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Since the CIGO is a relatively new position, the role's responsibilities are not set in stone and continue to evolve. For the most part, today's CIGOs: Manage all of an organization's information, tapping into as much value from it as possible (e.g., better-targeted marketing) while reducing exposure to its associated risks (e.g., lawsuits)
Some of the problems tackled by CRI are: creation of data warehouses of health care data that can be used for research, support of data collection in clinical trials by the use of electronic data capture systems, streamlining ethical approvals and renewals (in US the responsible entity is the local institutional review board), maintenance of ...
The need for data privacy, using applications, personal devices, and the internet all came to the forefront. The pandemic has had large amounts of data being generated especially in the healthcare sector. Big data is accrued for the healthcare sector now more than ever due to the growing coronavirus pandemic.
The data management plan describes the activities to be conducted in the course of processing data. Key topics to cover include the SOPs to be followed, the clinical data management system (CDMS) to be used, description of data sources, data handling processes, data transfer formats and process, and quality control procedure
Healthcare information in EMRs are important sources for clinical, research, and policy questions. Health information privacy (HIP) and security has been a big concern for patients and providers. Studies in Europe evaluating electronic health information poses a threat to electronic medical records and exchange of personal information. [ 6 ]
Big data in health research is particularly promising in terms of exploratory biomedical research, as data-driven analysis can move forward more quickly than hypothesis-driven research. [88] Then, trends seen in data analysis can be tested in traditional, hypothesis-driven follow up biological research and eventually clinical research.
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The scale and capabilities of artificial intelligence (AI) systems are growing rapidly, notably due to advances in big data. In healthcare, it is expected to provide easier accessibility of information, and to improve treatments while reducing cost. The integration of AI in healthcare tends to improve the quality and efficiency of complex tasks.