Big Data Risks and Rewards in Healthcare

Big Data Risks and Rewards in Healthcare

Big data in healthcare is the act of analyzing large data quantities collected from the healthcare data source. The data might be clinical data, pharmaceutical and Research and Development (R &D) data, and patient behavior and sentimental data. The use of big data in healthcare aids in transforming the industry towards a value-based model that delivers superior patient experiences, outcomes, and treatments (Manogaran & Sundarsekar, 2017).

One of the major benefits of big data in healthcare is data management, data analysis, and electronic medical record keeping. Big data helps in finding and identifying the right population or target group. However, it consists of a diverse group of population plus certain groups that can be identified for risk assessment and screenings. The presence of big data allows the development or modification of a program or intervention to target the health problem. It enables clinical trials to be initiated immediately (Groves & Kuiken, 2016). Big data gives a clearer picture of a population plus their medical problems. The distribution pattern or disease information allows quick development of intervention programs plus targeting the touched groups as early as possible.

The major challenge of big data is security. Since big data contains personal health history and information, it is essential for the databases to be kept secret and protected from hacking, phishing, and cyber theft, in which stolen information can be sold for a huge sum. Besides health information and personal data from health facilities that can get stolen and hacked, other big data from telecommunications, banks, and companies are also vulnerable without the know-how of the clients. However, before implementing big data, it is essential to ensure that the administration, security, and privacy of the big data are well catered for. Protection of health information might be done through using anti-virus software, multilayer authentication, data encryption, use of firewalls, among others. However, the accessibility of healthcare data must be consistently reviewed and monitored (Fang & Iyengar, 2016).

In my experience with big data security in healthcare, there is a method of authentication fitted to confirm authentication about the subject, whether they are true or authentic. The bull eye algorithm has been used in monitoring sensitive data in 360 degrees. The algorithm has been used to ensure data security plus manage relations between original data and replicated data. It allows only authorized persons to read or write critical data (Groves & Kuiken, 2016). However, in the healthcare system, both healthcare data offered by providers and the identities of consumers must be verified at the entry of every access.

References

Groves, P., Kayyali, B., Knott, D., & Kuiken, S. V. (2016). The big data revolution in healthcare: Accelerating value and innovation.

Fang, R., Pouyanfar, S., Yang, Y., Chen, S. C., & Iyengar, S. S. (2016). Computational health informatics in the big data age: a survey. ACM Computing Surveys (CSUR), 49(1), 12.

Manogaran, G., Thota, C., Lopez, D., Vijayakumar, V., Abbas, K. M., & Sundarsekar, R. (2017). Big data knowledge system in healthcare. In the Internet of things and big data technologies for next generation healthcare (pp. 133-157). Springer, Cham.

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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.

Big Data Risks and Rewards in Healthcare

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, and 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.

To Prepare:

Review the Resources and reflect on the web article  Big Data Means Big Potential, Challenges for Nurse Execs.

Reflect on your own experience with complex health information access and management and consider potential challenges and risks you may have experienced or observed.

Post a description of at least one potential benefit of using big data as part of a clinical system and explain why. Then, describe at least one potential challenge or risk of using big data as part of a clinical system and explain why. Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using the big data you described. Be specific and provide examples.