Big Data in home healthcare: A new frontier in personalized medicine. Medical emergency services and prediction of hypertension risks

ABSTRACT

This paper provides an in-depth analysis of the Big Data application in the field of medicine. This innovative technology is a significant topic because Big Data introduces new opportunities for medical practitioners and patients, including the improvement of patients’ quality of life and healthcare systems, the mitigation of specific illnesses, and the reduction of state-level healthcare costs. This paper discusses implications relative to wearable sensing devices as well as personalised medicine. The advantages of the analytical capabilities of Big Data are also discussed. For instance, Big Data analytics can aid in the improvement of healthcare cost-efficiency and profit generating capabilities. The limitations and vulnerabilities of Big Data application in the healthcare field, such as the development of the domain-specific system architecture, are exposed. This paper examines the elements of architecture (data acquisition & transmission, cloud processing, and analytics) adapted to healthcare needs. A brief outline of the restrictions for official approval of the new devices and methodologies is presented. Specifically, the sensor data are heterogeneous and untagged. Previously, the implementation of clinical records into models was required. Currently, adaptation of machine-learning techniques is required. Ethical issues relative to the personal privacy involved in healthcare data acquisition, storage, and processing are considered.

KEYWORDS:

• Big Data
• cloud biomedical information
• Electronic Health Records
• faster decision-making
• healthcare management
• health information systems
• emergency care
• personalized medicine

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Antonio Clim has started PhD studies in September 2017 at the Bucharest University of Economic Studies. His research interests include smart health services for smart cities with an accent on CDV diseases predictions.

Razvan Daniel Zota has graduated the Faculty of Mathematics – Computer Science Section at the University of Bucharest in 1992. In 2000 he has received the Ph.D. title from the Bucharest University of Economic Studies in the field of Cybernetics and Economic Informatics. His research interests include Business Informatics and Computer Networks.

Grigore Tinica is Professor of Cardiovascular Surgery in the University of Medicine and Pharmacy „Gr. T. Popa”, Iaşi, Romania, Head Department of Cardiovascular Surgery Manager, Cardiovascular Institute, Iaşi, Editor of the The Euro-Asian Journal of Surgery and Medicine, Corresponding Member of the Academy of Romanian Scientists and Romanian Academy of Medical Sciences, Honorary Member of the Academy of Sciences of Moldova, a world-renowned international authority, with over 30 years of experience in all aspects of cardiovascular pediatric and adult surgery.

ORCID

Antonio Clim http://orcid.org/0000-0003-4745-0431

Razvan Daniel Zota http://orcid.org/0000-0001-9324-7798

Grigore Tinica http://orcid.org/0000-0002-1755-9674