Web Scraping Techniques for Surgical Research: A Technical Tutorial With a Worked Example in Publication Data Mining

Area of Science:

• Medical Informatics
• Health Services Research
• Surgical Research

Background:

• Web scraping is crucial for researchers needing large-scale data collection.
• Limited technical guidance exists for surgeon-scientists on web scraping.
• Public web data is relevant for surgical outcomes, health services, and policy research.

Purpose of the Study:

• To provide a clinician-oriented technical guide to web scraping for surgical research.
• To demonstrate a complete web scraping pipeline with a practical example.
• To equip surgical researchers with foundational knowledge for data collection.

Main Methods:

• Tutorial covers key web scraping concepts: static vs. dynamic websites, CSS selectors, browser automation, rate limiting, and ethics.
• A worked example scrapes a surgical research group's publication page.
• A reusable code template is provided for adapting the pipeline.

Main Results:

• Successfully extracted structured publication data (titles, authors, abstracts, links) from a JavaScript-rendered website.
• Generated an analysis-ready bibliometric database.
• Demonstrated generalization to other surgical research applications (price transparency, residency data, quality metrics).

Conclusions:

• Web scraping is a powerful tool for surgeon-scientists when used with technical rigor and ethical responsibility.
• The tutorial equips researchers with the knowledge to design, implement, and adapt web scrapers.
• This approach facilitates efficient data collection for diverse surgical research questions.