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Data Fusion Techniques for Early Warning of Clinical Deterioration

Research output: Chapter in Book/Report/Conference proceedingChapter

Peter Charlton ; Marco Pimentel ; Sharukh Lokhandwala

Original languageEnglish
Title of host publicationSecondary Analysis of Electronic Health Record Data
PublisherSpringer International Publishing
Pages325-338
ISBN (Electronic)9783319437422
ISBN (Print)9783319437408
DOIs
StatePublished - 12 Sep 2016

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Abstract

Algorithms for identification of deteriorating patients from electronic health records (EHRs) fuse vital sign data, which can be measured at the bedside, with additional physiological data from the EHR. It has been observed that these algorithms provide improved performance over traditional early warning scores (EWSs), which are restricted to the use of vital signs alone. This case study demonstrates the development of an algorithm which uses logistic regression to fuse vital signs with additional physiological parameters commonly found in an EHR to predict deterioration.

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