Understanding patient behaviour through search data
Patients’ search behaviour is a real‑time window into what people worry about, misunderstand, and struggle to ask in the clinic, and tools like Google’s People Also Asked can turn that noisy stream into surprisingly actionable insight for clinicians, health systems, and innovators
Large surveys suggest the majority of adults now look online for health information, often weekly or even daily, and mostly through general search engines like Google. Patients most commonly look up specific diseases, symptoms, treatments, medications, and “which doctor/where to go” questions before or after visits. Health‑related queries are typically longer, more contextual, and more frequently misspelled than general searches, which itself signals uncertainty and anxiety.
Because people search from home and on their own devices, their queries often reveal concerns they never voice to clinicians, including taboo topics (sexual health, mental health, stigma‑laden diagnoses) and practical issues (cost, work, childcare) that rarely fit into a 15‑minute consult. In one emergency‑department study, health‑related searches roughly doubled in the week before presentation, showing that search behaviour tracks symptom escalation and decision‑making about when to seek care.
What queries reveal about the “patient journey”
Search histories around an episode of illness tend to follow a loose sequence: symptom interpretation, self‑triage, label seeking (“what could this be?”), treatment options, and logistics (which service, when, and how to access it). For example, parents of children with cancer shifted from generic symptom searches to specific diagnosis, treatment side effects, and support queries in the months around diagnosis and treatment, mapping a clear emotional and informational trajectory.
Systematic reviews show that online information seeking is shaped by age, education, digital literacy, and psychological orientation (promotion vs prevention focus), and that many people use search to prepare questions before appointments and to check or expand on advice afterwards. This means search logs do not just describe isolated questions; they sketch out pathways to care, revealing where people get stuck, bounce between sites, or abandon their journey altogether.
The special role of “People Also Asked”
Google’s People Also Asked (PAA) boxes aggregate the most frequently asked follow‑up questions linked to a given search, powered by large‑scale machine‑learning over millions of queries. In spine surgery, for instance, researchers used PAA to map the common patient questions that cluster around procedure names, uncovering patterns that would be hard to get from small clinic surveys alone.
This approach is powerful because it captures what patients actually type, not what they later remember and are willing to disclose on a questionnaire, and it surfaces the specific “next questions” that current content is failing to answer. If “back pain” consistently triggers “Is my back pain cancer?” or “When should I worry about back pain?”, that tells clinicians both what fears are most salient and where clearer safety‑net messaging is needed.
Insights for clinicians and health systems
Mining search queries and PAA patterns can yield several practical insights:
- Clinical communication gaps: If patients repeatedly search “normal side effects of [drug]” or “how long does [symptom] last after [procedure]”, discharge and consent materials may be too generic or poorly timed.
- Mismatched triage and access: Rising volumes of “urgent care or emergency for [symptom]?” questions, especially when health‑related searches spike in the days before ED visits, can highlight confusion about which service to use.
- Emerging public‑health concerns: During outbreaks such as COVID‑19, shifts in symptom and prevention queries have been used to track anxiety, misinformation, and behaviour change at population scale.
- Differential access and literacy issues: Studies link online health information seeking to education level, internet experience, and eHealth literacy, suggesting that who searches—and who doesn’t—can flag digital equity gaps.
An illustration: if a youth mental‑health service sees rising regional searches for “teen anxiety can’t sleep” plus PAA questions like “Is my teen’s anxiety normal?” and “How do I talk to my child’s school?”, that combination directly points to content and service redesign opportunities—school‑facing resources, parent guides, and clearer pathways to early intervention.
Beyond curiosity: turning search insight into better care
To move from observation to action, health organisations can treat search data and PAA outputs as a continuous feedback loop for service and content design. Public‑facing materials can be structured around the real question clusters that PAA surfaces, using plain language and layering information in the order people actually ask for it. Search data can also help prioritise which conditions or demographics need tailored digital pathways, as reviews show a growing and diverse set of online health‑seeking behaviours across age groups, including young adults.
All of this has to sit on a foundation of privacy, consent, and transparency: work linking individual search histories with clinical data has shown that about half of patients are willing to share their searches, but only when they understand how the data are used and protected. With thoughtful governance, analysing what patients search for—plus what they “also ask”—can evolve from a passive by‑product of the digital age into an active tool for designing more responsive, humane, and trustworthy healthcare.
Sources:
- Jia X, Pang Y, Liu LS, et al. Online health information seeking behavior: a systematic review. Healthcare (Basel). 2021;9(12):1740. doi:10.3390/healthcare9121740.
- Rong H, Chen M, Zhou H, et al. Online health information–seeking behaviors among the general Chinese population: cross-sectional study. JMIR Form Res. 2025;9(1):e56028.
- Cai HC, et al. Using the Google search engine for health information. (Article assessing quality of online health and nutrition information for “supplements for cancer”). Nutr Today or related outlet; 2021; details as per journal site.
- Kasthuri V, Venkatraman V, Mastrokostas PG, et al. Modern internet search analytics and spine. Global Spine J. 2023;13(7):1489‑1497. doi:10.1177/21925682231174263.
- Mastrokostas PG, et al. Modern internet search analytics: most searched questions and online resources for scoliosis management. Global Spine J. 2025; ahead of print. doi:10.1177/21925682241248110.
- Downing GJ, et al. Harnessing internet search data as a potential tool for early health concern detection: a scoping review. JMIR Med Inform. 2025;13(2):eXXXXX (in press pagination).
- Sadek N, Phillips C, et al. Utilizing Google search data to gain insight into health: emergency department and pediatric oncology pilot studies. Center for Health Technology and Innovation, University of Pennsylvania; 2024. Project report and web summary.
- Frontiers in Public Health. People behaviour during health information searching in the COVID‑19 context. Front Public Health. 2023;11:1166639.
- Google. Advancing health research with Google Health Studies. Google Blog. 8 Dec 2020. Accessed 2026.
- Digital pathways to healthcare: a systematic review for the European Society of Cardiology. Front Public Health. 2025;13:1497025.
- Online health information seeking behaviour of patients in primary care (family practice article). Fam Pract. 2022;39(1):38‑46.
- Evaluating the process of online health information searching: a qualitative study of consumer perspectives. J Med Internet Res or related open‑access outlet; 2014; article accessible via PubMed Central.
- Fox S. The social life of health information. Pew Research Center; 2014. (Cited within later search‑analytics and OHISB articles for prevalence figures.)
- Google for Health. What is Google for Health? Product overview and documentation. Accessed 2026.
- YouTube leads Google AI overviews citations for health searches. eWeek. 26 Jan 2026
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