Data Management Best Practice Guidelines for Nursing Students and Researcher

• Activity Number: 677
• Type: Topic Contributed
• Date/Time: Thursday, August 8, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistical Consulting
• Author(s): Jesse Chittams*+ and Alexandra L. Hanlon
• Companies: University of Pennsylvania and University of Pennsylvania School of Nursing
• Keywords: Consulting ; Data Management ; Nursing

Abstract

This topic will address various data management/analysis considerations important to advising graduate level nursing students. Specifically, the discussion will focus on best practices for assuring a smooth transition from the data collection phase to the data analysis phase of a project. Any statistician who has experienced the time consuming and frustrating task of cleaning messy datasets, or who has repeated a large set of data analyses due to errors that were detected a few days prior to a submission deadline, can appreciate the value of adopting simple but effective standard data management practices. Some of the recommendations that will be presented include: choosing the best data collection and storage software; ensuring patient confidentiality; adapting effective data quality assurance techniques, such as double data entry, and logical data checks; having the statistician review the data and give feedback very early in the data collection process; implementing an organized filing system for documents, data, and programs; and adopting effective procedures for checking derived variables and data merging.