Clinical Guidelines as Executable and Interactive Workflows with FHIR-Compliant Health Data Input Using GLEAN

William Van Woensel, Samina Abidi, Karthik Tennankore, George Worthen, Syed Sibte Raza Abidi

Producción científica: Capítulo en Libro/Reporte/Acta de conferenciaContribución a la conferencia

2 Citas (Scopus)

Resumen

By computerizing paper-based clinical guidelines on diagnosing and treating illnesses, knowledge-driven Clinical Decision Support (CDS) can issue salient and timely recommendations in line with the latest evidence. To access up-to-date patient health data, such CDS require interoperability with Electronic Health Records (EHR). The GLEAN model supports knowledge-based CDS by (a) encoding the guideline decision logic using Task Network Models (TNM) based on an extensible Finite State Machine (FSM); and (b) associating clinical tasks with HL7 FHIR resources that offer interoperability with FHIR-compliant EHR. In this demo, we show an online visualization tool that explains GLEAN CIG as visual and interactive workflows. Clinicians can dynamically submit HL7 FHIR patient data using the tool to drive the traversal of the workflow.

Idioma originalEnglish
Título de la publicación alojadaArtificial Intelligence in Medicine - 20th International Conference on Artificial Intelligence in Medicine, AIME 2022, Proceedings
EditoresMartin Michalowski, Syed Sibte Raza Abidi, Samina Abidi
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas421-425
Número de páginas5
ISBN (versión impresa)9783031093418
DOI
EstadoPublished - 2022
Evento20th International Conference on Artificial Intelligence in Medicine, AIME 2022 - Halifax, Canada
Duración: jun. 14 2022jun. 17 2022

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen13263 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conference

Conference20th International Conference on Artificial Intelligence in Medicine, AIME 2022
País/TerritorioCanada
CiudadHalifax
Período6/14/226/17/22

Nota bibliográfica

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

ASJC Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

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