title: Combining Structured and Free-text Data for Automatic Coding of Patient Outcomes.
abstract: Integrating easy-to-extract structured information such as medication and treatments into current natural language processing based systems can significantly boost coding performance; in this paper, we present a system that rigorously attempts to validate this intuitive idea. Based on recent i2b2 challenge winners, we derive a strong language model baseline that extracts patient outcomes from discharge summaries. Upon incorporating additional clinical cues into this language model, we see a significant boost in performance to F1 of 88.3 and a corresponding reduction in error of 23.52%.
authors.affiliation: Computer Science Department.
authors.forename: Suchi
authors.initials: S
authors.lastname: Saria
authors.forename: Gayle
authors.initials: G
authors.lastname: McElvain
authors.forename: Anand K
authors.initials: AK
authors.lastname: Rajani
authors.forename: Anna A
authors.initials: AA
authors.lastname: Penn
authors.forename: Daphne L
authors.initials: DL
authors.lastname: Koller
mesh_terms: D006801:Humans; D016247:Information Storage and Retrieval; D009323:Natural Language Processing