基于电子病历的耐药菌数据集，助力抗菌药物管理研究。
Antibiotic Resistance Microbiology Dataset (ARMD): A Resource for Antimicrobial Resistance from EHRs
- 从两家附属医院15年数据中提取耐药性信息
- 涵盖55种抗生素敏感性及患者脱敏特征
- 适合医学研究者开展抗感染决策分析
抗生素耐药微生物数据集（ARMD）是一个源自电子健康记录（EHR）的去标识化资源，支持抗菌药物耐药性（AMR）研究。该数据集整合了超过15年间来自两家学术附属医院的成年患者大数据，聚焦微生物培养、抗生素敏感性及相关的临床与人口统计学特征。关键属性包括病原体识别、55种抗生素的敏感性模式、隐含的敏感性规则以及去标识化的患者信息。该数据集支持抗菌药物管理、因果推断和临床决策研究，设计为可重用且互操作，促进在对抗耐药性方面的协作与创新。本文描述了数据集的获取、结构与用途，并详细说明其去标识化流程。
原文摘要 · Abstract (English)
The Antibiotic Resistance Microbiology Dataset (ARMD) is a de-identified resource derived from electronic health records (EHR) that facilitates research in antimicrobial resistance (AMR). ARMD encompasses big data from adult patients collected from over 15 years at two academic-affiliated hospitals, focusing on microbiological cultures, antibiotic susceptibilities, and associated clinical and demographic features. Key attributes include organism identification, susceptibility patterns for 55 antibiotics, implied susceptibility rules, and de-identified patient information. This dataset supports studies on antimicrobial stewardship, causal inference, and clinical decision-making. ARMD is designed to be reusable and interoperable, promoting collaboration and innovation in combating AMR. This paper describes the dataset's acquisition, structure, and utility while detailing its de-identification process.
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