<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>5(1)</volume><submitter>Luz CF</submitter><pubmed_abstract>&lt;h4>Objectives&lt;/h4>Insights about local antimicrobial resistance (AMR) levels and epidemiology are essential to guide decision-making processes in antimicrobial use. However, dedicated tools for reliable and reproducible AMR data analysis and reporting are often lacking. We aimed to compare traditional data analysis and reporting versus a new approach for reliable and reproducible AMR data analysis in a clinical setting.&lt;h4>Methods&lt;/h4>Ten professionals who routinely work with AMR data were provided with blood culture test results including antimicrobial susceptibility results. Participants were asked to perform a detailed AMR data analysis in a two-round process: first using their software of choice and next using our newly developed software tool. Accuracy of the results and time spent w</pubmed_abstract><journal>JAC-antimicrobial resistance</journal><pagination>dlac143</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9847555</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Better antimicrobial resistance data analysis and reporting in less time.</pubmed_title><pmcid>PMC9847555</pmcid><pubmed_authors>Sinha B</pubmed_authors><pubmed_authors>Glasner C</pubmed_authors><pubmed_authors>Lokate M</pubmed_authors><pubmed_authors>Berends MS</pubmed_authors><pubmed_authors>Luz CF</pubmed_authors><pubmed_authors>Friedrich AW</pubmed_authors><pubmed_authors>Zhou X</pubmed_authors></additional><is_claimable>false</is_claimable><name>Better antimicrobial resistance data analysis and reporting in less time.</name><description>&lt;h4>Objectives&lt;/h4>Insights about local antimicrobial resistance (AMR) levels and epidemiology are essential to guide decision-making processes in antimicrobial use. However, dedicated tools for reliable and reproducible AMR data analysis and reporting are often lacking. We aimed to compare traditional data analysis and reporting versus a new approach for reliable and reproducible AMR data analysis in a clinical setting.&lt;h4>Methods&lt;/h4>Ten professionals who routinely work with AMR data were provided with blood culture test results including antimicrobial susceptibility results. Participants were asked to perform a detailed AMR data analysis in a two-round process: first using their software of choice and next using our newly developed software tool. Accuracy of the results and time spent w</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 Feb</publication><modification>2025-04-22T01:03:56.066Z</modification><creation>2025-04-05T19:51:39.831Z</creation></dates><accession>S-EPMC9847555</accession><cross_references><pubmed>36686270</pubmed><doi>10.1093/jacamr/dlac143</doi></cross_references></HashMap>