title: HARVEST, a longitudinal patient record summarizer.
abstract: OBJECTIVE
  To describe HARVEST, a novel point-of-care patient summarization and visualization tool, and to conduct a formative evaluation study to assess its effectiveness and gather feedback for iterative improvements.
  
  
  METHODS
  HARVEST is a problem-based, interactive, temporal visualization of longitudinal patient records. Using scalable, distributed natural language processing and problem salience computation, the system extracts content from the patient notes and aggregates and presents information from multiple care settings. Clinical usability was assessed with physician participants using a timed, task-based chart review and questionnaire, with performance differences recorded between conditions (standard data review system and HARVEST).
  
  
  RESULTS
  HARVEST displays patient information longitudinally using a timeline, a problem cloud as extracted from notes, and focused access to clinical documentation. Despite lack of familiarity with HARVEST, when using a task-based evaluation, performance and time-to-task completion was maintained in patient review scenarios using HARVEST alone or the standard clinical information system at our institution. Subjects reported very high satisfaction with HARVEST and interest in using the system in their daily practice.
  
  
  CONCLUSIONS
  HARVEST is available for wide deployment at our institution. Evaluation provided informative feedback and directions for future improvements.
  
  
  CONCLUSIONS
  HARVEST was designed to address the unmet need for clinicians at the point of care, facilitating review of essential patient information. The deployment of HARVEST in our institution allows us to study patient record summarization as an informatics intervention in a real-world setting. It also provides an opportunity to learn how clinicians use the summarizer, enabling informed interface and content iteration and optimization to improve patient care.
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, USA Division of Nephrology, Department of Medicine, Columbia University, New York, USA.
authors.forename: Jamie S
authors.initials: JS
authors.lastname: Hirsch
authors.affiliation: College of Physicians and Surgeons, Columbia University, New York, USA.
authors.forename: Jessica S
authors.initials: JS
authors.lastname: Tanenbaum
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, USA.
authors.forename: Sharon
authors.initials: S
authors.lastname: Lipsky Gorman
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, USA.
authors.forename: Connie
authors.initials: C
authors.lastname: Liu
authors.affiliation: New York Presbyterian Hospital, New York, USA.
authors.forename: Eric
authors.initials: E
authors.lastname: Schmitz
authors.affiliation: New York Presbyterian Hospital, New York, USA.
authors.forename: Dritan
authors.initials: D
authors.lastname: Hashorva
authors.affiliation: New York Presbyterian Hospital, New York, USA.
authors.forename: Artem
authors.initials: A
authors.lastname: Ervits
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, USA.
authors.forename: David
authors.initials: D
authors.lastname: Vawdrey
authors.affiliation: New York Presbyterian Hospital, New York, USA.
authors.forename: Marc
authors.initials: M
authors.lastname: Sturm
authors.affiliation: Department of Biomedical Informatics, Columbia University, New York, USA.
authors.forename: Noémie
authors.initials: N
authors.lastname: Elhadad
mesh_terms: D001292:Attitude to Computers; D003626:Data Display; D057286:Electronic Health Records; D006801:Humans; D009323:Natural Language Processing; D012984:Software; D011795:Surveys and Questionnaires; D014584:User-Computer Interface
keywords: electronic health record; natural language processing; summarization; visualization