@article{805662,
      recid = {805662},
      author = {Delaney, Connie White, and Weaver, Charlotte A., and  Warren, Judith Jordan, and Clancy, Thomas R. and Simpson,  Roy L.,},
      title = {Big data-enabled nursing : education, research and  practice /},
      pages = {1 online resource (xxxv, 488 pages) :},
      abstract = {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. .},
      url = {http://library.usi.edu/record/805662},
      doi = {https://doi.org/10.1007/978-3-319-53300-1},
}