title: Using search engine query data to track pharmaceutical utilization: a study of statins.
abstract: OBJECTIVE
  To examine temporal and geographic associations between Google queries for health information and healthcare utilization benchmarks.
  
  
  METHODS
  Retrospective longitudinal study.
  
  
  METHODS
  Using Google Trends and Google Insights for Search data, the search terms Lipitor (atorvastatin calcium; Pfizer, Ann Arbor, MI) and simvastatin were evaluated for change over time and for association with Lipitor revenues. The relationship between query data and community-based resource use per Medicare beneficiary was assessed for 35 US metropolitan areas.
  
  
  RESULTS
  Google queries for Lipitor significantly decreased from January 2004 through June 2009 and queries for simvastatin significantly increased (P <.001 for both), particularly after Lipitor came off patent (P <.001 for change in slope). The mean number of Google queries for Lipitor correlated (r = 0.98) with the percentage change in Lipitor global revenues from 2004 to 2008 (P <.001). Query preference for Lipitor over simvastatin was positively associated (r = 0.40) with a community's use of Medicare services. For every 1% increase in utilization of Medicare services in a community, there was a 0.2-unit increase in the ratio of Lipitor queries to simvastatin queries in that community (P = .02).
  
  
  CONCLUSIONS
  Specific search engine queries for medical information correlate with pharmaceutical revenue and with overall healthcare utilization in a community. This suggests that search query data can track community-wide characteristics in healthcare utilization and have the potential for informing payers and policy makers regarding trends in utilization.
authors.affiliation: School of Medicine, University of Michigan, Ann Arbor, MI 48109, USA.
authors.forename: Nathaniel M
authors.initials: NM
authors.lastname: Schuster
authors.forename: Mary A M
authors.initials: MA
authors.lastname: Rogers
authors.forename: Laurence F
authors.initials: LF
authors.lastname: McMahon
mesh_terms: D003324:Coronary Artery Disease / Q000188:drug therapy / Q000191:economics; D003627:Data Interpretation, Statistical; D006296:Health Services / Q000191:economics / Q000706:statistics & numerical data*; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000191:economics* / Q000627:therapeutic use; D033181:Information Dissemination; D008137:Longitudinal Studies; D006278:Medicare / Q000191:economics / Q000706:statistics & numerical data; D055553:Prescription Drugs / Q000191:economics*; D012189:Retrospective Studies; D057386:Search Engine / Q000191:economics / Q000706:statistics & numerical data*; D013223:Statistics as Topic; D014481:United States
chemical_list: D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors; D055553:Prescription Drugs