A FHIR-Enabled Streaming Sepsis Prediction System for ICUs

Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul:2018:4093-4096. doi: 10.1109/EMBC.2018.8513347.

Abstract

Sepsis is a common disease with very costly, potentially deadly implications. Early prediction of Sepsis and initiation of antibiotic is widely considered as an important determinant of patient survival. Cross-institutional validation and implementation of algorithms for early prediction of Sepsis at a minimum require common data formats, streaming analytic platforms for timely risk assessment, and interoperable and standardized interfaces. In this work we present an open-source cloud-based analytic pipeline, which receives de-identified patient data from an interoperable server and produces real-time Sepsis risk scores for Intensive Care Unit (ICU) patients.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Critical Care
  • Humans
  • Intensive Care Units*
  • Risk Assessment
  • Sepsis*