Discussion: Big Data Risks and Rewards NURS 6051
Discussion: Big Data Risks and Rewards NURS 6051 – Step-by-Step Guide
The first step before starting to write the Discussion: Big Data Risks and Rewards NURS 6051, it is essential to understand the requirements of the assignment. The first step is to read the assignment prompt carefully to identify the topic, the length and format requirements. You should go through the rubric provided so that you can understand what is needed to score the maximum points for each part of the assignment.
It is also important to identify the audience of the paper and its purpose so that it can help you determine the tone and style to use throughout. You can then create a timeline to help you complete each stage of the paper, such as conducting research, writing the paper, and revising it to avoid last-minute stress before the deadline. After identifying the formatting style to be applied to the paper, such as APA, you should review its use, such as writing citations and referencing the resources used. You should also review how to format the title page and the headings in the paper.
How to Research and Prepare for Discussion: Big Data Risks and Rewards NURS 6051
The next step in preparing for your paper is to conduct research and identify the best sources to use to support your arguments. Identify the list of keywords from your topic using different combinations. The first step is to visit the university library and search through its database using the important keywords related to your topic. You can also find books, peer-reviewed articles, and credible sources for your topic from PubMed, JSTOR, ScienceDirect, SpringerLink, and Google Scholar. Ensure that you select the references that have been published in the last words and go through each to check for credibility. Ensure that you obtain the references in the required format, for example, in APA, so that you can save time when creating the final reference list.
You can also group the references according to their themes that align with the outline of the paper. Go through each reference for its content and summarize the key concepts, arguments and findings for each source. You can write down your reflections on how each reference connects to the topic you are researching about. After the above steps, you can develop a strong thesis that is clear, concise and arguable. Next you should create a detailed outline of the paper so that it can help you to create headings and subheadings to be used in the paper. Ensure that you plan what point will go into each paragraph.
How to Write the Introduction for Discussion: Big Data Risks and Rewards NURS 6051
The introduction of the paper is the most crucial part as it helps to provide the context of your work, and will determine if the reader will be interested to read through to the end. You should start with a hook, which will help capture the reader’s attention. You should contextualize the topic by offering the reader a concise overview of the topic you are writing about so that they may understand its importance. You should state what you aim to achieve with the paper. The last part of the introduction should be your thesis statement, which provides the main argument of the paper.
How to Write the Body for Discussion: Big Data Risks and Rewards NURS 6051
The body of the paper helps you to present your arguments and evidence to support your claims. You can use headings and subheadings developed in the paper’s outline to guide you on how to organize the body. Start each paragraph with a topic sentence to help the reader know what point you will be discussing in that paragraph. Support your claims using the evidence conducted from the research, ensure that you cite each source properly using in-text citations. You should analyze the evidence presented and explain its significance and how it connects to the thesis statement. You should maintain a logical flow between each paragraph by using transition words and a flow of ideas.
How to Write the In-text Citations for Discussion: Big Data Risks and Rewards NURS 6051
In-text citations help the reader to give credit to the authors of the references they have used in their works. All ideas that have been borrowed from references, any statistics and direct quotes must be referenced properly. The name and date of publication of the paper should be included when writing an in-text citation. For example, in APA, after stating the information, you can put an in-text citation after the end of the sentence, such as (Smith, 2021). If you are quoting directly from a source, include the page number in the citation, for example (Smith, 2021, p. 15). Remember to also include a corresponding reference list at the end of your paper that provides full details of each source cited in your text. An example paragraph highlighting the use of in-text citations is as below:
The integration of technology in nursing practice has significantly transformed patient care and improved health outcomes. According to Smith (2021), the use of electronic health records (EHRs) has streamlined communication among healthcare providers, allowing for more coordinated and efficient care delivery. Furthermore, Johnson and Brown (2020) highlight that telehealth services have expanded access to care, particularly for patients in rural areas, thereby reducing barriers to treatment.
How to Write the Conclusion for Discussion: Big Data Risks and Rewards NURS 6051
When writing the conclusion of the paper, start by restarting your thesis, which helps remind the reader what your paper is about. Summarize the key points of the paper, by restating them. Discuss the implications of your findings and your arguments. End with a call to action that leaves a lasting impact on the reader or recommendations.
How to Format the Reference List for Discussion: Big Data Risks and Rewards NURS 6051
The reference helps provide the reader with the complete details of the sources you cited in the paper. The reference list should start with the title “References” on a new page. It should be aligned center and bolded, in sentence sentence care. The references should be organized in an ascending order alphabetically and each should have a hanging indent. If a source has no author, it should be alphabetized by the title of the work, ignoring any initial articles such as “A,” “An,” or “The.” If you have multiple works by the same author, list them in chronological order, starting with the earliest publication.
Each reference entry should include specific elements depending on the type of source. For books, include the author’s last name, first initial, publication year in parentheses, the title of the book in italics, the edition (if applicable), and the publisher’s name. For journal articles, include the author’s last name, first initial, publication year in parentheses, the title of the article (not italicized), the title of the journal in italics, the volume number in italics, the issue number in parentheses (if applicable), and the page range of the article. For online sources, include the DOI (Digital Object Identifier) or the URL at the end of the reference. An example reference list is as follows:
References
Johnson, L. M., & Brown, R. T. (2020). The role of telehealth in improving patient outcomes. Journal of Nursing Care Quality, 35(2), 123-130. https://doi.org/10.1097/NCQ.0000000000000456
Smith, J. A. (2021). The impact of technology on nursing practice. Health Press.
Discussion: Big Data Risks and Rewards NURS 6051 Instructions
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.
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To Prepare this Discussion: Big Data Risks and Rewards NURS 6051:
- 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.
- Discussion: Big Data Risks and Rewards NURS 6051
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. Have a look at NURS 6051 Discussion Healthcare Information Technology Trends.
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 Discussion: Big Data Risks and Rewards NURS 6051.
*Note: Throughout this program, your fellow students are referred to as colleagues.
Discussion: Big Data Risks and Rewards NURS 6051 Example 1
Big Data in nursing practice has no unified definition. However, the baseline meaning of Big Data corresponds to the enormous size of data regarding volume, velocity, variety, and veracity (Wong et al., 2016).
The advancement of technology and clinical research studies has increased the amount of data handled in every facet of nursing practice. The use of big data in the clinical system has potential benefits and risks. This paper will discuss the potential benefits and risks associated with the utilization of big data in nursing clinical systems and propose one strategy to prevent the risks.
Potential Benefit of Using Big Data
In the nursing practice, big data sources include the nursing clinical research findings, patient medical records, and results of clinical examination and laboratory investigations, including imaging. The application of big data concepts in the healthcare industry aims at improving the quality of healthcare outcomes by revolutionizing and modernizing healthcare practice (Agrawal & Prabakaran, 2020).
Including technology in handling big data in nursing and clinical research has potential benefits for future healthcare. Analysis and utilization of big data will positively impact healthcare quality by increasing its effectiveness while reducing costs.
Secondly, insight descriptive analysis of big data yields diagnostic data that result in predictive outcomes. The predictive outcomes yield prescriptive results that lead to smarter and cost-effective health outcomes (Dash et al., 2019).
This can happen in four different ways: early risk factor determination; early determination of markers or signals of adverse situations of disease or intervention; timely decision making based on analyzed past data; and ability to predict future outcomes of diseases (Pastorino et al., 2019). Through these four ways, big data ensures timely diagnosis and effectiveness of interventions, improved patient safety and pharmaco-vigilance, and disease prevention.
Scrutinizing big data differs from a secondary healthcare data analysis in the health setting. The intention of big data analysis and utilization of this data with undiscovered scope or size is to answer certain research questions and uncover certain disease conditions that are yet to be fully epidemiologically described. Therefore, big data has the potential of changing the course and practice of medicine and nursing by making them more preventive, diagnostic, and therapeutic (Ienca et al., 2018).
Potential Challenge or Risk of Using Big Data
Despite the described benefits of big data, it is still unclear whether it is the answer to the limited quality of care delivery and access faced in different global contexts. The concept of unmeasured confounding makes determinations of the statistical associations in causations Discussion: Big Data Risks and Rewards NURS 6051.
The increase in the size of data increases the chances of biases in data sets and making inferences from the analyzed big data. Various other confounders can cause a high variation in correlations from the big data analyses. As a new concept of data mining and utilization in the clinical system, big data analysis will require specialized advanced technology and skills that are yet to be widespread among clinical researchers and clinicians (Wong et al., 2016).
Further, digital maturity in healthcare lags compared to other fields (Suter-Crazzolara, 2018). There are ethical implications and violations that come with the utilization of big data, such as privacy, gender discrimination, and data protection (Alexandru et al., 2018). A study by Ienca et al. (2018) suggests a solution to the ethical challenges that entails scrutinizing biomedical research using big data regarding social benefits, data control, accountability, purpose, ability, and intention to share. While solvable, the methodological and ethical risks that come with the utilization of big data tend to require proper scrutinization.
Conclusion
The big data concept implies the enormous volume, veracity, and velocity of ever-increasing data available in biomedical research and data analysis Discussion: Big Data Risks and Rewards NURS 6051.
The benefit of the utilization of big data would reduce the cost of healthcare while increasing its effectiveness and timeliness of care. However, there still exist challenges of technical limitations and risks of ethical violations in big data use, which, alongside the apparent lag in big data usage in clinical settings, might jeopardize future integration into nursing practice.
Discussion: Big Data Risks and Rewards NURS 6051 References
Agrawal, R., & Prabakaran, S. (2020). Big data in digital healthcare: lessons learned and recommendations for general practice. Heredity, 124(4), 525-534. https://doi.org/10.1038/s41437-020-0303-2
Alexandru, A., Radu, I., & Bizon, M. (2018). Big Data in Healthcare – Opportunities and Challenges. Informatica Economica, 22(2/2018), 43-54. https://doi.org/10.12948/issn14531305/22.2.2018.05
Dash, S., Shakyawar, S., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis, and future prospects. Journal Of Big Data, 6(1). https://doi.org/10.1186/s40537-019-0217-0
Ienca, M., Ferretti, A., Hurst, S., Puhan, M., Lovis, C., & Vayena, E. (2018). Considerations for ethics review of big data health research: A scoping review. PLOS ONE, 13(10), e0204937. https://doi.org/10.1371/journal.pone.0204937
Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019). Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. European Journal Of Public Health, 29(Supplement_3), 23-27. https://doi.org/10.1093/eurpub/ckz168
Wong, H., Chiang, V., Choi, K., & Loke, A. (2016). The Need for a Definition of Big Data for Nursing Science: A Case Study of Disaster Preparedness. International Journal Of Environmental Research And Public Health, 13(10), 1015. https://doi.org/10.3390/ijerph13101015
NURS 6051 Module 4: Technologies Supporting Applied Practice and Optimal Patient Outcomes (Weeks 6-8)
Laureate Education (Producer). (2018). Informatics Tools and Technologies [Video file]. Baltimore, MD: Author.
Accessible player –Downloads– Download Video w/CC Download Audio Download Transcript
Learning Objectives
Students will:
- Evaluate healthcare technology trends for data and information in nursing practice and healthcare delivery
- Analyze challenges and risks inherent in healthcare technology
- Analyze healthcare technology benefits and risks for data safety, legislation, and patient care
- Evaluate healthcare technology impact on patient outcomes, efficiencies, and data management
- Analyze research on the application of clinical systems to improve outcomes and efficiencies
Discussion: Big Data Risks and Rewards NURS 6051 Example 2
Adopting new healthcare technology as information technology also advances comes with big data. According to Dash et al. (2019), big data means the enormous amount of information created by adopting technologies that collect patients’ records, which require new technology to capture, store, analyze, and assist decision-making, optimize processes, and manage hospital performance.
Big data may have different potential benefits and challenges. However, some strategies can be used to overcome the risks. This discussion presents the potential benefits and challenges of using big data as part of a clinical system and the reasons behind these potential benefits or challenges. It will also propose a strategy to mitigate big data’s potential challenges or risks effectively.
The potential benefits of having big data as a part of a clinical system include improved research and better patient care. As mentioned earlier, big data means enormous amounts of information. When researchers have large volumes of information, they are more likely to collect enough data for medical research.
Hassan et al. (2019) note that big data enhances better and more unbiased medical research since there is enough data from which to draw conclusions. In addition, big data in clinical systems can lead to better patient care in that adequate data volumes mean a better understanding of current patient care services. According to Shilo et al. (2020), big data enables healthcare administrators to understand patient care experiences better, thus improving them.
The potential challenges and risks of using big data in clinical systems include privacy and security issues and lack of the required talent/skillset. Big data entails patients’ personal/medical information. Thew (2016) notes that access to patient data by unauthorized persons may lead to privacy and security issues as the data can be used for phishing and scams, among other malicious intentions. In addition, managing and analyzing big data requires a certain skill set, which is a significant challenge. A combination of statistical, medical, and information technology knowledge is needed to apply big data solutions, which is hard to find.
One strategy to mitigate the risks of using big data in clinical systems is robust data privacy and security safeguards. These safeguards include biometric verification, passwords, firewall installation, and the development of institutional policies for data protection. The other strategy is providing comprehensive and quality data training for the personnel to manage big data in an institution. Therefore, using the proposed strategies will help overcome big data risks and enable an institution to enjoy big data benefits.
Discussion: Big Data Risks and Rewards NURS 6051 References
Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6(1), 1-25. https://doi.org/10.1186/s40537-019-0217-0
Hassan, M. K., El Desouky, A. I., Elghamrawy, S. M., & Sarhan, A. M. (2019). Big data challenges and opportunities in healthcare informatics and smart hospitals. Security in Smart Cities: Models, Applications, and Challenges, 3-26. https://doi.org/10.1007/978-3-030-01560-2_1
Shilo, S., Rossman, H., & Segal, E. (2020). Axes of a revolution: challenges and promises of big data in healthcare. Nature Medicine, 26(1), 29-38. https://doi.org/10.1038/s41591-019-0727-5
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Accessed 21st June 2023 from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
HealthIT.gov. (2018c). What is an electronic health record (EHR)? Retrieved from
https://www.healthit.gov/faq/what-electronic-health-record-ehr
Also Read: Assignment: Evidence-Based Project, Part 2: Advanced Levels of Clinical Inquiry and Systematic Reviews
Discussion: Big Data Risks and Rewards NURS 6051 Example 3
Technology advancements have revolutionized healthcare delivery. Big data entails widely implemented technology, focusing on increasing efficiency in care delivery. An example of big data is electronic health records widely applied in all healthcare facility departments. These technologies convey risks and advantages, and this essay addresses the advantages and rewards of big data in healthcare.
One of the potential benefits of big data is improved decision-making (Ngiam & Khor, 2019). Decisions made are high-quality and big data improves access to information and analytics. Big data helps provide a patient health history and analytics such as prevalence, incidences, and rates without much hustle. The information and analytics help make better care decisions hence better outcomes.
Ngiam and Khor (2019) note that big data also enhances healthcare data organization, making it easy to retrieve and utilize. Patient information is significant, and big data integration in the healthcare system allows individuals to organize information appropriately for more efficient care. For example, nurses can categorize patients based on age or diagnosis for easier management.
One potential risk of big data use is incompetent data analysis risks (Ngiam & Khor, 2019). Healthcare decisions primarily rely on analyzed data for decision-making. Big data provide an efficient way for data analysis. However, mistakes in the analysis process may lead to significant problems due to poor inferences and bad decisions based on wrong analysis.
Vigilance is thus necessary to prevent such problems. Data privacy issues are also a common problem with Big Data in healthcare (Ngiam & Khor, 2019). External attackers often target data from these systems and can access patient data for personal use, which is against privacy rules and regulations.
Intrusion detection and encryption software are essential strategies for ensuring the security and privacy of healthcare data (Price & Cohen, 2019). These strategies help prevent intruders from accessing the systems and also help ensure intruders who access the systems are detected and action against their activity implemented.
My current institution uses multiple data systems to ensure data analyzed is correct. Analysis using different systems helps establish data consistency and reliability. Big data integral in healthcare systems are vital and covey benefits such as better decision making. However, issues such as privacy and security breaches affect the technologies. Strategies such as intrusion detection can help address these risks.
References
Ngiam, K. Y., & Khor, W. (2019). Big data and machine learning algorithms for healthcare delivery. The Lancet Oncology, 20(5), e262-e273. https://doi.org/10.1016/S1470-2045(19)30149-4
Price, W. N., & Cohen, I. G. (2019). Privacy in the age of medical big data. Nature Medicine, 25(1), 37-43. https://doi.org/10.1038/s41591-018-0272-7
