Using Google Trends Data to Track Healthcare Use for Hand Osteoarthritis

Abstract

Background Google Trends (GT) is a free tool that provides analysis of search traffic for specified terms entered into the Google search engine. In this study, we evaluate the association between public interest in hand osteoarthritis (OA) as determined by GT search volumes and healthcare usage related to hand OA. Methodology We compiled GT data from 2010 to 2017 for the following group of hand OA-related search terms: "hand osteoarthritis," "hand arthritis," "hand swelling," "hand stiffness," and "chronic hand pain." Claims associated with hand OA codes were obtained from an administrative database (14.8 million patients) using International Classification of Diseases codes from 2010 to 2017. We performed trend analysis using univariate linear regression of GT data and hand OA claims. A month-by-month analysis of variation from yearly GT means was conducted for hand OA-related search terms. Results There was increased public interest in hand OA-related search terms from January 2010 to December 2017. Univariate linear regression of GT data for hand OA-related search terms compared with hand OA claims demonstrated a significant positive correlation (p < 0.001, r = 0.707). Peak public interest in hand OA-related search terms was observed in July, May, and June. Conclusions This study demonstrates the ability of GT to track healthcare use related to hand OA. Our data also add to the evidence for monthly variations in public interest related to hand OA. Clinics and surgery centers can employ GT data to anticipate resource utilization by hand OA patients.