Classification of traumatic brain injury severity complexities in retrospective data
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Sandra Rogers, PhD, MBA, BSN, Department of Nursing, Marymount University, Arlington, Virginia, USA
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- Eta Alpha
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- Marymount University, Arlington, Virginia, USA
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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.
29th International Nursing Research Congress: Innovative Global Nursing Practice and Education Through Research and Evidence-based Practice, July 19-23, 2018. Melbourne, Australia.
Items submitted to a conference/event were evaluated/peer-reviewed at the time of abstract submission to the event. No other peer-review was provided prior to submission to the Henderson Repository, unless otherwise noted.
Type | Presentation |
Acquisition | Proxy-submission |
Review Type | Abstract Review Only: Reviewed by Event Host |
Format | Text-based Document |
Evidence Level | N/A |
Research Approach | N/A |
Keywords | Big Data; Injury Classification; Traumatic Brain Injury |
Name | 29th International Nursing Research Congress |
Host | Sigma Theta Tau International |
Location | Melbourne, Australia |
Date | 2018 |
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