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Big Data-Enabled Nursing: Education, Research and Practice (Health Informatics) - Hardcover

 
9783319532998: Big Data-Enabled Nursing: Education, Research and Practice (Health Informatics)

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Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing.  It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors. 

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Five editors are national and international experts in nursing & health informatics, representing  all sectors including  health systems,  corporate and vendors, academia,  policy, and professional associations.  All invited authors are recognized experts.

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This text reflects how the learning health system infrastructure is maturing and being advanced by health information exchanges (HIEs) with multiple organizations blending their data or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery.

Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing has consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery.

Big Data-Enabled Nursing reflects on how health systems have developed and how electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. It provides instruction on the new opportunities for nursing and educates readers on the new skills in research methodologies that are being further enabled by new partnerships spanning all sectors.

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9783319851204: Big Data-Enabled Nursing: Education, Research and Practice (Health Informatics)

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ISBN 10:  3319851209 ISBN 13:  9783319851204
Verlag: Springer-Verlag GmbH, 2018
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Delaney, Connie W.|Weaver, Charlotte A.|Warren, Judith J.|Clancy, Thomas R.|Simpson, Roy L.
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors. Artikel-Nr. 9783319532998

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Buch. Zustand: Neu. Neuware -Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 524 pp. Englisch. Artikel-Nr. 9783319532998

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Delaney, Connie W. (Edited by)/ Weaver, Charlotte A. (Edited by)/ Warren, Judith J. (Edited by)/ Clancy, Thomas R. (Edited by)/ Simpson, Roy L. (Edited by)
Verlag: Springer, 2017
ISBN 10: 3319532995 ISBN 13: 9783319532998
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Hardcover. Zustand: Brand New. 1st edition. 488 pages. 9.25x6.25x1.25 inches. In Stock. Artikel-Nr. 3319532995

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