Development & Deployment of a Real-time Healthcare Predictive Analytics Platform

Annu Int Conf IEEE Eng Med Biol Soc. 2023 Jul:2023:1-4. doi: 10.1109/EMBC40787.2023.10340351.

Abstract

The deployment of predictive analytic algorithms that can safely and seamlessly integrate into existing healthcare workflows remains a significant challenge. Here, we present a scalable, cloud-based, fault-tolerant platform that is capable of extracting and processing electronic health record (EHR) data for any patient at any time following admission and transferring results back into the EHR. This platform has been successfully deployed within the UC San Diego Health system and utilizes interoperable data standards to enable portability.Clinical relevance- This platform is currently hosting a deep learning model for the early prediction of sepsis that is operational in two emergency departments.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Delivery of Health Care
  • Electronic Health Records*
  • Emergency Service, Hospital
  • Hospitalization
  • Humans