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Big Data and Health Analytics

Sprachen: Englisch. 24,0 cm / 16,1 cm / 2,5 cm ( B/H/T )
Buch (Hardcover), 384 Seiten
EAN 9781482229233
Veröffentlicht Dezember 2014
Verlag/Hersteller Auerbach Publications

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Beschreibung

This book provides frameworks, use cases, and examples that illustrate the role of big data and analytics in modern health care, including how public health information can inform health delivery. Written for health care professionals and executives, this book presents the current thinking of academic and industry researchers and leaders from around the world. Using non-technical language, it includes case studies that illustrate the business processes that underlie the use of big data and health analytics to improve health care delivery.

Portrait

Harold Lehmann, M.D., Ph.D., Associate Professor and Interim Director, Division of Health Sciences Informatics School of Medicine, The Johns Hopkins University Katherine Marconi, Ph.D., MS, Professor and Director, Health Informatics Administration, The Graduate School, University of Medicine University College

Inhaltsverzeichnis

Little Big Data: Mastering Existing Information as a Foundation for Big Data. Managing Unstructured Data in a Health Care Setting. Experiences with Linking Data Systems for Analyzing Large Data. The Ecosystem of Federal Big Data and Its Use in Health Care. Big Data from the Push of Clinical Information: Harvesting User Feedback for Continuing Education. Addressing Social Determinants of Health Using Big Data. An International Perspective: Institutionalizing Quality Improvement through Data Utilization at a Multicountry, Multiclinic Level. Big Data: Architecture and Its Enablement. Health Data Governance: Balancing Best Practices for Data Governance and Management with User Needs. Roadblocks, Regulation, and Red Tape: How American Health Policy and Industry Norms Threaten the Big Data Revolution.Education and Training of Health Informaticists. Interactive Visualization. Driving Successful Population Health Management and Achieving Triple Aim with Clinical Analytics. Improving Decision-Making Using Health Data Analytics. Measuring e-Health Impact: An e-Health Evaluation Framework that Leverages Process Control Theory and Big Data Analytics.

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