Training to prevent healthcare associated infections

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منابع مشابه

a survey of adherence to guidelines to prevent healthcare-associated infections in iranian intensive care units

conclusions evidence-based post-insertion recommended care practices were not consistently and uniformly implemented in the intensive care units. establishment of a program for the surveillance of adherence to recommended guidelines is required for improving compliance by health professionals and the quality of preventive care. background healthcare-associated infections (hais) are acquired by ...

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Strategies to prevent healthcare-associated infections through hand hygiene.

Affiliations: 1. Centers for Disease Control and Prevention, Atlanta, Georgia; 2. Westchester Medical Center and New York Medical College Department of Medicine, Valhalla, New York; 3. Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina; 4. The Joint Commission, Oakbrook Terrace, Illinois; 5. Johns Hopkins University School of Medicine, Baltimore, ...

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AHRQ’s Efforts to Prevent and Reduce Healthcare-Associated Infections

Healthcare-associated infections (HAIs) are infections that patients get while receiving treatment for another condition in some type of health care facility. A study of patients in 2002 estimated that HAIs account for an estimated 1.7 million infections and 99,000 associated deaths annually, making them the most common complication of hospital care. The added financial burden attributable to H...

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A Survey of Adherence to Guidelines to Prevent Healthcare-Associated Infections in Iranian Intensive Care Units

BACKGROUND Healthcare-associated infections (HAIs) are acquired by patients while receiving care. The highest incidence of HAIs has been documented in admissions to intensive care units. Adherence to evidence-based practices is the most important step for preventing HAIs. OBJECTIVES To determine the rate of adherence to evidence-based post-insertion recommended care practices after admission ...

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Learning to prevent healthcare-associated infections: leveraging data across time and space to improve local predictions

The proliferation of electronic medical records holds out the promise of using machine learning and data mining to build models that will help healthcare providers improve patient outcomes. However, building useful models from these datasets presents many technical problems. Among the challenges are the large number of factors (both intrinsic and extrinsic) influencing a patient's risk of an ad...

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ژورنال

عنوان ژورنال: The European Research Journal

سال: 2015

ISSN: 2149-3189

DOI: 10.18621/eurj.2015.1.3.94