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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
The language of data: tools to translate evidence for nurses in clinical practice
Bradi B Granger1, Yanfang Zhao, Jennifer Rogers
1Bradi B. Granger, PhD, RN, FAHA, FAAN, is Cardiovascular Clinical Nurse Specialist, Duke University Health Systems, and Associate Professor, Duke Translational Nursing Institute, School of Nursing, Duke University, Durham, North Carolina. Yanfang Zhao, MS, is Statistician, Duke Translational Nursing Institute, Duke University, Durham, North Carolina. Jennifer Rogers, MEd, is Educational Consultant, EnGage Consulting, LLC. Durham, North Carolina. Corinne Miller, BSN, RN, is Clinical Nurse, Cardiac Care Unit, Duke Heart Center, Duke University Health System, Durham, North Carolina. Catherine L. Gilliss, PhD, RN, is Dean, School of Nursing, Duke University, Vice Chancellor for Nursing Affairs, Duke University, Durham, North Carolina. Mary Champagne, PhD, RN, is Professor, School of Nursing, Duke University, Durham, North Carolina.
Abstract:
In clinical practice, nurses are expected to understand and implement the science that supports patient care, yet they fall short of goals to implement evidence in practice. One reason is difficulty in interpreting research results. Interpretation requires an ability to read and speak a language that many nurses have never mastered-the language of data. This article presents a skill-based solution for use in nursing professional development to improve nurses' understanding of statistics as a language.
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