Related Experiment Video
Updated: Sep 9, 2025
05:47
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
570
Twelve tips for data extraction for knowledge syntheses
Lauren A Maggio1, Joseph A Costello1, Dario M Torre2
1Department of Medical Education, University of Illinois Chicago, Chicago, IL, USA.
Medical Teacher
|September 2, 2025
Summary
This study offers 12 practical tips for data extraction in knowledge syntheses, a crucial step in medical education research. These guidelines enhance the rigor and efficiency of synthesizing evidence for better educational practice and policy.
Area of Science:
- Medical Education Research
- Evidence Synthesis Methodologies
Background:
- Knowledge syntheses are increasingly influential in medical education practice, research, and policy.
- Existing guidance for knowledge synthesis often lacks practical detail on data extraction.
- Flawed or time-consuming data extraction can compromise the quality of evidence synthesis.
Purpose of the Study:
- To address the gap in practical guidance for data extraction in knowledge syntheses.
- To provide actionable strategies for improving the quality and efficiency of data extraction.
- To offer 12 evidence-based tips for conducting systematic data extraction.
Main Methods:
- The article presents 12 practical tips for data extraction, grounded in literature and expert experience.
- Tips are organized into creating a data extraction tool and operationalizing its use.
- Guidance covers aligning extraction with objectives, team-based approaches, discrepancy resolution, and piloting.
Main Results:
- The 12 tips offer concrete strategies for systematic data extraction.
- The proposed methods aim to enhance the rigor, efficiency, and reliability of knowledge syntheses.
- Practical advice is provided for tool development and implementation in team settings.
Conclusions:
- Effective data extraction is critical for high-quality knowledge syntheses in medical education.
- The provided tips offer a practical framework to improve data extraction processes.
- Implementing these strategies can lead to more reliable and efficient evidence synthesis for educational advancement.
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