title: Quantifying care coordination using natural language processing and domain-specific ontology.
abstract: OBJECTIVE
  This research identifies specific care coordination activities used by Aging in Place (AIP) nurse care coordinators and home healthcare (HHC) nurses when coordinating care for older community-dwelling adults and suggests a method to quantify care coordination.
  
  
  METHODS
  A care coordination ontology was built based on activities extracted from 11,038 notes labeled with the Omaha Case management category. From the parsed narrative notes of every patient, we mapped the extracted activities to the ontology, from which we computed problem profiles and quantified care coordination for all patients.
  
  
  RESULTS
  We compared two groups of patients: AIP who received enhanced care coordination (n=217) and HHC who received traditional care (n=691) using 128,135 narratives notes. Patients were tracked from the time they were admitted to AIP or HHC until they were discharged. We found that patients in AIP received a higher dose of care coordination than HHC in most Omaha problems, with larger doses being given in AIP than in HHC in all four Omaha categories.
  
  
  CONCLUSIONS
  'Communicate' and 'manage' activities are widely used in care coordination. This confirmed the expert hypothesis that nurse care coordinators spent most of their time communicating about their patients and managing problems. Overall, nurses performed care coordination in both AIP and HHC, but the aggregated dose across Omaha problems and categories is larger in AIP.
authors.affiliation: Sinclair School of Nursing, University of Missouri, Columbia, Missouri, USA.
authors.forename: Lori L
authors.initials: LL
authors.lastname: Popejoy
authors.affiliation: Department of Computer Science, University of Missouri, Columbia, Missouri, USA.
authors.forename: Mohammed A
authors.initials: MA
authors.lastname: Khalilia
authors.affiliation: Health Management and Informatics Department, University of Missouri, Columbia, Missouri, USA.
authors.forename: Mihail
authors.initials: M
authors.lastname: Popescu
authors.affiliation: School of Social Work, University of Missouri, Columbia, Missouri, USA.
authors.forename: Colleen
authors.initials: C
authors.lastname: Galambos
authors.affiliation: Sinclair School of Nursing, University of Missouri, Columbia, Missouri, USA.
authors.forename: Vanessa
authors.initials: V
authors.lastname: Lyons
authors.affiliation: Sinclair School of Nursing, University of Missouri, Columbia, Missouri, USA.
authors.forename: Marilyn
authors.initials: M
authors.lastname: Rantz
authors.affiliation: Health Management and Informatics Department, University of Missouri, Columbia, Missouri, USA.
authors.forename: Lanis
authors.initials: L
authors.lastname: Hicks
authors.affiliation: Sinclair School of Nursing, University of Missouri, Columbia, Missouri, USA.
authors.forename: Frank
authors.initials: F
authors.lastname: Stetzer
mesh_terms: D000368:Aged; D064229:Biological Ontologies; D066264:Datasets as Topic; D057286:Electronic Health Records; D064650:Home Health Nursing / Q000145:classification / Q000458:organization & administration*; D006801:Humans; D033262:Narration; D009323:Natural Language Processing; D009737:Nursing Records; D010346:Patient Care Management / Q000458:organization & administration*
keywords: Omaha classification system; care coordination; natural language processing; ontology