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A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data Environment

In recent decades, information technology in healthcare, such as Electronic Medical Record (EMR) system, is potential to improve service quality and cost efficiency of the hospital. The continuous use of EMR systems has generated a great amount of data. However, hospitals tend to use these data to r...

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Detalles Bibliográficos
Autores principales: Mao, Hongyi, Sun, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322460/
https://www.ncbi.nlm.nih.gov/pubmed/28280506
http://dx.doi.org/10.1155/2017/9185686
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author Mao, Hongyi
Sun, Yang
author_facet Mao, Hongyi
Sun, Yang
author_sort Mao, Hongyi
collection PubMed
description In recent decades, information technology in healthcare, such as Electronic Medical Record (EMR) system, is potential to improve service quality and cost efficiency of the hospital. The continuous use of EMR systems has generated a great amount of data. However, hospitals tend to use these data to report their operational efficiency rather than to understand their patients. Base on a dataset of inpatients' medical records from a Chinese general public hospital, this study applies a configuration analysis from a managerial perspective and explains inpatients management in a different way. Four inpatient configurations (valued patients, managed patients, normal patients, and potential patients) are identified by the measure of the length of stay and the total hospital cost. The implications of the finding are discussed.
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spelling pubmed-53224602017-03-09 A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data Environment Mao, Hongyi Sun, Yang Int J Telemed Appl Research Article In recent decades, information technology in healthcare, such as Electronic Medical Record (EMR) system, is potential to improve service quality and cost efficiency of the hospital. The continuous use of EMR systems has generated a great amount of data. However, hospitals tend to use these data to report their operational efficiency rather than to understand their patients. Base on a dataset of inpatients' medical records from a Chinese general public hospital, this study applies a configuration analysis from a managerial perspective and explains inpatients management in a different way. Four inpatient configurations (valued patients, managed patients, normal patients, and potential patients) are identified by the measure of the length of stay and the total hospital cost. The implications of the finding are discussed. Hindawi Publishing Corporation 2017 2017-02-09 /pmc/articles/PMC5322460/ /pubmed/28280506 http://dx.doi.org/10.1155/2017/9185686 Text en Copyright © 2017 Hongyi Mao and Yang Sun. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Mao, Hongyi
Sun, Yang
A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data Environment
title A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data Environment
title_full A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data Environment
title_fullStr A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data Environment
title_full_unstemmed A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data Environment
title_short A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data Environment
title_sort way to understand inpatients based on the electronic medical records in the big data environment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5322460/
https://www.ncbi.nlm.nih.gov/pubmed/28280506
http://dx.doi.org/10.1155/2017/9185686
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