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

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)...

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Autores principales: Boussina, Aaron, Shashikumar, Supreeth, Amrollahi, Fatemeh, Pour, Hayden, Hogarth, Michael, Nemati, Shamim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10120788/
https://www.ncbi.nlm.nih.gov/pubmed/37090509
http://dx.doi.org/10.1101/2023.04.10.23288373
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author Boussina, Aaron
Shashikumar, Supreeth
Amrollahi, Fatemeh
Pour, Hayden
Hogarth, Michael
Nemati, Shamim
author_facet Boussina, Aaron
Shashikumar, Supreeth
Amrollahi, Fatemeh
Pour, Hayden
Hogarth, Michael
Nemati, Shamim
author_sort Boussina, Aaron
collection PubMed
description 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.
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spelling pubmed-101207882023-04-22 Development & Deployment of a Real-time Healthcare Predictive Analytics Platform Boussina, Aaron Shashikumar, Supreeth Amrollahi, Fatemeh Pour, Hayden Hogarth, Michael Nemati, Shamim medRxiv Article 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. Cold Spring Harbor Laboratory 2023-04-11 /pmc/articles/PMC10120788/ /pubmed/37090509 http://dx.doi.org/10.1101/2023.04.10.23288373 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Boussina, Aaron
Shashikumar, Supreeth
Amrollahi, Fatemeh
Pour, Hayden
Hogarth, Michael
Nemati, Shamim
Development & Deployment of a Real-time Healthcare Predictive Analytics Platform
title Development & Deployment of a Real-time Healthcare Predictive Analytics Platform
title_full Development & Deployment of a Real-time Healthcare Predictive Analytics Platform
title_fullStr Development & Deployment of a Real-time Healthcare Predictive Analytics Platform
title_full_unstemmed Development & Deployment of a Real-time Healthcare Predictive Analytics Platform
title_short Development & Deployment of a Real-time Healthcare Predictive Analytics Platform
title_sort development & deployment of a real-time healthcare predictive analytics platform
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10120788/
https://www.ncbi.nlm.nih.gov/pubmed/37090509
http://dx.doi.org/10.1101/2023.04.10.23288373
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