Big Data-Enabled Nursing : Education, Research and Practice

Connie W. Delaney

ISBN 10: 3319532995 / ISBN 13: 9783319532998

Published by Springer International Publishing, Springer Nature Switzerland, 2017

About this Item

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.

Seller Inventory # 9783319532998

Bibliographic Details

• Title: Big Data-Enabled Nursing : Education, Research and Practice
• Publisher: Springer International Publishing, Springer Nature Switzerland
• Publication Date: 2017
• Language: English
• ISBN 10: 3319532995
• ISBN 13: 9783319532998
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 32D millimeters 241 millimeters width by 160 millimeters height by 32 millimeters depth
• Weight: 1041 grams

About this title

Synopsis

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. 

About the Author

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.