# 3.6 Healthcare Big data statistics & search service Healthcare big data statistics & search service is a highly difficult analytic solution that easily converts the complexly dispersed healthcare and medical data held by users into meaningful information. Although the main data include healthcare data including medical data, sub-medical data with relatively lower importance are also included. Sub-medical data corresponds to name/age/gender/name of insurance company/ID code of medical department/family doctor/medical treatment cost/ID code for disease and illness, etc.. For example, In the case of medical institute, it is possible to support establishment of medical big data-based research ecosystem by markedly improve the resources required for medical data analysis at the time of clinical studies. Moreover, user can discern through the disclosed statistics that specific insurance company can provide insurance services optimized for his/her circumstances in advance. It is therefore possible to realize easy access and linkage with healthcare big data for research among patient, medical scientist and corporation by markedly reducing enormous amount of time and efforts as well as costs necessary for healthcare service researches based on this solution. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://lemonchain.gitbook.io/lemonchain_whitepaper_v1.9_eng/whitepaper/3.-lemonchain-new-healthcare-data-ecosystem/3.6-healthcare-big-data-statistics-and-search-service.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.