Hospital organisation, management, and structure for prevention of health-care-associated infection: a systematic review and expert consensus

Zingg, Walter; Holmes, Alison; Dettenkofer, Markus; Goetting, Tim; Secci, Federica; Clack, Lauren; Allegranzi, Benedetta; Magiorakos, Anna-Pelagia; Pittet, Didier

doi:10.1016/s1473-3099(14)70854-0

Cited by 393 publications

(360 citation statements)

References 121 publications

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“…Most researchers fail to learn from the experience since it is not uncommon that there are no timely publications, reports and feedbacks provided by the pilot projects. Usually, the projects are target-oriented [169]. However, chances are that there exist alternate solutions that are cost-effective which may replace the current solution.…”

Section: Pilot Studies and Real Projectsmentioning

confidence: 99%

Disease Diagnosis in Smart Healthcare: Innovation, Technologies and Applications

et al. 2017

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Abstract:To promote sustainable development, the smart city implies a global vision that merges artificial intelligence, big data, decision making, information and communication technology (ICT), and the internet-of-things (IoT). The ageing issue is an aspect that researchers, companies and government should devote efforts in developing smart healthcare innovative technology and applications. In this paper, the topic of disease diagnosis in smart healthcare is reviewed. Typical emerging optimization algorithms and machine learning algorithms are summarized. Evolutionary optimization, stochastic optimization and combinatorial optimization are covered. Owning to the fact that there are plenty of applications in healthcare, four applications in the field of diseases diagnosis (which also list in the top 10 causes of global death in 2015), namely cardiovascular diseases, diabetes mellitus, Alzheimer's disease and other forms of dementia, and tuberculosis, are considered. In addition, challenges in the deployment of disease diagnosis in healthcare have been discussed.

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Section: Pilot Studies and Real Projectsmentioning

confidence: 99%

Disease Diagnosis in Smart Healthcare: Innovation, Technologies and Applications

et al. 2017

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“…A recent review of best practice in infection control found that regular audits followed by timely feedback were effective in improving compliance with control measures and ultimately reducing healthcare-associated infections. [21][22][23][24][25][26] Heuristics, which can be described as mental shortcuts or rules of thumb, draw on existing mental models in order to enable rapid judgements. Notably, the affect heuristic, also described as 'risk as feelings', and the availability heuristic, in which individuals judge the likelihood of an event by how easy it is to think of examples, play an important role in how individuals perceive and act on risks.…”

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confidence: 99%

Mental models: a basic concept for human factors design in infection prevention

Sax

Clack

2015

Journal of Hospital Infection

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Much of the effort devoted to promoting better hand hygiene is based on the belief that poor hand hygiene reflects poor motivation. We argue, however, that automatic unconscious behaviour driven by 'mental models' is an important contributor to what actually happens. Mental models are concepts of reality-imaginary, often blurred, and sometimes unstable. Human beings use them to reduce mental load and free up capacity in the conscious mind to focus on deliberate activities. They are pragmatic solutions to the complexity of life. Knowledge of such mental processes helps healthcare designers and clinicians overcome barriers to behavioural change. This article reviews the concept of mental models and considers how it can be used to improve hand hygiene and patient safety.

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“…Este hecho cobra especial relevancia al momento de hospitalizar, decidir el uso de terapias antimicrobianas empíricas y, posteriormente, la suspensión de éstas cuando la evolución no ha sido compatible con una infección bacteriana. La estadía hospitalaria, en espera de resultados microbiológicos, contribuye al uso injustificado de antimicrobianos y aumenta el riesgo de infecciones asociadas a la atención de salud (IAAS), descritas en 4,5 por 100 admisiones hospitalarias 3,4 . Por ello, acceder a un diagnóstico virológico amplio y oportuno puede influir en reducir la adquisición de IAAS y permitiría el uso de antivirales específicos, de haberlos disponibles 5 .…”

Section: Introductionunclassified