The SADI personal health lens: A web browser-based system for identifying personally relevant drug interactions

Background: the web provides widespread access to vast quantities of health-related information that can improve quality-of-life through better understanding of personal symptoms,medical conditions,and available treatments. unfortunately,identifying a credible and personally relevant subset of information can be a time-consuming and challenging task for users without a medical background. objective: the objective of the personal health lens system is to aid users when reading health-related webpages by providing warnings about personally relevant drug interactions. more broadly,we wish to present a prototype for a novel,generalizable approach to facilitating interactions between a patient,their practitioner(s),and the web. methods: we utilized a distributed,semantic web-based architecture for recognizing personally dangerous drugs consisting of: (1) a private,local triple store of personal health information,(2) semantic web services,following the semantic automated discovery and integration (sadi) design pattern,for text mining and identifying substance interactions,(3) a bookmarklet to trigger analysis of a webpage and annotate it with personalized warnings,and (4) a semantic query that acts as an abstract template of the analytical workflow to be enacted by the system. results: a prototype implementation of the system is provided in the form of a java standalone executable jar file. the jar file bundles all components of the system: the personal health database,locally-running versions of the sadi services,and a javascript bookmarklet that triggers analysis of a webpage. in addition,the demonstration includes a hypothetical personal health profile,allowing the system to be used immediately without configuration. usage instructions are provided. conclusions: the main strength of the personal health lens system is its ability to organize medical information and to present it to the user in a personalized and contextually relevant manner. while this prototype was limited to a single knowledge domain (drug/drug interactions),the proposed architecture is generalizable,and could act as the foundation for much richer personalized-health-web clients,while importantly providing a novel and personalizable mechanism for clinical experts to inject their expertise into the browsing experience of their patients in the form of customized semantic queries and ontologies.