Reasoning and discovering novel treatments in linked social health records

Abstract

Discovering novel, alternative treatment options that may have the same efficacy and patient safety as existing drugs is a challenging task for clinicians. Through research and observations, clinicians can form a hypothesis about a possible compatible option, but it is difficult to support or refute it. In this study, we present an approach that utilizes the Semantically Linked Data of different Social Health Records (SHR), which contain patient-generated, health-related contents. The SHRs can provide information about the crowd of online patients' health practices that is lacking within specific Electronic Health Records (EHR) systems. We present the Linked Data framework for building an SHR knowledge base, and describe methods for reasoning and discovering potential novel alternative treatment options, as well as an approach for gathering support that an alternative treatment can indeed be substituted for standard treatment options.