Big data risks and rewards
Big data risks and rewards
Discussion: Big Data Risks and Rewards
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 datalarge, complex sets of data that require specialized approaches to use effectively. Big data has the potential for significant rewardsand significant risksto 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.
By Day 3 of Week 5
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 big data you described. Be specific and provide examples.
Excellent
Main Posting 45 (45%) 50 (50%)
Answers all parts of the discussion question(s) expectations with reflective critical analysis and synthesis of knowledge gained from the course readings for the module and current credible sources.
Supported by at least three current, credible sources.
Written clearly and concisely with no grammatical or spelling errors and fully adheres to current APA manual writing rules and style.
Main Post: Timeliness 10 (10%) 10 (10%)
Posts main post by day 3.
First Response 17 (17%) 18 (18%)
Response exhibits synthesis, critical thinking, and application to practice settings.
Responds fully to questions posed by faculty.
Provides clear, concise opinions and ideas that are supported by at least two scholarly sources.
Demonstrates synthesis and understanding of learning objectives.
Communication is professional and respectful to colleagues.
Responses to faculty questions are fully answered, if posed.
Response is effectively written in standard, edited English.
Second Response 16 (16%) 17 (17%)
Response exhibits synthesis, critical thinking, and application to practice settings.
Responds fully to questions posed by faculty.
Provides clear, concise opinions and ideas that are supported by at least two scholarly sources.
Demonstrates synthesis and understanding of learning objectives.
Communication is professional and respectful to colleagues.
Responses to faculty questions are fully answered, if posed.
Response is effectively written in standard, edited English.
Participation 5 (5%) 5 (5%)
Meets requirements for participation by posting on three different days.
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Solution
Big Data Risks and Rewards
Big data is the organization of large complex data set that acts as the central processing zone when more detailed information is needed, providing an opportunity for reliability and credibility for the information when making important decisions. As such, big data analytics is one of the most popular undertakings that has taken over the healthcare industry.
Considering the huge amount of data that the healthcare facilities handle, its complexity can only be resolved with the big data analytics to manage the data and get important information that can inform various organizational decisions (Glassman, 2017).
With the demand for specialized treatments, disease control, cost benefit analysis, visibility into performance and an increasing demand for healthcare professional management, the healthcare institutions have adopted the big data analytics in order to effectively manage all these elements.
Nevertheless, the big data has arrived with a mix of benefits and a fair share of challenges. Its application within the healthcare industry has not been easy, with the professionals and the institutions being required to undergo an extra mile to ensure that the data integration within the clinical systems yields the best results in terms of reliable information that informs decisions.
To begin with, one major potential benefit of using big data as part of a clinical system has been reduction of the medical errors. With various data required to perform diagnostic analysis, right from the personal details to medical history, as well as various examination results, the patient data is huge and complex (Wang et al., 2018).
Big data has however brought in a connection of all these data, where important diagnostic decisions can be made in record time after retrieving the important clinical data from the facility system which has enabled accuracy in diagnostic and medical procedures, thus minimizing the medical error cases that can be witnessed with a non-integrated data.
However, one notable challenge for using big data as part of a clinical system is the assurance for data safety and security. Patient and other stakeholders data is sensitive and keeping it safe when consolidated together online requires employment of high technical measures and data protocols for its protection (Abouelmehdi et al., 2018).
Cases of data loss and data theft can be catastrophic and therefore, data safety is a serious challenge to the clinical systems when it comes to the management and use of big data. In my observation, many healthcare institutions have however made a big milestone in mitigating the data risks through hiring of nursing informatics and other information experts that will ensure the establishment of data protocols for data capture, storage, sharing and retrieval.
This ensures that only the authorized personnel may access the stored data. On the other hand, these experts also ensure that the data is protected through strong firewalls which prevents illegal online access for the clinical systems.
References
Abouelmehdi, K., Beni-Hessane, A., & Khaloufi, H. (2018). Big healthcare data: Preserving
security and privacy. Journal of Big Data, 5(1), 1-18. doi:http://dx.doi.org/10.1186/s40537-017-0110-7
Glassman, S. K. (2017). Using Data in Nursing Practice. Practice Matters. America Nurse
Today.
Wang, Y.; Kung, L.; Byrd, T.A. (2018). Big data analytics: Understanding its capabilities and
potential benefits for healthcare organizations. Technol. Forecast. Soc. Chang. 126, 3-13.
