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

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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Bibliographic Details
Main Authors: Hongyi Mao, Yang Sun
Format: Article
Language:English
Published: Hindawi Limited 2017-01-01
Series:International Journal of Telemedicine and Applications
Online Access:http://dx.doi.org/10.1155/2017/9185686
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spelling doaj-171747515add42b782b990304b0570992020-11-25T00:17:09ZengHindawi LimitedInternational Journal of Telemedicine and Applications1687-64151687-64232017-01-01201710.1155/2017/91856869185686A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data EnvironmentHongyi Mao0Yang Sun1Economics and Management School, Jiujiang University, Jiujiang 332005, ChinaUnion Hospital, Tongji Medical School, Huazhong University of Science and Technology, Wuhan 430022, ChinaIn 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.http://dx.doi.org/10.1155/2017/9185686
collection DOAJ
language English
format Article
sources DOAJ
author Hongyi Mao
Yang Sun
spellingShingle Hongyi Mao
Yang Sun
A Way to Understand Inpatients Based on the Electronic Medical Records in the Big Data Environment
International Journal of Telemedicine and Applications
author_facet Hongyi Mao
Yang Sun
author_sort Hongyi Mao
title 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_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_sort way to understand inpatients based on the electronic medical records in the big data environment
publisher Hindawi Limited
series International Journal of Telemedicine and Applications
issn 1687-6415
1687-6423
publishDate 2017-01-01
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.
url http://dx.doi.org/10.1155/2017/9185686
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