Linking Annual Prescription Volume of Antidepressants to Corresponding Web Search Query Data: A Possible Proxy for Medical Prescription Behavior?

AbstractPersons using the Internet to retrieve medical information generate large amounts of health-related data, which are increasingly used in modern health sciences. We analyzed the relation between annual prescription volumes (APVs) of several antidepressants with marketing approval in Germany and corresponding web search query data generated in Google to test whether web search query volume may be a proxy for medical prescription practice. We obtained APVs of several antidepressants related to corresponding prescriptions at the expense of the statutory health insurance in Germany from 2004 to 2013. Web search query data generated in Germany and related to defined search terms (active substance or brand name) were obtained with Google Trends. We calculated correlations (Person’s r) between the APVs of each substance and the respective annual “search share” values; coefficients of determination (R2) were computed to determine the amount of variability shared by the 2 variables. Significant and strong correlations between substance-specific APVs and corresponding annual query volumes were found for each substance during the observational interval: agomelatine (r = 0.968, R2 = 0.932, P = 0.01), bupropion (r = 0.962, R2 = 0.925, P = 0.01), citalopram (r = 0.970, R2 = 0.941, P = 0.01), escitalopram (r = 0.824, R2 = 0.682, P = 0.01), fluoxetine (r = 0.885, R2 = 0.783, P = 0.01), paroxetine (r = 0.801, R2 = 0.641, P = 0.01), and sertraline (r = 0.880, R2 = 0.689, P = 0.01). Although the used data did not allow to perform an analysis with a higher temporal resolution (quarters, months), our results suggest that web search query volume may be a proxy for corresponding prescription behavior. However, further studies analyzing other pharmacologic agents and prescription data that facilitate an increased temporal resolution are needed to confirm this hypothesis.

[1]  Brandon H Hidaka Depression as a disease of modernity: explanations for increasing prevalence. , 2012, Journal of affective disorders.

[2]  Jacob E Simmering,et al.  Web search query volume as a measure of pharmaceutical utilization and changes in prescribing patterns. , 2014, Research in social & administrative pharmacy : RSAP.

[3]  John S. Brownstein,et al.  Erratum to: Digital Drug Safety Surveillance: Monitoring Pharmaceutical Products in Twitter , 2014, Drug Safety.

[4]  R. Platt,et al.  The new Sentinel Network--improving the evidence of medical-product safety. , 2009, The New England journal of medicine.

[5]  E. Gabrilovich,et al.  Postmarket Drug Surveillance Without Trial Costs: Discovery of Adverse Drug Reactions Through Large-Scale Analysis of Web Search Queries , 2013, Journal of medical Internet research.

[6]  T. Furukawa,et al.  Paroxetine versus other anti-depressive agents for depression. , 2007, Cochrane Database of Systematic Reviews.

[7]  Ryen W. White,et al.  Web-scale pharmacovigilance: listening to signals from the crowd , 2013, J. Am. Medical Informatics Assoc..

[8]  Ryen W. White,et al.  Toward Enhanced Pharmacovigilance Using Patient-Generated Data on the Internet , 2014, Clinical pharmacology and therapeutics.

[9]  J. Pirkis,et al.  Suicide-related Internet use: A review , 2015, The Australian and New Zealand journal of psychiatry.

[10]  R. Ravasio,et al.  Use and treatment modalities for SSRI and SNRI antidepressants in Italy during the period 2003–2009 , 2012, Current medical research and opinion.

[11]  H. Westenberg,et al.  Tolerability and safety of fluvoxamine and other antidepressants , 2006, International journal of clinical practice.

[12]  L Pochard,et al.  Analysis of patients' narratives posted on social media websites on benfluorex's (Mediator®) withdrawal in France , 2014, Journal of clinical pharmacy and therapeutics.

[13]  H. Varian,et al.  Predicting the Present with Google Trends , 2009 .

[14]  M. Schuemie,et al.  Combining electronic healthcare databases in Europe to allow for large‐scale drug safety monitoring: the EU‐ADR Project , 2011, Pharmacoepidemiology and drug safety.

[15]  P. F. Adams,et al.  Use of the internet for health information: United States, 2009. , 2011, NCHS data brief.

[16]  B. Guthrie,et al.  Trends in primary care antidepressant prescribing 1995-2007: a longitudinal population database analysis. , 2011, The British journal of general practice : the journal of the Royal College of General Practitioners.

[17]  Jerry Avorn,et al.  Evaluating drug effects in the post-Vioxx world: there must be a better way. , 2006, Circulation.

[18]  Robin E. Ferner,et al.  Internet Accounts of Serious Adverse Drug Reactions , 2012, Drug Safety.

[19]  C. Rummel-Kluge,et al.  Mental health related Internet use among psychiatric patients: a cross-sectional analysis , 2014, BMC Psychiatry.

[20]  Geoff Watts Google watches over flu , 2008, BMJ : British Medical Journal.

[21]  J. Overhage,et al.  Advancing the Science for Active Surveillance: Rationale and Design for the Observational Medical Outcomes Partnership , 2010, Annals of Internal Medicine.

[22]  G. Glaeske,et al.  Trends in antidepressant prescriptions for children and adolescents in Germany from 2005 to 2012 , 2014, Pharmacoepidemiology and drug safety.

[23]  L. Baker,et al.  Use of the Internet and e-mail for health care information: results from a national survey. , 2003, JAMA.

[24]  T. Svensson,et al.  Experiences from consumer reports on psychiatric adverse drug reactions with antidepressant medication: a qualitative study of reports to a consumer association , 2012, BMC Pharmacology and Toxicology.

[25]  Jeremy Ginsberg,et al.  Detecting influenza epidemics using search engine query data , 2009, Nature.

[26]  Nicola Luigi Bragazzi,et al.  Psychology Research and Behavior Management Dovepress a Google Trends-based Approach for Monitoring Nssi , 2022 .

[27]  Vicki L Burt,et al.  Prescription drug use continues to increase: U.S. prescription drug data for 2007-2008. , 2010, NCHS data brief.

[28]  N. Freemantle,et al.  SSRIs versus other antidepressants for depressive disorder. , 2000, The Cochrane database of systematic reviews.

[29]  M. Menchetti,et al.  Trend in SSRI-SNRI antidepressants prescription over a 6-year period and predictors of poor adherence , 2013, European Journal of Clinical Pharmacology.

[30]  D. Wysowski,et al.  Adverse drug event surveillance and drug withdrawals in the United States, 1969-2002: the importance of reporting suspected reactions. , 2005, Archives of internal medicine.

[31]  Robin E Ferner,et al.  Internet accounts of serious adverse drug reactions: a study of experiences of Stevens-Johnson syndrome and toxic epidermal necrolysis. , 2012, Drug safety.

[32]  D. Lester,et al.  Using google searches on the internet to monitor suicidal behavior. , 2013, Journal of affective disorders.

[33]  John D Seeger,et al.  Drug safety in the digital age. , 2014, The New England journal of medicine.