The design and evaluation of an antimicrobial resistance surveillance system for neonatal intensive care units in Iran

Rezaei‐Hachesu, Peyman; Samad‐Soltani, Taha; Yaghoubi, Sajad; Ghazisaeedi, Marjan; Mirnia, Kayvan; Masoumi-Asl, Hossein; Safdari, Reza

doi:10.1016/j.ijmedinf.2018.04.007

Cited by 8 publications

(7 citation statements)

References 20 publications

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“…Such information could then be used to better guide policy making 48 , e.g., to interpret the data with an intersectoral approach (human, animal, environment), and to assess and predict the risk of transmission. Beyond many older works, which are reviewed in 48 , it is worth highlighting a recent paper describing the design and evaluation of such a dashboard in northwestern Iranian hospitals 49 , for going beyond a pure research work and being an example of an actual deployed solution.…”

Section: Resultsmentioning

confidence: 99%

Public Health and Epidemiology Informatics: Can Artificial Intelligence Help Future Global Challenges? An Overview of Antimicrobial Resistance and Impact of Climate Change in Disease Epidemiology

2019

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Objectives: To provide an oveiview of the current application of artificial intelligence (AI) in the field of public health and epidemiology, with a special focus on antimicrobial resistance and the impact of climate change in disease epidemiology. Both topics are of vital importance and were included in the “Ten threats to global health in 2019“ report published by the World Health Organization. Methods: We analysed publications that appeared in the last two years, between January 2017 and October 2018. Papers were searched using Google Scholar with the following keywords: public health, epidemiology, machine learning, data analytics, artificial intelligence, disease surveillance, climate change, antimicrobial resistance, and combinations thereof. Selected articles were organised by theme. Results: In spite of a large interest in AI generated both within and outside the scientific community, and of the many opinions pointing towards the importance of a better use of data in public health, few papers have been published on the selected topics in the last two years. We identify several potential reasons, including the complexity of the integration of heterogeneous data, and the lack of sound and unbiased validation procedures. Conclusions: As there is a better comprehension of AI and more funding available, artificial intelligence will become not only the centre of attention in informatics, but more importantly the source of innovative solutions for public health.

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Section: Resultsmentioning

confidence: 99%

Public Health and Epidemiology Informatics: Can Artificial Intelligence Help Future Global Challenges? An Overview of Antimicrobial Resistance and Impact of Climate Change in Disease Epidemiology

2019

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“…Indeed, involving users in the early stages of prototype design is a key factor contributing to the success of a system 10 . Several studies have highlighted the significance of focusing on users and their needs for the successful implementation of a system 11–13 . With the increasing use of medical information exchange systems, the importance of users' feedback in the design, implementation, and acceptance of these systems has become highly significant 14 .…”

Section: Background and Aimsmentioning

confidence: 99%

Requirements specification, design, and evaluation of dental image exchange and management system with user‐centered approach: A case study in Iran

Rahimi,

Karimian,

Ghaznavi

et al. 2023

Health Science Reports

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Background and AimsSystems existing in hospital or clinic settings offer services within the physical environment. Examples of such systems include picture archiving and communication systems, which provide remote services for patients. To develop a successful system, methods like software development life cycles (SDLCs) and design techniques, such as prototyping, are needed. This study aimed to specify requirements, design, and evaluation of dental image exchange and management system using a user‐centered approach.MethodsThis cross‐sectional study was conducted in four phases, each corresponding to different stages of SDLCs. User‐needs data were used to gathered by interviews and observations. A prototype was developed using object‐oriented programming and presented to users for feedback. Finally, focus group was used to finalized the prototype into the desired system.ResultsUser needs were identified and prioritized from the outset, with ease of use, security, and mobile apps being their most essential requirements. The prototype underwent several iterations of design and evaluation in focus group sessions until users were satisfied, and their feedback was incorporated. Eventually, the prototype was refined into the final system with users' consent.ConclusionThe study revealed that instant access to information, voluntary participation, user interface (UI) design, and usefulness were critical variables for users and should be integral to any system. Successful implementation of such a system requires careful consideration of end‐users' needs and their application to the system. Moreover, integrating the system with electronic health records can further enhance the treatment process and the efficiency of medical staff. The voluntary perspective of users played a significant role in achieving an exemplary UI and overall satisfaction with the system. Developers and policymakers should consider these aspects in similar system development projects.

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“…The Naïve Bayes method has been used to identify resistance determinants and build a resistance profile of biomarkers [60]. In addition, this method has been used in to determine the probability of effective antibiotic treatment when not targeted to a specific pathogen [61].…”

Section: Artificial Intelligence For the Prediction Of Antimicrobial ...mentioning

confidence: 99%

“…In turn, this resistance profile can be used to determine Molecular Tools for the Study of Resistance to Disinfectants DOI: http://dx.doi.org/10.5772/intechopen.104414 which resistance biomarkers are not present and therefore which antimicrobials the isolate is most likely susceptible [62]. This generates a list of potential antimicrobials that will be effective against a particular pathogen based on its genomic characteristics and biomarkers present in the genome [60].…”

Section: Artificial Intelligence For the Prediction Of Antimicrobial ...mentioning

confidence: 99%

Molecular Tools for the Study of Resistance to Disinfectants

Carlie¹,

Staats²,

Belter³

et al. 2022

The Global Antimicrobial Resistance Epidemic - Innovative Approaches and Cutting-Edge Solutions

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Disinfectants, antiseptics, and sanitizers are crucial for hygiene standards and disease control, as recently emphasized by the SARS-CoV-2 (COVID-19) pandemic. With the foreshadowing of antibiotic resistance, new cutting-edge technologies and innovative methodology need to be applied to prevent the latest emerging antimicrobial resistance crisis, resistance to disinfectants. Disinfectant resistance is a relatively novel field of study, and although some molecular mechanisms have been elucidated, little is known about complex mechanisms, cross-resistance with antibiotics, and the existence of resistance biomarkers. Fortunately, great advances have been made in the field of sequencing technology and bioinformatics. Although there are many limitations to this technology, various “omics” approaches to disinfectant resistance will be crucial in directing environment-specific disinfection programs. In addition, the vast amounts of data generated by sequencing technologies can be applied by artificial intelligence (AI) models to identify key disinfectant resistance markers and in the surveillance of disinfectant resistance genes. A combination of these approaches will be crucial in identifying new disinfectant resistance mechanisms, in monitoring resistant populations, and in identifying cellular targets for new disinfectant formulations. These molecular tools will be vital in the battle against disinfectant resistance, the latest development in the antimicrobial resistance crisis.

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The design and evaluation of an antimicrobial resistance surveillance system for neonatal intensive care units in Iran

Cited by 8 publications

References 20 publications

Public Health and Epidemiology Informatics: Can Artificial Intelligence Help Future Global Challenges? An Overview of Antimicrobial Resistance and Impact of Climate Change in Disease Epidemiology

Public Health and Epidemiology Informatics: Can Artificial Intelligence Help Future Global Challenges? An Overview of Antimicrobial Resistance and Impact of Climate Change in Disease Epidemiology

Requirements specification, design, and evaluation of dental image exchange and management system with user‐centered approach: A case study in Iran

Molecular Tools for the Study of Resistance to Disinfectants

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