National Utilization and Forecasting of Ototopical Antibiotics: Medicaid Data Versus "Dr. Google".

Journal Article (Journal Article)

OBJECTIVES: To forecast national Medicaid prescription volumes for common ototopical antibiotics, and correlate prescription volumes with internet user search interest using Google Trends (GT). STUDY DESIGN: National United States Medicaid prescription and GT user search database analysis. METHODS: Quarterly national Medicaid summary drug utilization data and weekly GT search engine data for ciprofloxacin-dexamethasone (CD), ofloxacin (OF), and Cortisporin (CS) ototopicals were obtained from January 2008 to July 2014. Time series analysis was used to assess prescription seasonality, Holt-Winter's method for forecasting quarterly prescription volumes, and Pearson correlations to compare GT and Medicaid data. RESULTS: Medicaid prescription volumes demonstrated sinusoidal seasonality for OF (r = 0.91), CS (r = 0.71), and CD (r = 0.62) with annual peaks in July, August, and September. In 2017, OF was forecasted to be the most widely prescribed ototopical, followed by CD. CS was the least prescribed, and volumes were forecasted to decrease 9.0% by 2017 from 2014. GT user search interest demonstrated analogous sinusoidal seasonality and significant correlations with Medicaid data prescriptions for CD (r = 0.38, p = 0.046), OF (r = 0.74, p < 0.001), CS (r = 0.49, p = 0.008). CONCLUSION: We found that OF, CD, and CS ototopicals have sinusoidal seasonal variation with Medicaid prescription volume peaks occurring in the summer. After 2012, OF was the most commonly prescribed ototopical, and this trend was forecasted to continue. CS use was forecasted to decrease. Google user search interest in these ototopical agents demonstrated analogous seasonal variation. Analyses of GT for interest in ototopical antibiotics may be useful for health care providers and administrators as a complementary method for assessing healthcare utilization trends.

Full Text

Duke Authors

Cited Authors

  • Crowson, MG; Schulz, K; Tucci, DL

Published Date

  • September 2016

Published In

Volume / Issue

  • 37 / 8

Start / End Page

  • 1049 - 1054

PubMed ID

  • 27348390

Electronic International Standard Serial Number (EISSN)

  • 1537-4505

Digital Object Identifier (DOI)

  • 10.1097/MAO.0000000000001115


  • eng

Conference Location

  • United States