cost of antimicrobial resistance (AMR) is important for decision making and should be estimated accurately. Highly variable or erroneous estimates may alarm policy makers and hospital administrators to act, but they also create confusion as to what the most reliable estimates are and how these should be assessed. This study by Wozniak, et al. (2019) aimed to assess the quality of methods used in studies that quantify the costs of AMR and to determine the best available evidence of the incremental cost of these infections.
In this systematic review, the researchers searched PubMed, Embase, Cinahl, Cochrane databases and grey literature sources published between January 2012 and October 2016. Articles reporting the additional burden of Enterococcus spp., Escherichia coli (E. coli), Klebsiella pneumoniae (K. pneumoniae), Pseudomonas aeruginosa (P. aeruginosa) and Staphylococcus aureus (S. aureus) resistant versus susceptible infections were sourced. The included studies were broadly classified as reporting oncosts from the healthcare/hospital/hospital charges perspective or societal perspective. Risk of bias was assessed based on three methodological components: (1) adjustment for length of stay prior to infection onset and consideration of time-dependent bias, (2) adjustment for comorbidities or severity of disease, and (3) adjustment for inappropriate antibiotic therapy.
Of 1094 identified studies, the researchers identified 12 peer-reviewed articles and two reports that quantified the economic burden of clinically important resistant infections. Two studies used multi-state modelling to account for the timing of infection minimising the risk of time dependent bias and these were considered to generate the best available cost estimates. Studies report an additional CHF 9473 per extended-spectrum beta-lactamases -resistant Enterobacteriaceae bloodstream infections (BSI); additional â¬3200 per third-generation cephalosporin resistant Enterobacteriaceae BSI; and additional â¬1600 per methicillin-resistant S. aureus (MRSA) BSI. The remaining studies either partially adjusted or did not consider the timing of infection in their analysis.
Implementation of AMR policy and decision-making should be guided only by reliable, unbiased estimates of effect size. Generating these estimates requires a thorough understanding of important biases and their impact on measured outcomes. This will ensure that researchers, clinicians, and other key decision makers concerned with increasing public health threat of AMR are accurately guided by the best available evidence.
Reference: Wozniak TM, et al. Using the best available data to estimate the cost of antimicrobial resistance: a systematic review. Antimicrobial Resistance & Infection Control. 2019;8:26
A Helping Hand: Innovative Approaches to Expanding Hand Hygiene Programs in Acute Care Settings
July 9th 2025Who knew candy, UV lights, and a college kid in scrubs could double hand hygiene adherence? A Pennsylvania hospital’s creative shake-up of its infection prevention program shows that sometimes it takes more than soap to get hands clean—and keep them that way.
Broadening the Path: Diverse Educational Routes Into Infection Prevention Careers
July 4th 2025Once dominated by nurses, infection prevention now welcomes professionals from public health, lab science, and respiratory therapy—each bringing unique expertise that strengthens patient safety and IPC programs.
How Contaminated Is Your Stretcher? The Hidden Risks on Hospital Wheels
July 3rd 2025Despite routine disinfection, hospital surfaces, such as stretchers, remain reservoirs for harmful microbes, according to several recent studies. From high-touch areas to damaged mattresses and the effectiveness of antimicrobial coatings, researchers continue to uncover persistent risks in environmental hygiene, highlighting the critical need for innovative, continuous disinfection strategies in health care settings.