The Burgeoning of Medical Social-Media Postings and the Need for Improved Natural Language Mapping Tools

Abstract

Medical social-media data provides a wealth of data generated by both healthcare professionals and patients alike. In fact, there are many medical social-media sites such as forums, where patients freely dialog with a healthcare professional or with other patients, often posing questions and responding to advice, or Weblogs, where groups of people describe their experiences with medical conditions and the various treatment plans to treat those conditions. All in all, one can no longer ignore the fact that social media has dramatically changed the structure of healthcare delivery in many ways. Simply from a medical data standpoint alone, social-media platforms have altered the way medical information is disseminated. That is, important medical information is no longer found exclusively in patients’ clinical narratives, commonly shared by physicians and other healthcare workers at regular professional meetings and conferences. Instead, user-generated content on the Web has become a new source of useful information to be added to the conventional methods of collecting clinical data. The challenge we face, however, is to design information extraction tools that can make the rich resources of medical data found in social-media postings exploitable. In this chapter we analyze the linguistic features of medical social-media postings juxtaposed to the linguistic features of both clinical narratives (e.g., discharge summaries, chart reviews, and operative reports) and biomedical literature, for which there already exists tools for performing information extraction. We show the shortcomings of these mapping tools when applied to medical social-media postings, and propose ways to improve such tools so that the wealth of medical data located in medical social-media can be made available to healthcare providers, pharmaceutical companies, and government-supported epidemiological agencies.