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改善日本医疗数据系统以有效管理新冠病毒疾病患者:一项全国性调查。

Improvement of the Japanese healthcare data system for the effective management of patients with COVID-19: A national survey.

作者信息

Takeshita Kohei, Takao Hiroyuki, Imoto Seiya, Murayama Yuichi

机构信息

Division of Innovation for Medical Information Technology, The Jikei University School of Medicine, Tokyo, Japan.

Division of Innovation for Medical Information Technology, The Jikei University School of Medicine, Tokyo, Japan; Department of Neurosurgery, The Jikei University School of Medicine, Tokyo, Japan.

出版信息

Int J Med Inform. 2022 Mar 24;162:104752. doi: 10.1016/j.ijmedinf.2022.104752.

DOI:10.1016/j.ijmedinf.2022.104752
PMID:35390591
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8944184/
Abstract

OBJECTIVE

The burden of data entry in public platforms used for reporting patients with novel coronavirus disease 2019 (COVID-19) is a challenge in the healthcare setting. The key to mitigating the burden of data entry is system integration and elimination of double data entry. In addition, the linkage between public platforms and electronic medical records (EMRs) involves external networks, which are an important target for security management. The purpose of this study was to elucidate the status and challenges of infrastructure for continuous data reporting from hospitals in Japan.

MATERIALS AND METHODS

An online survey of Japanese care delivery institutions was conducted from January 25 to February 22, 2021, to obtain data on the admission of patients with COVID-19, use of information infrastructures, and status of network connections with external organizations. The survey request was distributed to each care delivery institution by Japanese health authorities.

RESULTS

Of the care delivery institutions that responded to the survey, 53.9% treated patients with COVID-19. Of these institutions, 73.3% used EMRs. 57.8% of the EMRs were connected to an external network. The purpose of connecting to the external network was to contribute to regional health information-sharing with other hospitals (22.0%), report online medical insurance claims (27.5%), and conduct intrahospital system maintenance (61.5%). A frequent concern about connecting an EMR to an external network was data leakage.

DISCUSSION

In cases where the frequency of reporting patients with COVID-19 is high, health authorities should provide information regarding anti-data-leakage measures and coordinate frameworks for efficient, sustainable data collection.

CONCLUSIONS

We obtained information on existing infrastructures for patient data sharing among care delivery institutions and public health authorities. Our findings may be referenced by the government to make informed decisions about investments.

摘要

目的

在医疗环境中,用于报告2019年新型冠状病毒病(COVID-19)患者的公共平台的数据录入负担是一项挑战。减轻数据录入负担的关键是系统集成和消除重复数据录入。此外,公共平台与电子病历(EMR)之间的连接涉及外部网络,而外部网络是安全管理的重要目标。本研究的目的是阐明日本医院持续数据报告基础设施的现状和挑战。

材料与方法

2021年1月25日至2月22日对日本医疗服务机构进行了在线调查,以获取有关COVID-19患者入院情况、信息基础设施使用情况以及与外部组织网络连接状况的数据。调查请求由日本卫生当局分发给每个医疗服务机构。

结果

在回复调查的医疗服务机构中,53.9%治疗过COVID-19患者。在这些机构中,73.3%使用电子病历。57.8%的电子病历连接到了外部网络。连接外部网络的目的是促进与其他医院的区域健康信息共享(22.0%)、在线提交医疗保险理赔申请(27.5%)以及进行医院内部系统维护(61.5%)。将电子病历连接到外部网络时常见的担忧是数据泄露。

讨论

在COVID-19患者报告频率较高的情况下,卫生当局应提供有关防数据泄露措施的信息,并协调高效、可持续数据收集的框架。

结论

我们获得了有关医疗服务机构和公共卫生当局之间患者数据共享现有基础设施的信息。我们的研究结果可供政府参考,以便做出明智的投资决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/44525e2f98a1/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/a7f1a618d260/ga1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/e474de47fd61/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/8af608f28c2f/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/0782dca47026/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/4a9b117939ad/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/44525e2f98a1/gr5_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/a7f1a618d260/ga1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/e474de47fd61/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/8af608f28c2f/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/0782dca47026/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/4a9b117939ad/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d2ec/8944184/44525e2f98a1/gr5_lrg.jpg

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