This open access book aims to present an overview of the governance and management of medial data sharing and application based on China s evidence and experience. The basic knowledge and guidelines of medical data sharing in China and international consensus are introduced, including the identifications of medical data and its sharing, the mechanism of data sharing, medical ethics and data ethics, institutional management, privacy policy, etc. The challenges to law and governance from medical big data and AI in medicine are discussed, which are the key trends in both public and individual health. This book builds an academic system for governance and management of medical data sharing and application, as well as a practical guidance. It would be insightful for researchers and practitioners in medical institutions.

Autorentext

Guan Jian, M.D., is Professor, Peking Union Medical College Hospital, Peking Union Medical College(PUMC) & Chinese Academy of Medical Sciences (CAMS). She is the appointed next chair of Chinese Society of Medical Research Management, the Chinese Medical Association (CMA), and is a member of the CODATA-DETG of the International Science Council (ISC). She serves as the deputy editor-in-chief of Chinese Journal Medical Science Research Management, deputy editor-in-chief of Chinese Medical Ethics. She is an interdisciplinary expert major in big data governance and data ethics in the health field, with twenty years of experience as the executive deputy director of the Clinical Scientific Data Center at the National Population and Health Scientific Data Sharing Service Platform. She has published over 90 articles and contributed to the compilation of nine books.

Inhalt

Overview of the Medical Scientific Data and its Sharing.- Sharing Mechanism and Guarantee System of Practice .- International Policy and Consensus.- Medical Research Ethics.- Data Ethics.- Institutional Data Management.- Privacy Protection.- Informed Consent.- Framework of Data Standard.- Construction of interactive data standards and Value Evaluation.- Introduction of Big Data in Health Field.- Big Data in Healthcare.- Public Health Big Data.- Omics Data.- Artificial Intelligence in health field.