Antibiotic Resistance Microbiology Dataset (ARMD): A Resource for Antimicrobial Resistance from EHRs
Abstract 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 h...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05649-7 |
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| author | Fateme Nateghi Haredasht Fatemeh Amrollahi Manoj V. Maddali Nicholas Marshall Stephen P. Ma Lauren N. Cooper Andrew O. Johnson Ziming Wei Richard J. Medford Sanjat Kanjilal Niaz Banaei Stanley Deresinski Mary K. Goldstein Steven M. Asch Amy Chang Jonathan H. Chen |
| author_facet | Fateme Nateghi Haredasht Fatemeh Amrollahi Manoj V. Maddali Nicholas Marshall Stephen P. Ma Lauren N. Cooper Andrew O. Johnson Ziming Wei Richard J. Medford Sanjat Kanjilal Niaz Banaei Stanley Deresinski Mary K. Goldstein Steven M. Asch Amy Chang Jonathan H. Chen |
| author_sort | Fateme Nateghi Haredasht |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-5c256fdc128e44e9be7b8b2f3108e314 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-5c256fdc128e44e9be7b8b2f3108e3142025-08-20T03:45:45ZengNature PortfolioScientific Data2052-44632025-07-011211810.1038/s41597-025-05649-7Antibiotic Resistance Microbiology Dataset (ARMD): A Resource for Antimicrobial Resistance from EHRsFateme Nateghi Haredasht0Fatemeh Amrollahi1Manoj V. Maddali2Nicholas Marshall3Stephen P. Ma4Lauren N. Cooper5Andrew O. Johnson6Ziming Wei7Richard J. Medford8Sanjat Kanjilal9Niaz Banaei10Stanley Deresinski11Mary K. Goldstein12Steven M. Asch13Amy Chang14Jonathan H. Chen15Stanford Center for Biomedical Informatics Research, Stanford UniversityStanford Center for Biomedical Informatics Research, Stanford UniversityDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Stanford University School of MedicineDivision of Pediatric Infectious Diseases, Department of Pediatrics, Stanford University School of MedicineDivision of Hospital Medicine, Stanford UniversityClinical Informatics Center, University of Texas Southwestern Medical CenterInformation Services, East Carolina UniversityDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare InstituteClinical Informatics Center, University of Texas Southwestern Medical CenterDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare InstituteDivision of Infectious Diseases and Geographic Medicine, Stanford University School of MedicineDivision of Infectious Diseases and Geographic Medicine, Stanford University School of MedicineDepartment of Health Policy, Stanford University School of MedicineDivision of Primary Care and Population Health, Stanford University School of MedicineDivision of Infectious Diseases and Geographic Medicine, Stanford University School of MedicineStanford Center for Biomedical Informatics Research, Stanford UniversityAbstract 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.https://doi.org/10.1038/s41597-025-05649-7 |
| spellingShingle | Fateme Nateghi Haredasht Fatemeh Amrollahi Manoj V. Maddali Nicholas Marshall Stephen P. Ma Lauren N. Cooper Andrew O. Johnson Ziming Wei Richard J. Medford Sanjat Kanjilal Niaz Banaei Stanley Deresinski Mary K. Goldstein Steven M. Asch Amy Chang Jonathan H. Chen Antibiotic Resistance Microbiology Dataset (ARMD): A Resource for Antimicrobial Resistance from EHRs Scientific Data |
| title | Antibiotic Resistance Microbiology Dataset (ARMD): A Resource for Antimicrobial Resistance from EHRs |
| title_full | Antibiotic Resistance Microbiology Dataset (ARMD): A Resource for Antimicrobial Resistance from EHRs |
| title_fullStr | Antibiotic Resistance Microbiology Dataset (ARMD): A Resource for Antimicrobial Resistance from EHRs |
| title_full_unstemmed | Antibiotic Resistance Microbiology Dataset (ARMD): A Resource for Antimicrobial Resistance from EHRs |
| title_short | Antibiotic Resistance Microbiology Dataset (ARMD): A Resource for Antimicrobial Resistance from EHRs |
| title_sort | antibiotic resistance microbiology dataset armd a resource for antimicrobial resistance from ehrs |
| url | https://doi.org/10.1038/s41597-025-05649-7 |
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