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VM01-482 Handbook of Research on Optimizing Healthcare Management Techniques(文景書局)

  優化醫療保健管理技術研究手冊
ISBN: 9781799813712 Year: 2020  Price: US$ 405.00
Author: Nilmini Wickramasinghe
A b s t r a c t


Healthcare is noted for using leading-edge technologies and embracing new scientific discoveries to enable better cures for diseases and better means to enable early detection of most life-threatening diseases. However, the healthcare industry globally, and in the US specifically, has been extremely slow to adopt technologies that focus on better practice management and administrative needs. Presently, healthcare is grappling with many challenges both nationally and globally, including escalating costs, a move to a preventative care environment, and a technologically savvy patient with high expectations.

The Handbook of Research on Optimizing Healthcare Management Techniques is a pivotal reference source that provides an extensive and rich compilation of various ICT initiatives and examines the role that ICT plays and will play in the future of healthcare delivery. It represents ways in which healthcare delivery can be made superior and the healthcare industry can begin to address the major challenges it faces in the 21st century so that ultimately the most important person in the web of healthcare players, the patient, can be confident about receiving high-quality, cost-effective healthcare. While highlighting topics such as e-health, medical informatics, and patient value, this publication explores the role of supportive technologies as well as the methods of focused, patient-centric outcomes. This book is ideally designed for doctors, nurses, hospital administrators, medical staff, hospital directors, medical boards, IT consultants, health practitioners, academicians, researchers, and students.

Topics Covered
The many academic areas covered in this publication include, but are not limited to:
•Crowdsourcing
•Data Analytics
•E-Health
•Healthcare Delivery
•Medical Informatics
•Medical Technologies
•Mental Health
•Patient Value
•Predictive Analysis
•Risk Detection


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