iPatient in Medical Information Systems and Future of Internet of Health

被引：0

作者：

Kolesnichenko, Olga ^{[1
]}

Smorodin, Gennady ^{[2
]}

Mazelis, Andrey ^{[3
]}

Nikolaev, Alexander ^{[3
]}

Mazelis, Lev ^{[3
]}

Martynov, Alexander ^{[4
]}

Pulit, Valeriy ^{[4
]}

Balandin, Sergey ^{[5
]}

Kolesnichenko, Yuriy ^{[6
]}

机构：

[1] Secur Anal Bulletin, Moscow, Russia

[2] Dell EMC External Res & Acad Alliances, St Petersburg, Russia

[3] Vladivostok State Univ Econ & Serv, Vladivostok, Russia

[4] SP ARM, St Petersburg, Russia

[5] Mech & Opt ITMO Univ, Univ Informat Technol, Open Innovat Assoc FRUCT, St Petersburg, Russia

[6] Cybersecur Technol, Moscow, Russia

来源：

PROCEEDINGS OF THE 20TH CONFERENCE OF OPEN INNOVATIONS ASSOCIATION (FRUCT 2017) | 2017年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The results of Study "iHealthCare Optimization", provided by Dell EMC External Research and Academic Alliances, are presented. Big Data analytics of Medical information system qMS records was implemented using cluster analysis in Python. Software for cluster analysis was created by Andrey Mazelis (Vladivostok State University of Economics and Service). There are two directions of cluster analysis: Series treatment (number of investigation procedures for each patient) and Series time (waiting time for investigation procedures for each patient). Two models of patients management (Model A and Model B) were found, that can be used for better planning of care management. Models approach provides the new capability to implement Health Care Standard in mode aaS, using feedback after Big Data analytics. Around 80-90% of patients with Essential hypertension can get treatment in Day Hospital without hospitalization.

引用

页码：169 / 180

页数：12

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