Lesson 6 – Systematic Literature Review Course: Data Extraction

Missed last week? Read our Past Lesson: Screening Literature. Be sure to check it out if you haven’t already!

From Abstracts to Full Texts – The Data Extraction Process

Once you’ve narrowed down your list of relevant articles, the next step in the systematic literature review is the detailed process of data extraction. This phase involves reviewing full-text articles, extracting critical information, and organizing it into an evidence table. Here’s how to do it efficiently.

Step 1: Obtain Full-Text Articles

Abstracts provide a helpful overview, but full articles hold the key details necessary for evaluating the safety and performance (S&P) of your product. Be prepared to exclude articles that, upon closer inspection, lack the required information.

Step 2: Define Your Data Points

Clearly outline what data you need to extract, focusing on the metrics that align with your product’s claims and its Instructions for Use (IFU). Typically, these include:

• Safety Metrics: Adverse events, complications, or the absence of such issues.
• Performance Metrics: Numerical comparisons, measurable outcomes, or indirect indicators supporting performance.

Step 3: Build an Evidence Table

An evidence table simplifies the data extraction process. Here’s a breakdown of fields commonly included:

This structured approach ensures you capture all critical data while maintaining clarity and brevity.

Step 4: Extract Data for Both S&P and SOTA

Extracting data isn’t limited to your product. Summarize the State of the Art (SOTA) literature to provide a comparative analysis. Use consistent data fields to streamline your review process and create an easy-to-read summary.

Prioritize High-Quality Evidence

Not all studies carry equal weight. Randomized controlled trials (RCTs) are considered the gold standard due to their reliability. Observational studies and case reports, while valuable, should be critically appraised for their relevance and potential biases.

Writing Summaries vs. Focusing on Data

Rather than writing lengthy summaries for each article, focus on extracting relevant data points. A brief narrative highlighting key insights can complement your evidence table but keep it concise and regulatory-friendly. For example:

• Summarize safety and performance metrics for quick reference.
• Use bullet points to highlight critical findings without unnecessary elaboration.

Tools and Tips for Efficient Extraction

The CiteMed system offers built-in templates and fields for data extraction, ensuring consistency and simplifying the review process. Customize these fields as needed to fit your specific product or device.

Conclusion

The data extraction phase is a critical step in building a robust case for your product’s safety and performance. By systematically reviewing full-text articles and compiling key metrics into an organized evidence table, you lay the groundwork for a compelling and compliant submission.

Ready to streamline your data extraction process? Let’s get started today!