When you wake in the morning, you may reach for your cell phone to reply to a few text or email messages that you missed overnight. On your drive to work, you may stop to refuel your car. Upon your arrival, you might swipe a key card at the door to gain entrance to the facility. And before finally reaching your workstation, you may stop by the cafeteria to purchase a coffee.
From the moment you wake, you are in fact a data-generation machine. Each use of your phone, every transaction you make using a debit or credit card, even your entrance to your place of work, creates data. It begs the question: How much data do you generate each day? Many studies have been conducted on this, and the numbers are staggering: Estimates suggest that nearly 1 million bytes of data are generated every second for every person on earth.
As the volume of data increases, information professionals have looked for ways to use big data—large, complex sets of data that require specialized approaches to use effectively. Big data has the potential for significant rewards—and significant risks—to healthcare. In this Discussion, you will consider these risks and rewards.
BY DAY 6 OF WEEK 5
Respond to at least two of your colleagues* on two different days, by offering one or more additional mitigation strategies or further insight into your colleagues’ assessment of big data opportunities and risks.
Response 1
Big data refers to data collections frequently evaluated using modern computing techniques to reveal information about human activities, trends, and patterns. Big data helps the healthcare industry adapt faster data processing speeds, enabling individuals to obtain pertinent insights that aid in the treatment they provide for patients. One of the primary benefits of using big data in a clinical system is that care providers can constantly and efficiently monitor patients' vital signs. Healthcare providers frequently attempt to improve the health of patients suffering from chronic diseases by monitoring their vitals, such as temperature and blood pressure. The development of big data technology, such as electronic health records, has facilitated the collectio
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