Implementation Science
Implementation Science
Never have we had vast amounts of data at our fingertips like we do today. However, before we can meaningfully access and use data for interpretation, it must be transformed. To derive meaning from the data collected, you need to understand that data collection is rapidly changing and constantly evolving. The methods with which data is collected, analyzed, and used to justify, support, or lend credibility to research aims, are all important considerations for the nurse researcher. As it relates to Big Data, the methods of how data is collected, analyzed, and used for implementation is also important. While the availability of data collection certainly has its advantages, many researchers point to the concerns over Big Data
For this Discussion, reflect on your understanding of Big Data and the implications for implementation. Consider the impact of research as it relates to collection via Big Data and consider how this impact might lead to potential barriers in implementation and practice gaps. Reflect on your experience and consider how these key issues might impact nursing practice.
To Prepare
• Review the Learning Resources for this week, focusing specifically on the implementation science articles and web resources.
• Consider the issues related to research and Big Data.
Post and describe what you believe is most significant as a key issue with Big Data in which dissertation research has been completed, yet the data has not been analyzed or implemented.
• Please cite specific examples of research that was completed with potential for great social impact but was not implemented.
• What are some potential barriers for implementing the research analyzed?
• What potential gaps exist between evidence-based approaches and the research process?
READING RESOURCES
Sipes, C. (2020). Project management for the advanced practice nurse (2nd ed.). Springer Publishing.
• Chapter 4, “Planning: Project Management—Phase 2” (pp. 75–120)
• Chapter 2, “Foundational Project Management Theories that Support Decision-Making” (pp. 22–25)
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