Other Titles

Promoting clinical outcomes

Abstract

Retrospective research utilizing big data sets is essential as we collect and examine data across the globe. However, inconsistencies are noted when classifying data such as the case of traumatic brain injury classification. This project examined inconsistencies in classification when working with big data sets and retrospective data.

Authors

Sandra Rogers

Author Details

Sandra Rogers, PhD, MBA, BSN, Department of Nursing, Marymount University, Arlington, Virginia, USA

Sigma Membership

Unknown

Lead Author Affiliation

Marymount University, Arlington, Virginia, USA

Type

Presentation

Format Type

Text-based Document

Study Design/Type

N/A

Research Approach

N/A

Keywords:

Big Data, Injury Classification, Traumatic Brain Injury

Conference Name

29th International Nursing Research Congress

Conference Host

Sigma Theta Tau International

Conference Location

Melbourne, Australia

Conference Year

2018

Rights Holder

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All permission requests should be directed accordingly and not to the Sigma Repository.

All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.

Acquisition

Proxy-submission

Additional Files

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Classification of traumatic brain injury severity complexities in retrospective data

Melbourne, Australia

Retrospective research utilizing big data sets is essential as we collect and examine data across the globe. However, inconsistencies are noted when classifying data such as the case of traumatic brain injury classification. This project examined inconsistencies in classification when working with big data sets and retrospective data.