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Nursing Knowledge: Big Data Science-Implications for Nurse Leaders.

Bonnie L Westra1, Thomas R Clancy, Joyce Sensmeier

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Summary

Big Data in healthcare, including nursing data, enables predictive models to enhance patient safety and control costs. Understanding Big Data science is crucial for nursing leaders to improve care quality and efficiency.

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Area of Science:

  • Healthcare Informatics
  • Data Science
  • Nursing Leadership

Background:

  • Healthcare enterprises are integrating Big Data from electronic health records and information systems.
  • Mobile health applications are increasing the volume of Big Data as healthcare shifts to community-based models.
  • A national initiative is underway to incorporate nursing data into Big Data science.

Purpose of the Study:

  • To highlight the opportunity of Big Data for developing predictive models in nursing.
  • To emphasize the importance of integrating diverse data sources for improved patient outcomes.
  • To advocate for nursing leaders' understanding and application of Big Data science.

Main Methods:

  • Collaboration among diverse stakeholders (practice, industry, education, research, professional organizations) through conferences.
  • Development of recommendations for the inclusion and integration of nursing data.
  • Focus on standardizing data and workflow processes for advanced analytics.

Main Results:

  • Actionable predictive models can be developed to increase nursing leaders' confidence in decision-making.
  • Integration of nursing data with patient-generated, interprofessional, and contextual data is recommended.
  • Standardization of data and workflows is critical for leveraging advanced analytics.

Conclusions:

  • Big Data science offers significant potential to improve patient outcomes, safety, and cost control in nursing.
  • Nursing leaders must understand Big Data principles to effectively utilize advanced analytics.
  • Standardized data and workflows are essential for maximizing the benefits of Big Data in healthcare.