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Health care analytics is the health care analysis activities that can be undertaken as a result of data collected from four areas within healthcare: (1) claims and cost data, (2) pharmaceutical and research and development (R&D) data, (3) clinical data (such as collected from electronic medical records (EHRs)), and (4) patient behaviors and preferences data (e.g. patient satisfaction or retail ...
Health data are classified as either structured or unstructured. Structured health data is standardized and easily transferable between health information systems. [4] For example, a patient's name, date of birth, or a blood-test result can be recorded in a structured data format.
The European Union has implemented the General Data Protection Regulation (GDPR) to protect citizens' personal data, which applies to the use of AI in healthcare. In addition, the European Commission has established guidelines to ensure the ethical development of AI, including the use of algorithms to ensure fairness and transparency. [ 143 ]
The Data Project used rankings from Open Data Watch to explore how the U.S. compares to other countries in data transparency and openness.
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Hospital price transparency. All hospitals would be required to make public the cash and insurance-adjusted costs of at least 300 health care services.
Research transparency is a major aspect of scientific research. It covers a variety of scientific principles and practices: reproducibility, data and code sharing, citation standards or verifiability. The definitions and norms of research transparency significantly differ depending on the disciplines and fields of research.
Health care organizations are increasingly using cloud computing as a way to handle large amounts of data. This type of data storage, however, is susceptible to natural disasters, cybercrime and technological terrorism, and hardware failure. Health information breaches accounted for the 39 percent of all breaches in 2015.
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