Contextualizing Breast Implant Removal Patterns with Google Trends: Big Data Applications in Surgical Demand

Area of Science:

• Plastic Surgery
• Public Health Trends
• Digital Epidemiology

Background:

• Breast implant removal (BIR) demand has significantly increased.
• Public perception and online information-seeking behaviors may influence surgical trends.
• Understanding these influences is crucial for healthcare providers.

Purpose of the Study:

• To analyze the correlation between public search interest and breast implant removal (BIR) surgical volume.
• To identify geographic and temporal patterns in BIR demand using Google Trends.
• To explore the relationship between online health queries and patient decision-making for BIR.

Main Methods:

• Utilized Google Trends data for BIR-related search terms in the US (2006-2019).
• Established a network of correlated search terms via pairwise correlative analysis.
• Correlated search volumes with national BIR case data and developed a state-by-state surgical demand index.

Main Results:

• Identified a network of correlated search terms, including "explant," "breast implant removal," "breast implant illness" (BII), and "ALCL," positively correlating with BIR volume.
• Found a negative correlation between "breast augmentation" searches and BIR volume.
• The 2019 BIR surgical demand index indicated highest per capita demand in Nevada, Arizona, and Louisiana.

Conclusions:

• Google Trends effectively tracks public interest and online health information seeking.
• Networks of related search terms demonstrate a correlation with actual BIR surgical volume.
• Analyzing online patient queries aids physicians in understanding decision-making factors for breast implant removal.