iPatient in medical information systems and future of internet of health

Autor:	Olga Kolesnichenko, Gennady Smorodin, Andrey Mazelis, Alexander Nikolaev, Lev Mazelis, Alexander Martynov, Valeriy Pulit, Sergey Balandin, Yuriy Kolesnichenko
Jazyk:	angličtina
Rok vydání:	2017
Předmět:	Big Data analytics Medical information system cluster analysis Python Models approach Internet of Health Hypertensive heart disease iPatient ECG examination ultrasonography examination digestive diseases Health Care Standard telemedicine socio-medical portrait Telecommunication TK5101-6720
Zdroj:	Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 776, Iss 20, Pp 169-180 (2017)
Druh dokumentu:	article
ISSN:	2305-7254 2343-0737
DOI:	10.23919/FRUCT.2017.8071308
Popis:	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.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/fe9ae559397c4723a122e2ac10b89d09 Zobrazit plný text záznamu View record in DOAJ