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


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.

SUBMITTER: Senecal C 

PROVIDER: S-EPMC6583097 | biostudies-literature |

REPOSITORIES: biostudies-literature

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