Legal and Ethical Concerns of Big Data: Predictive Analytics

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Healthcare has been transformed by the introduction of the electronic medical record. The era of big data has provided an endless source of valuable data for exploration. Knowledge is doubling every 12 months in the current electronic world, and in the future, that will be as dynamic as every 12 hours. The human brain cannot synthesize all available data that will be required to predict a patient's medical future and potentially change the treatment cascade for the patient based on the integration of that data. The future of big data will require a paradigm shift because of its complexity and scale. The enormous amount of streaming data will demand new techniques, algorithms, and analytics so that knowledge gained will be meaningful to the clinician.1 Predictive analytics is the use of electronic algorithms that predict the probability of future events.2 Predictive analytics allows for the use of big data to improve the health of patients and potentially lowering the cost of healthcare. Developing and implementing predictive analytics, however, requires a team of experts who are also aware of the challenges relating to policy and ethical and legal aspects.2
Before the electronic medical record, an evaluation of a patient's risk of a preventable serious adverse event would have taken minutes to hours and would have had limited accuracy and discrimination. With the current technology available including early warning systems, a patient's risk score can be calculated continuously and with lead times of as little as 12 hours.3 The opportunity to predict adverse serious events using big data to develop algorithms based on real-time data and past medical history raises ethical and legal challenges for organizations developing their own predictive analytics systems based on their patient populations and for medical device companies developing commercial algorithims.
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