Towards event sequence representation, reasoning and visualization for EHR data

Cui Tao, Krist Wongsuphasawat, Kim Clark, Catherine Plaisant, Ben Shneiderman, Christopher G. Chute

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

Efficient analysis of event sequences and the ability to answer time-related, clinically important questions can accelerate clinical research in several areas such as causality assessments, decision support systems, and retrospective studies. The Clinical Narrative Temporal Reasoning Ontology (CNTRO)-based system is designed for semantically representing, annotating, and inferring temporal relations and constraints for clincial events in Electronic Health Records (EHR) represented in both structured and unstructured ways. The LifeFlow system is designed to support an interactive exploration of event sequences using visualization techniques. The combination of the two systems will provide a comprehensive environment for users to visualize inferred temporal relationships from EHR data. This paper discusses our preliminary efforts on connecting the two systems and the benefits we envision from such an environment.

Original languageEnglish (US)
Title of host publicationIHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Pages801-805
Number of pages5
DOIs
StatePublished - Mar 8 2012
Event2nd ACM SIGHIT International Health Informatics Symposium, IHI'12 - Miami, FL, United States
Duration: Jan 28 2012Jan 30 2012

Publication series

NameIHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium

Other

Other2nd ACM SIGHIT International Health Informatics Symposium, IHI'12
CountryUnited States
CityMiami, FL
Period1/28/121/30/12

Keywords

  • EHR
  • Semantic web
  • Temporal relation reasoning
  • Time trend visualization

ASJC Scopus subject areas

  • Health Informatics
  • Health Information Management

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  • Cite this

    Tao, C., Wongsuphasawat, K., Clark, K., Plaisant, C., Shneiderman, B., & Chute, C. G. (2012). Towards event sequence representation, reasoning and visualization for EHR data. In IHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium (pp. 801-805). (IHI'12 - Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium). https://doi.org/10.1145/2110363.2110461