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Brief Report
December 2018

Association of Search Engine Queries for Chest Pain With Coronary Heart Disease Epidemiology

Author Affiliations
  • 1Department of Cardiovascular Diseases, Mayo Clinic and College of Medicine, Rochester, Minnesota
  • 2Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic and College of Medicine, Rochester, Minnesota
JAMA Cardiol. 2018;3(12):1218-1221. doi:10.1001/jamacardio.2018.3459
Key Points

Question  Do search engine queries for chest pain correlate with known epidemiology of coronary heart disease?

Findings  In this study, searches for chest pain and variants closely mirrored the known epidemiology for coronary heart disease in regards to state-by-state variation, seasonal variation, and diurnal variation.

Meaning  Search engine query data may provide an important new resource for cardiovascular research and patient care.

Abstract

Importance  Online search for symptoms is common and may be useful in early identification of patients experiencing coronary heart disease (CHD) and in epidemiologically studying the disease.

Objective  To investigate the correlation of online symptom search for chest pain with disease prevalence of CHD.

Design, Setting, and Participants  This retrospective study used Google Trends, a publicly available tool that provides relative search frequency for queried terms, to find searches for chest pain from January 2010 to June 2017 in the United States, the United Kingdom, and Australia. For the United States, results were obtained by state. These data were compared with publicly available prevalence data from the US Centers for Disease Control and Prevention of CHD hospitalizations by state for the same period. The same terms were used to evaluate seasonal and diurnal variation. Data were analyzed from July 2017 to October 2017.

Main Outcomes and Measures  Correlation of search engine query for chest pain symptoms with temporal and geographic epidemiology.

Results  State-by-state comparisons with reported CHD hospitalization were correlated (R = 0.81; P < .001). Significant monthly variation was appreciated in all countries studied, with the United States, United Kingdom, and Australia showing an 11% to 39% increase in search frequency in winter months compared with summer months. Diurnal variation showed a morning peak for search between local time 6 am and 8 am, with a greater than 100% increase seen in peak searching hours, which was consistent among the 3 countries studied.

Conclusions and Relevance  Relative search frequency closely correlated with CHD epidemiology. This may have important implications for search engines as a resource for patients and a potential early-detection mechanism for physicians moving forward.

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