iPatient in medical information systems and future of internet of health

Abstract

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.

Keywords

• 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