OBJECTIVE: To determine whether Internet search volume for kidney stones has seasonal and geographic distributions similar to known kidney stone incidence. MATERIAL AND METHODS: Google Insights for Search analyzes a portion of Google web searches from all Google domains to compute how many searches are performed for a given term relative to the total number of searches done over a specific time interval and geographic region. Selected terms related to kidney stones were examined to determine which most closely tracked kidney stone incidence. Google Insights for Search data were correlated with hospital admissions for the emergent treatment of nephrolithiasis found through the Nationwide Inpatient Sample. Ambient temperature in Seattle and New York were compared with search volume for these regions to display qualitative relationships. RESULTS: The term "kidney stones" had the highest seasonal correlation of terms examined (r = .81, P = .0014). Google Insights for Search output and national Inpatient Sample admissions also correlated when regions were compared (r = .90, P = .005). Qualitative relationships between ambient temperatures and kidney stone search volume do exist. CONCLUSIONS: Internet search volume activity for kidney stones correlates with temporal and regional kidney stone insurance claims data. In the future, with improved modeling of search detection algorithms and increased Internet usage, search volume has the potential to serve as a surrogate for kidney stone incidence.
OBJECTIVE: To determine whether Internet search volume for kidney stones has seasonal and geographic distributions similar to known kidney stone incidence. MATERIAL AND METHODS: Google Insights for Search analyzes a portion of Google web searches from all Google domains to compute how many searches are performed for a given term relative to the total number of searches done over a specific time interval and geographic region. Selected terms related to kidney stones were examined to determine which most closely tracked kidney stone incidence. Google Insights for Search data were correlated with hospital admissions for the emergent treatment of nephrolithiasis found through the Nationwide Inpatient Sample. Ambient temperature in Seattle and New York were compared with search volume for these regions to display qualitative relationships. RESULTS: The term "kidney stones" had the highest seasonal correlation of terms examined (r = .81, P = .0014). Google Insights for Search output and national Inpatient Sample admissions also correlated when regions were compared (r = .90, P = .005). Qualitative relationships between ambient temperatures and kidney stone search volume do exist. CONCLUSIONS: Internet search volume activity for kidney stones correlates with temporal and regional kidney stone insurance claims data. In the future, with improved modeling of search detection algorithms and increased Internet usage, search volume has the potential to serve as a surrogate for kidney stone incidence.
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