ABSTRACT
Objective To analyze ethical challenges raised from big data in healthcare,provide suggestions for improving its application and development.Methods The ethical challenges were discussed according to the study of important literatures,typical case analysis,analyzing the current situation and its development trend of big data in healthcare.Results The advancement of technology and policies favorable have provided new opportunities for development of big data in healthcare.However,there are still some ethical challenges for its application.For instance,the difficulty of perform traditional informed consent process,the high risk of EHR information release during data storage and transmission,and inadequate privacy protection.To solve these problems,the corresponding regulation and some guidelines should be refined and/or updated;the management system that include informed consent should be adjusted;the corresponding technical supporting platform and specialized interdisciplinary team are also needed.Conclusions The establishment and application is a systematic project.The solution of the ethical challenges is also based on a comprehensive safeguard system of laws,regulations,management and technology.
ABSTRACT
Medical practice generates and stores immense amounts of clinical process data, while integrating and utilization of these data requires interdisciplinary cooperation together with novel models and methods to further promote applications of medical big data and research of artificial intelligence. A "Datathon" model is a novel event of data analysis and is typically organized as intense, short-duration, competitions in which participants with various knowledge and skills cooperate to address clinical questions based on "real world" data. This article introduces the origin of Datathon, organization of the events and relevant practice. The Datathon approach provides innovative solutions to promote cross-disciplinary collaboration and new methods for conducting research of big data in healthcare. It also offers insight into teaming up multi-expertise experts to investigate relevant clinical questions and further accelerate the application of medical big data.
ABSTRACT
A detailed, high-scale clinical data can be generated in the process of diagnosis and treatment of emergency critically ill patients. The integration and analysis and utilization of these data are of great value for improving the treatment level and efficiency and developing the data-driven clinical assistant decision support. China has large volume of health information resources, however, the construction of healthcare databases and subsequent secondary analysis has just started. With the effort of the Chinese PLA General Hospital in building an emergency database and promoting data sharing, the first emergency database was published in China and a health Datathon was organized utilizing this database, providing experience for clinical data integration, database construction, cross-disciplinary collaboration and data sharing. Referring to the development at home and abroad, this review discussed work in this area and further proposed establishing a big data cooperation for emergency medicine and building a learning healthcare system to integrate more clinical resources and form a closed loop of "clinical database construction-analysis-applications", and enhance the effectiveness of medical big data in reducing medical costs and improving healthcare delivery.