AUTHOR=Naylor Nichola R. , Yamashita Kazuto , Iwami Michiyo , Kunisawa Susumu , Mizuno Seiko , Castro-Sánchez Enrique , Imanaka Yuichi , Ahmad Raheelah , Holmes Alison 

TITLE=Code-Sharing in Cost-of-Illness Calculations: An Application to Antibiotic-Resistant Bloodstream Infections

JOURNAL=Frontiers in Public Health

VOLUME=8

YEAR=2020

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2020.562427

DOI=10.3389/fpubh.2020.562427

ISSN=2296-2565

ABSTRACT=<p><bold>Background:</bold> More data-driven evidence is needed on the cost of antibiotic resistance. Both Japan and England have large surveillance and administrative datasets. Code sharing of costing models enables reduced duplication of effort in research.</p><p><bold>Objective:</bold> To estimate the burden of antibiotic-resistant <italic>Staphylococcus aureus</italic> bloodstream infections (BSIs) in Japan, utilizing code that was written to estimate the hospital burden of antibiotic-resistant <italic>Escherichia coli</italic> BSIs in England. Additionally, the process in which the code-sharing and application was performed is detailed, to aid future such use of code-sharing in health economics.</p><p><bold>Methods:</bold> National administrative data sources were linked with voluntary surveillance data within the Japan case study. R software code, which created multistate models to estimate the excess length of stay associated with different exposures of interest, was adapted from previous use and run on this dataset. Unit costs were applied to estimate healthcare system burden in 2017 international dollars (I$).</p><p><bold>Results:</bold> Clear supporting documentation alongside open-access code, licensing, and formal communication channels, helped the re-application of costing code from the English setting within the Japanese setting. From the Japanese healthcare system perspective, it was estimated that there was an excess cost of I$6,392 per <italic>S. aureus</italic> BSI, whilst oxacillin resistance was associated with an additional I$8,155.</p><p><bold>Conclusions:</bold><italic>S. aureus</italic> resistance profiles other than methicillin may substantially impact hospital costs. The sharing of costing models within the field of antibiotic resistance is a feasible way to increase burden evidence efficiently, allowing for decision makers (with appropriate data available) to gain rapid cost-of-illness estimates.</p>