Among the most urgent and serious threats to public health are 7 antibiotic-resistant bacterial infections predominately acquired during health-care delivery. There is an emerging field of health-care epidemiology that is focused on preventing health care–associated infections with antibiotic-resistant bacteria and incorporates data from patient transfers or patient movements within and between facilities. This analytic field is being used to help public health professionals identify best opportunities for prevention. Different analytic approaches that draw on uses of big data are being explored to help target the use of limited public health resources, leverage expertise, and enact effective policy to maximize an impact on population-level health. Here, the following recent advances in data-driven responses to preventing spread of antibiotic resistance across health-care settings are summarized: leveraging big data for machine learning, integration or advances in tracking patient movement, and highlighting the value of coordinating response across institutions within a region.

中文翻译：

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数据驱动的响应在防止跨保健场所传播抗生素耐药性方面的进展。

在公共卫生领域，最紧急和严重的威胁之一是在卫生保健期间主要获得了7种对抗生素产生抗药性的细菌感染。卫生保健流行病学有一个新兴领域，其重点是预防与抗生素抗药性细菌相关的卫生保健相关感染，并将来自患者转移或患者在设施内部和设施之间移动的数据合并在一起。该分析领域正用于帮助公共卫生专业人员确定最佳的预防机会。正在探索利用大数据使用的不同分析方法，以帮助确定有限公共卫生资源的使用为目标，利用专业知识，制定有效的政策以最大程度地提高对人口级健康的影响。这里，