Quantifying Consumer Interest in Medicare Advantage: Development and Usability Study Using Google Trends Data

BACKGROUND: Since 2020, Medicare Advantage (MA)-related internet searches have tripled, accompanied by increased regional marketing by private insurers. Commercial health insurance dominates the internet during enrollment periods, often outpacing public sources in accessibility. Prior studies suggest that MA advertising significantly shapes enrollment and may fuel choices over traditional Medicare in certain subpopulations. We sought to better understand how health plan marketing strategies affect consumers by using Google Trends data and MA health plan enrollment selection. We applied novel analysis to assess statistical relationships among marketing, internet searches, and enrollment data. OBJECTIVE: The objectives of this paper are (1) to establish the validity of Google Trends data as a surrogate measure for consumer MA plan selection by demonstrating stable, repeatable seasonality and domain specificity using control terms such as "car insurance" and "life insurance" at national and Designated Market Area levels; (2) to quantify the congruency between MA search interest and Centers for Medicare and (3) to assess whether local search intensity aligns with advertising exposure by evaluating search behavior as a potential proxy for marketing impact and consumer engagement. METHODS: This study is a retrospective Google Trends analysis of consumer search patterns from January 2004 to December 2024, using relative search volume and conducting correlations with MA enrollment. Search data are accessible via the Google Trends website Explore tool or by applying for Google Trends application programming interface alpha access. MA enrollment data originated from the Centers for Medicare & Medicaid Services MA Dashboard. KFF (formerly the Kaiser Family Foundation) provided the medical advertising marketing data. RESULTS: A consistent, significant correlation between MA advertising and searches on MA exists across US markets, particularly before and during MA enrollment windows. Findings suggest a linkage in user behavior between volume of searches and subsequent enrollment in an MA plan. CONCLUSIONS: Internet search data can provide an open, near-real-time means of tracking patterns in MA-related search activity across time and geography, offering insight into how consumer interest fluctuates around enrollment periods. Our analysis reveals repeatable patterns in consumer interest over time that may be useful for contextualizing insurance marketing dynamics of consumers choosing commercial MA over traditional Medicare benefits. We also identified a significant correlation of seasonal trends in searches using terms associated with MA plans that peaked during the annual enrollment period (October-December). Improved accessibility to Medicare resources and directed messaging can bridge information gaps for underserved populations and can lead to more cost-effective decision-making by Medicare-eligible beneficiaries.