NURS 6051S Week 5 Discussion: Big Data Risks and Rewards

NURS 6051S Week 5 Discussion: Big Data Risks and Rewards

NURS 6051S Week 5 Discussion: Big Data Risks and Rewards

Big Data refers to the data and information which can’t be handled or processed through the current traditional software systems. Big Data is large sets of structured and unstructured data which needs be processed by advanced analytics and visualization techniques to uncover hidden patterns and find unknown correlations to improve the decision-making process. Many organizations have huge volume of data, but they can’t utilize it because it still in raw, semi-structured or unstructured format which is difficult to realize. (Nasser and Tariq, 2015) NURS 6051S Week 5 Discussion: Big Data Risks and Rewards.

Some of the challenges of big data security and privacy. Securing data requires a holistic approach to protect organizations from complex threat landscape across diverse system. Security tools need to monitor and alert on suspicious malware infection on the system, database or a web CMS such as WordPress, and big data security experts must be proficient in cleanup and know how to remove malware from WordPress (, 2020) NURS 6051S Week 5 Discussion: Big Data Risks and Rewards.


Big Data Security – Issues, Challenges, Tech & Concerns. (2020). Www.Rd-Alliance.Org. Retrieved December 29, 2020

Nasser, T., & Tariq, R. S. (2015). Big data challenges. J Comput Eng Inf Technol 4: 3 Retrieved December 29.2020. doi: http://dx. doi. org/10.4172/2324, 9307(2).

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 NURS 6051S Week 5 Discussion: Big Data Risks and Rewards. 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. NURS 6051S Week 5 Discussion: Big Data Risks and Rewards

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.
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.

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.

Sample 2

Big Data Risks and Rewards

       Data usage is part of our daily activity. It is expected that the health care system would turn into a data rich industry. Big data refers to data being gathered and analyzed to build trends in care and improve patient outcomes (What is big health care data, 2020).



The advantages of using big data in health care are endless. In the healthcare organization, most employees have access to the data entry system, but the nursing staff is responsible for entering the patient’s essential information from admission to discharge. A few advantages of using big data include the nursing staff’s data improves communication with other disciplines and provides better patient outcomes. Other advantages include development of policies, improve employee education, monitor of care trends. The data system can help reduce the patient’s readmission rate by trending risk factors, cost clinical, setting operational data together to monitor productivity and outcome (W. Raghupathi, 2014).



Some of the challenges are when the system does not recognize some of the medical terminologies when nurses or other health care professionals are charting ((Macieira et al., 2017). Other challenges are the risk of having a patient’s information stolen or hacked which can be terrifying to both patients and healthcare organizations. When big data is compromised, it put patient’s data at risk and all employees who have access to the system in the hospital or remotely because hackers are not only people from the outside of the hospital. It can be from the hospital employees accessing the wrong charts, their friends ‘charts, or their own personal medical records.  These are the most common type of high-level privacy violations (Brooks & Jiang, 2018).  To decrease these violations employees are educated about the seriousness of the violation and the penalties that come with them. At the facility where this nurse works, these violations can cause an employee to lose his/her job NURS 6051S Week 5 Discussion: Big Data Risks and Rewards.


Brooks, C., & Jiang, X. (2018, November 16). Health care providers – not hackers – leak more of your data. MSUToday.

Macieira, T., Smith, M. B., Davis, N., Yao, Y., Wilkie, D. J., Lopez, K. D., & Keenan, G. (2017). Evidence of progress in making nursing practice visible using standardized nursing data: A systematic review. PubMed Central (PMC).

Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: Promise and potential. PubMed Central (PMC).

What is patient engagement? | Evariant: The leading healthcare CRM solution. (n.d.). Healthgrades | Evariant.   NURS 6051S Week 5 Discussion: Big Data Risks and Rewards

sample 3

Big data typically refers to a large complex data set that yields substantially more information when analyzed as a fully integrated data set as compared to the outputs achieved with smaller sets of the same data that are not integrated. (Keenan, 2014). The CDC is able to track epidemics around the round with use of big data. Currently with the CDC data tracker is able to track Covid-19 globally. Data is gathered and viewed from different regions of the world on case trends for vaccinations, global cases and death, populations affected. The data is used to compare with trends in population and forecast. CDC, 2020) NURS 6051S Week 5 Discussion: Big Data Risks and Rewards

The movement toward use of larger integrated data sets in health care follows other industries that have realized multiple cost savings and improvements in business processes, customer services, and forecasting from their big data.  Specifically, health care stakeholders expect the availability of high quality “big data” gathered in Electronic Health Records (EHRs) to bring value through enabling (keen.2014) NURS 6051S Week 5 Discussion: Big Data Risks and Rewards

The Big data is a primary target for hackers. Data security professionals need to take an active role as soon as possible. Organization come under threat because of hacking and vulnerabilities within their systems in the organization.  Potential risks and challenges associated with EHR include security concerns. Research indicates that security concerns stem from increased mobile devices such as smartphones and medical identity theft.  Additionally, security concerns arise from data exchange among organizations, clinicians, federal agencies, and patients (Harman et al., 2012). NURS 6051S Week 5 Discussion: Big Data Risks and Rewards Organizations have placed safeguards to protect patients’ information that including only authorized individuals access patient information, passwords are changed at set intervals, and educating staff about potential threats for data to be hacked, manipulated, or destroyed by internal or external users.


CDC COVID Data Tracker. (n.d.). Retrieved December 31, 2020, from

Electronic Health Records: Privacy, Confidentiality, and Security. (2012). AMA Journal of Ethics.

Keenan G. M. (2014). Big Data in Health Care: An Urgent Mandate to CHANGE Nursing EHRs!. On-line journal of nursing informatics, 18(1), NURS 6051S Week 5 Discussion: Big Data Risks and Rewards.



NURS 6051S Week 5 Discussion: Big Data Risks and Rewards Sample 4

Big data is defined by The McKinsey Global Institute as “datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze” (Sensmeier, 2016). “It is a collection of a vast amount of trustworthy data accumulating in high velocity, and coming from a variety of sources, not only medical records” (Jastania et al, 2019).NURS 6051S Week 5 Discussion: Big Data Risks and Rewards.


These enormous datasets offer a great opportunity to improve patient outcomes, lower healthcare costs, offer more transparency, and achieve a higher patient satisfaction level. Big Data also presents many challenges, including but not limited to posing a threat to security and privacy threats.


Collecting data and measuring clinical outcomes it not new to nursing; however, utilizing electronic health records (EHRs) is done with ease and in real-time NURS 6051S Week 5 Discussion: Big Data Risks and Rewards. By adding innovative big data technologies, clinical decision support for nurses has become more precise, more predictive, and more meaningful for many outcomes, including clinical deterioration; falls with injury; pressure ulcers; delirium; and healthcare-associated infections from urinary catheters, central lines, or surgical sites (Linnen, 2016). Patient care is improved as clinicians are able to identify the most effective course of treatment for an individual based on the data and trends that are available in the EHR. Additionally, monitoring a patient’s vital signs such as blood pressure, heart rate, temperature, oxygen saturation, and glucose are done with the touch of a button and one can identify trends and risks more quickly, minimizing adverse events NURS 6051S Week 5 Discussion: Big Data Risks and Rewards.


Data security is the number one priority for healthcare organizations, especially in the wake of a rapid-fire series of high profile breaches, hackings, and ransomware episodes (Bresnick, 2019). There is a list of technical safeguards imposed by the HIPPA Security Rule that healthcare organizations must follow, however, an organization can still be taken down very easily due to human error. Staff must be reminded and educated about hospital policy, updating software and opening emails from an unknown source, and the threats they present. Recently in Massachusetts, some staff members at several hospitals received erroneous emails claiming to be the U.S. Department of Health and Human Services seeking statistical information about COVID 19 NURS 6051S Week 5 Discussion: Big Data Risks and Rewards. These types of phishing attempts increase concern for privacy breeches and in some cases have taken over the hospital data systems requiring the hospital to enter into financial negotiations in order to regain control of their data system. Through increased protection with filtering external emails, updating software regularly, using multi-factor authentication, and educating staff to avoid malicious email links organizations are able to prevent these types of attacks.

Bresnick, J. (2019, June 19). Top 10 Challenges of Big Data Analytics in Healthcare.

Linnen, D. (2016). The Promise of Big Data Improving Patient Safety and Nursing Practice .

Sensmeier, J. (2016). Understanding the impact of big data on nursing knowledge.

Jastania, R., Nageeti, T., Al-Juhani, H., Basahel, A., Aljuraid, R., Alanazi, A., Aldosari, H., & Aldosari, B. (2019). Utilizing Big Data in Healthcare, How to Maximize Its Value. Studies in Health Technology & Informatics, 262, 356-359.  NURS 6051S Week 5 Discussion: Big Data Risks and Rewards

Our Essay Writing Service Features

Qualified Writers
Looming deadline? Get your paper done in 6 hours or less. Message via chat and we'll get onto it.
We care about the privacy of our clients and will never share your personal information with any third parties or persons.
Free Turnitin Report
A plagiarism report from Turnitin can be attached to your order to ensure your paper's originality.
Safe Payments
The further the deadline or the more pages you order, the lower the price! Affordability is in our DNA.
No Hidden Charges
We offer the lowest prices per page in the industry, with an average of $7 per page
24/7/365 Support
You can contact us any time of day and night with any questions; we'll always be happy to help you out.
$15.99 Plagiarism report
$15.99 Plagiarism report
$15.99 Plagiarism report
$15.99 Plagiarism report
$3.99 Outline
$21.99 Unlimited Revisions
Get all these features for $65.77 FREE
Do My Paper

Frequently Asked Questions About Our Essay Writing Service

Academic Paper Writing Service

Our essay writers will gladly help you with:

Business Plan
Presentation or Speech
Admission Essay
Case Study
Reflective Writing
Annotated Bibliography
Creative Writing
Term Paper
Article Review
Critical Thinking / Review
Research Paper
Thesis / Dissertation
Book / Movie Review
Book Reviews
Literature Review
Research Proposal
Editing and proofreading
Find Your Writer

Latest Feedback From Our Customers

Customer ID:  # 678224
Research Paper
Highly knowledgeable expert, reasonable price. Great at explaining hard concerts!
Writer: Raymond B.
Customer ID: # 619634
Essay (any type)
Helped me with bear and bull markets right before my exam! Fast teacher. Would work with Grace again.
Writer: Lilian G.
Customer ID: # 519731
Research Paper
If you are scanning reviews trying to find a great tutoring service, then scan no more. This service elite!
Writer: Grace P.
Customer ID: #499222
Essay (any type)
This writer is great, finished very fast and the essay was perfect. Writer goes out of her way to meet your assignment needs!
Writer: Amanda B.
Place an Order

Calculate the price of your order

You will get a personal manager and a discount.
We'll send you the first draft for approval by at
Total price:

Powered by

× WhatsApp Us