Harnessing Internet Search Data as a Potential Tool for Medical Diagnosis: Literature Review.

Background: Access to accurate medical diagnosis has been hindered by socioeconomic disparities, limited availability of specialized medical professionals, and lack of patient education, among other factors. Inequities in access to high-quality healthcare services exacerbate these challenges, often leading to disparities in health outcomes. Missed or inaccurate diagnoses can lead to delayed or unnecessary treatments, risking worsening of the condition. The historical reliance on direct patient-doctor interactions for diagnosis has often failed to bridge these gaps. The emergence of the internet and digital data in the latter part of the 20th century began to alter this landscape. Early research highlighted the early potential of the internet in patient education, setting the stage for an ever-increasing reliance on online health information, but questions remain regarding information accuracy, access and benefits, and privacy. Internet search data represent one of the largest sources of health data people seek. As of mid-2023, Google's daily search volume was over 8.5 billion queries. Around 5% of Google Searches are health related, and about 77% of persons with a new diagnosis use search engines. These and other data have prompted a series of research projects to address the feasibility and utility of using internet search data for seeking health services. Although the use of patient search data represents just one facet of technology being explored to help obtain more timely and accurate data about patient conditions, this paper focuses only on research studies that use internet search data.

Objective: To explore the potential and challenges of utilizing internet search data in medical diagnosis, focusing on ethical, technical, and policy considerations by assessing the current state of research, identifying gaps and limitations, and proposing future research directions to advance this emerging field.

Methods: A comprehensive analysis of peer-reviewed literature was conducted to examine the landscape of internet search data utilization in medical research. Searchers were performed for published peer-reviewed literature in PubMED (October to December 2023).

Results: Systematic selection according to predefined criteria resulted in the inclusion of 40 articles of the 2,499 identified citations. The analysis reveals a nascent domain of internet search data research in medical diagnosis, characterized by advancements in analytics and data integration. However, significant challenges such as bias, data privacy, and infrastructure limitations hinder its widespread adoption. Emerging initiatives may offer the transformative potential to reshape data collection methodologies and privacy safeguards.

Conclusions: Signals correlating with diagnostic considerations have been identified in certain diseases and conditions, indicating the potential for such data to enhance clinical diagnostic capabilities. However, leveraging internet search data for improved early diagnosis and healthcare outcomes necessitates addressing ethical, technical, and policy challenges effectively. By fostering interdisciplinary collaboration, advancing infrastructure development, and prioritizing patient engagement and consent, researchers can unlock the transformative potential of internet search data in medical diagnosis, ultimately enhancing patient care and advancing healthcare practice and policy.