Language Technology and the Clinical Narrative
Electronic health records have the potential for enormous good, but in order for them to live up to their full potential, information about patients -- their symptoms, diagnoses, allergic reactions, medical backgrounds, family histories -- must take the form of standardized, structured, easy-to-manipulate data. One obvious way to get there is to tightly structure the way that doctors create the medical record. As a result, physicians are under increasing pressure to abandon unrestricted natural language and the clinical narrative, and turn the medical documentation process into a jungle of pull-down menus, checkboxes, and restricted vocabularies. In this presentation I argue that the results could be catastrophic, I make the case for preserving the clinical narrative, and I argue for a practical way out of the dilemma: using natural language processing technology to produce the structured records we need, while still allowing physicians the freedom of unrestricted clinical language.
Philip Resnik is a professor at the University of Maryland, holding
joint appointments in the Department of Linguistics and at the
Institute for Advanced Computer Studies. He received his bachelor's
degree in Computer Science at Harvard in 1987, and his Ph.D. in
Computer and Information Science at the University of Pennsylvania in
1993, and he has worked in industry R&D at Bolt Beranek and Newman, IBM T.J. Watson Research Center, and Sun Microsystems Laboratories. Dr. Resnik's research focuses on combining knowledge-based and statistical methods for natural language processing, with applications in machine translation, translation crowdsourcing, and computational social science. His current work is supported by NSF, DARPA, IARPA, ARL, and a Google Research Award. Outside academia, he serves as strategic technology advisor for CodeRyte Inc., the nation's fastest growing provider of NLP solutions in healthcare, and as lead scientist for Converseon, a leading social media consultancy.