The Ethics Of Using Big Data In Healthcare

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But some within health care still wary of using big data. Adding big data to more traditional medical research is a dramatic shift for scientists. Scientists are used of using data from tightly controlled clinical trials, where they start with a hypothesis and set out to prove it with data from their research. With big data, no hypothesis is needed. The data speaks for itself. The shift for researchers doesn’t stop with eliminating the hypothesis. When it comes to medical research, big data is often considered "dirty data,” because it’s collected outside of the standards of a traditional laboratory study. Researchers in health care can use big data, it just needs to be viewed differently than data from experiments and used in the suitable context. …show more content…

Medical records are governed by rules to protect privacy in ways that traditional consumer marketing data is not. At minimum, a big data analytics platform in healthcare must support the key functions necessary for processing the data. The criteria for platform evaluation may include ease of use, permanence, ease of use, scalability, ability to control at different levels of granularity, privacy and security enablement, and quality assurance. To succeed, big data analytics in healthcare needs to be packaged so it is menu-driven, user-friendly and clear. Real-time big data analytics is a key requirement in healthcare. The lag between data collection and processing has to be addressed. The dynamic availability of numerous analytics algorithms, models and methods in a pull-down type of menu is also necessary for large-scale adoption. The important managerial issues of ownership, governance and standards have to be considered. Health care data is rarely uniform, often uneven, or generated in legacy IT systems with incompatible formats. This great challenge needs to be addressed as …show more content…

Champions of big data promote it as a revolutionary advance. But even the examples that people give of the successes so it can be concluded that big data is at its best when analyzing things that are extremely common, but often falls short when analyzing things that are less common. For instance, programs that use big data to deal with text, such as search engines and translation programs often rely heavily on something called trigrams: sequences of three words in a row (like “in a row”). Reliable statistical information can be compiled about common trigrams, precisely because they appear frequently. But no existing body of data will ever be large enough to include all the trigrams that people might use, because of the continuing inventiveness of

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