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Advances in Data-Driven Responses to Preventing Spread of Antibiotic Resistance Across Health-Care Settings.
Fridkin, Scott K.
Afiliação
  • Fridkin SK; Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia.
Epidemiol Rev ; 41(1): 6-12, 2019 01 31.
Article em En | MEDLINE | ID: mdl-31673712
Among the most urgent and serious threats to public health are 7 antibiotic-resistant bacterial infections predominately acquired during health-care delivery. There is an emerging field of health-care epidemiology that is focused on preventing health care-associated infections with antibiotic-resistant bacteria and incorporates data from patient transfers or patient movements within and between facilities. This analytic field is being used to help public health professionals identify best opportunities for prevention. Different analytic approaches that draw on uses of big data are being explored to help target the use of limited public health resources, leverage expertise, and enact effective policy to maximize an impact on population-level health. Here, the following recent advances in data-driven responses to preventing spread of antibiotic resistance across health-care settings are summarized: leveraging big data for machine learning, integration or advances in tracking patient movement, and highlighting the value of coordinating response across institutions within a region.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Resistência Microbiana a Medicamentos / Infecção Hospitalar Limite: Humans Idioma: En Revista: Epidemiol Rev Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Geórgia

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Resistência Microbiana a Medicamentos / Infecção Hospitalar Limite: Humans Idioma: En Revista: Epidemiol Rev Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Geórgia