Visual analytics for evaluating clinical pathways

Humberto S. Garcia Caballero, Alberto Corvò, Prabhakar M. Dixit, Michel A. Westenberg

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

100 Downloads (Pure)

Abstract

Digital platforms in healthcare institutions enable tracking and recording of patient care pathways. Besides the Electronic Health Records (EHRs), the event logs from Hospital Information Systems (HIS) are a very efficient source of information, from both operational and clinical point of view. Process mining allows comparison of a patient care pathway with the event log(s) from HIS, to understand how well the reality as depicted in the event log fits the expectation as modeled using a care pathway. In this paper, we present SepVis, a visual analytics tool which aims to fill the gap in current process-centric applications by looking at patients' pathways from a clinical point of view. We demonstrate the utility of SepVis in selected use cases derived by the guidelines in the management of sepsis patients.

Original languageEnglish
Title of host publication2017 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages39-46
Number of pages8
ISBN (Electronic)9781538631874
DOIs
Publication statusPublished - 1 Oct 2017
Event8th Annual IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017 - Phoenix, United States
Duration: 1 Oct 2017 → …

Conference

Conference8th Annual IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017
CountryUnited States
CityPhoenix
Period1/10/17 → …

    Fingerprint

Keywords

  • Conformance-checking
  • Event-logs
  • Process Mining
  • Sepsis
  • Visual Analytics

Cite this

Caballero, H. S. G., Corvò, A., Dixit, P. M., & Westenberg, M. A. (2017). Visual analytics for evaluating clinical pathways. In 2017 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017 (pp. 39-46). Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/VAHC.2017.8387499