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Data integration of electronic medical record under administrative decentralization of medical insurance and healthcare in China: a case study

In most regions of China, Electronic Medical Record (EMR) systems in hospitals are developed in an uncoordinated manner. Medical Insurance and Healthcare Administration are localised and organizations gather data from a functional management viewpoint without consideration of wider information shari...

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Autor principal: Wang, Zhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442402/
https://www.ncbi.nlm.nih.gov/pubmed/30929644
http://dx.doi.org/10.1186/s13584-019-0293-9
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author Wang, Zhong
author_facet Wang, Zhong
author_sort Wang, Zhong
collection PubMed
description In most regions of China, Electronic Medical Record (EMR) systems in hospitals are developed in an uncoordinated manner. Medical Insurance and Healthcare Administration are localised and organizations gather data from a functional management viewpoint without consideration of wider information sharing. Discontinuity of data resources is serious. Despite the government’s repeated emphasis on EMR data integration, little progress has been made, causing inconvenience to patients, but also significantly hindering data mining. This exploratory investigation used a case study to identify bottlenecks of data integration and proposes countermeasures. Interviews were carried out with 27 practitioners from central and provincial governments, hospitals, and related enterprises in China. This research shows that EMR data collection without patients’ authorization poses a major hazard to data integration. In addition, non-uniform information standards and hospitals’ unwillingness to share data are also significant obstacles to integration. Moreover, friction caused by the administrative decentralization, as well as unsustainability of public finance investment, also hinders the integration of data resources. To solve these problems, first, a protocol should be adopted for multi-stakeholder participation in data collection. Administrative authorities should then co-establish information standards and a data audit mechanism. Finally, measures are proposed for expanding data integration for multiplying effectiveness and adopting the Public-Private Partnerships model.
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spelling pubmed-64424022019-04-11 Data integration of electronic medical record under administrative decentralization of medical insurance and healthcare in China: a case study Wang, Zhong Isr J Health Policy Res Integrative Article In most regions of China, Electronic Medical Record (EMR) systems in hospitals are developed in an uncoordinated manner. Medical Insurance and Healthcare Administration are localised and organizations gather data from a functional management viewpoint without consideration of wider information sharing. Discontinuity of data resources is serious. Despite the government’s repeated emphasis on EMR data integration, little progress has been made, causing inconvenience to patients, but also significantly hindering data mining. This exploratory investigation used a case study to identify bottlenecks of data integration and proposes countermeasures. Interviews were carried out with 27 practitioners from central and provincial governments, hospitals, and related enterprises in China. This research shows that EMR data collection without patients’ authorization poses a major hazard to data integration. In addition, non-uniform information standards and hospitals’ unwillingness to share data are also significant obstacles to integration. Moreover, friction caused by the administrative decentralization, as well as unsustainability of public finance investment, also hinders the integration of data resources. To solve these problems, first, a protocol should be adopted for multi-stakeholder participation in data collection. Administrative authorities should then co-establish information standards and a data audit mechanism. Finally, measures are proposed for expanding data integration for multiplying effectiveness and adopting the Public-Private Partnerships model. BioMed Central 2019-04-01 /pmc/articles/PMC6442402/ /pubmed/30929644 http://dx.doi.org/10.1186/s13584-019-0293-9 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Integrative Article
Wang, Zhong
Data integration of electronic medical record under administrative decentralization of medical insurance and healthcare in China: a case study
title Data integration of electronic medical record under administrative decentralization of medical insurance and healthcare in China: a case study
title_full Data integration of electronic medical record under administrative decentralization of medical insurance and healthcare in China: a case study
title_fullStr Data integration of electronic medical record under administrative decentralization of medical insurance and healthcare in China: a case study
title_full_unstemmed Data integration of electronic medical record under administrative decentralization of medical insurance and healthcare in China: a case study
title_short Data integration of electronic medical record under administrative decentralization of medical insurance and healthcare in China: a case study
title_sort data integration of electronic medical record under administrative decentralization of medical insurance and healthcare in china: a case study
topic Integrative Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6442402/
https://www.ncbi.nlm.nih.gov/pubmed/30929644
http://dx.doi.org/10.1186/s13584-019-0293-9
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