Automating the Generation of Antimicrobial Resistance Surveillance Reports: Proof-of-Concept Study Involving Seven Hospitals in Seven Countries
| العنوان: | Automating the Generation of Antimicrobial Resistance Surveillance Reports: Proof-of-Concept Study Involving Seven Hospitals in Seven Countries |
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| المؤلفون: | Nguyen Phu Huong Lan, H. Rogier van Doorn, Clare Ling, Elizabeth A. Ashley, Sharon J. Peacock, Ben S. Cooper, Direk Limmathurotsakul, Abhilasha Karkey, Cherry Lim, Paul Turner, Viriya Hantrakun, Tri Wangrangsimakul, Sopon Iamsirithaworn, Soawapak Hinjoy, Nicholas P. J. Day, Batra Rahul, Prapit Teparrukkul, Htet Naing Lin, Htay Htay Hlaing, John Stelling, Thyl Miliya, Manivanh Vongsouvath, Susanna Dunachie, Jonathan D. Edgeworth, Mayfong Mayxay, Le Van Tan, Vilada Chansamouth, Guy E. Thwaites, Myint Thazin Aung, Buddha Basnyat, Lam Minh Yen, William Hk Schilling |
| المصدر: | Journal of Medical Internet Research, Vol 22, Iss 10, p e19762 (2020) Journal of Medical Internet Research |
| بيانات النشر: | JMIR Publications Inc., 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Computer science, data analysis, Health Informatics, Information repository, lcsh:Computer applications to medicine. Medical informatics, Proof of Concept Study, World Wide Web, 03 medical and health sciences, 0302 clinical medicine, Drug Resistance, Bacterial, Data file, Information system, Humans, antimicrobial resistance, 030212 general & internal medicine, report, Original Paper, 0303 health sciences, 030306 microbiology, lcsh:Public aspects of medicine, lcsh:RA1-1270, Hospitals, Test (assessment), Identifier, Epidemiological Monitoring, surveillance, Microsoft Windows, lcsh:R858-859.7, Electronic data, application, Test data |
| الوصف: | Background Reporting cumulative antimicrobial susceptibility testing data on a regular basis is crucial to inform antimicrobial resistance (AMR) action plans at local, national, and global levels. However, analyzing data and generating a report are time consuming and often require trained personnel. Objective This study aimed to develop and test an application that can support a local hospital to analyze routinely collected electronic data independently and generate AMR surveillance reports rapidly. Methods An offline application to generate standardized AMR surveillance reports from routinely available microbiology and hospital data files was written in the R programming language (R Project for Statistical Computing). The application can be run by double clicking on the application file without any further user input. The data analysis procedure and report content were developed based on the recommendations of the World Health Organization Global Antimicrobial Resistance Surveillance System (WHO GLASS). The application was tested on Microsoft Windows 10 and 7 using open access example data sets. We then independently tested the application in seven hospitals in Cambodia, Lao People’s Democratic Republic, Myanmar, Nepal, Thailand, the United Kingdom, and Vietnam. Results We developed the AutoMated tool for Antimicrobial resistance Surveillance System (AMASS), which can support clinical microbiology laboratories to analyze their microbiology and hospital data files (in CSV or Excel format) onsite and promptly generate AMR surveillance reports (in PDF and CSV formats). The data files could be those exported from WHONET or other laboratory information systems. The automatically generated reports contain only summary data without patient identifiers. The AMASS application is downloadable from https://www.amass.websiteTest/. The participating hospitals tested the application and deposited their AMR surveillance reports in an open access data repository. Conclusions The AMASS is a useful tool to support the generation and sharing of AMR surveillance reports. |
| تدمد: | 1438-8871 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::827946359f72a0b155d5bc3d44b983abTest https://doi.org/10.2196/19762Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....827946359f72a0b155d5bc3d44b983ab |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 14388871 |
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