title: Interactive Cohort Identification of Sleep Disorder Patients Using Natural Language Processing and i2b2.
abstract: Nationwide Children's Hospital established an i2b2 (Informatics for Integrating Biology & the Bedside) application for sleep disorder cohort identification. Discrete data were gleaned from semistructured sleep study reports. The system showed to work more efficiently than the traditional manual chart review method, and it also enabled searching capabilities that were previously not possible.
  
  
  OBJECTIVE
  We report on the development and implementation of the sleep disorder i2b2 cohort identification system using natural language processing of semi-structured documents.
  
  
  METHODS
  We developed a natural language processing approach to automatically parse concepts and their values from semi-structured sleep study documents. Two parsers were developed: a regular expression parser for extracting numeric concepts and a NLP based tree parser for extracting textual concepts. Concepts were further organized into i2b2 ontologies based on document structures and in-domain knowledge.
  
  
  RESULTS
  26,550 concepts were extracted with 99% being textual concepts. 1.01 million facts were extracted from sleep study documents such as demographic information, sleep study lab results, medications, procedures, diagnoses, among others. The average accuracy of terminology parsing was over 83% when comparing against those by experts. The system is capable of capturing both standard and non-standard terminologies. The time for cohort identification has been reduced significantly from a few weeks to a few seconds.
  
  
  CONCLUSIONS
  Natural language processing was shown to be powerful for quickly converting large amount of semi-structured or unstructured clinical data into discrete concepts, which in combination of intuitive domain specific ontologies, allows fast and effective interactive cohort identification through the i2b2 platform for research and clinical use.
authors.affiliation: Research Information Solutions and Innovations , Columbus, OH.
authors.forename: W
authors.initials: W
authors.lastname: Chen
authors.affiliation: Center for Innovation in Pediatric Practice , Columbus, OH.
authors.forename: R
authors.initials: R
authors.lastname: Kowatch
authors.affiliation: Research Information Solutions and Innovations , Columbus, OH.
authors.forename: S
authors.initials: S
authors.lastname: Lin
authors.affiliation: Sleep Disorder Center, Nationwide Children's Hospital , Columbus, OH.
authors.forename: M
authors.initials: M
authors.lastname: Splaingard
authors.affiliation: Research Information Solutions and Innovations , Columbus, OH.
authors.forename: Y
authors.initials: Y
authors.lastname: Huang
mesh_terms: D064229:Biological Ontologies; D015331:Cohort Studies; D057225:Data Mining; D006801:Humans; D008490:Medical Informatics / Q000379:methods*; D009323:Natural Language Processing; D009626:Terminology as Topic; D014584:User-Computer Interface
keywords: Sleep disorder; clinical ontology; cohort identification; i2b2; natural language processing (NLP)