Big Data Risks and Rewards NURS 6051 Discussion

Want create site? With Free visual composer you can do it easy.

Big Data Risks and Rewards NURS 6051 Discussion

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.

Click here to ORDER NOW FOR AN ORIGINAL PAPER ASSIGNMENT ON  Big Data Risks and Rewards NURS 6051 Discussion

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. Big Data Risks and Rewards NURS 6051 Discussion

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 4

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. Big Data Risks and Rewards NURS 6051 Discussion

By Day 6 of Week 4

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.

*Note: Throughout this program, your fellow students are referred to as colleagues. Big Data Risks and Rewards NURS 6051 Discussion.

Big Data Risks and Rewards NURS 6051 Discussion

The health care arena relies on data, both subjective and objective, to determine and plan individualized care for each patient. The use of technology has paved the way for nurses to conveniently collect and gather information from patients. Nursing informatics is used in practice settings to help organize and apply data, information, knowledge, and wisdom to make a decision and provide care (Laureate Education, 2012). Big Data Risks and Rewards NURS 6051 Discussion

The information collected from every patient can create a large set of information that helps health care professionals to establish a pattern and improve patient outcomes.  In a diary by Tishgart in 2012, “more data means more knowledge, greater insights, smarter ideas and expanded opportunities for organizations to harness and learn from their data” (cited in McGonigle & Mastrian, 2018). In the hospital I work at, there had been an increase in patient complaints in the Emergency Room (ER) because of bed unavailability in floor units which sometimes caused a deterioration of patients’ status while waiting. This has led the management to investigate the overall data on floor units’ discharges and it had been found out that several factors such as home medication preparations, physicians’ orders, nursing staffing have contributed to an unintentional delay of patient discharges causing an increase waiting time of patients in the ER. All these sets on information were gathered overtime and had made changes in our discharge procedures to accommodate patients and improve health outcomes. According to Englebright, “big data will also facilitate a balanced approach to assessing organizational and nursing performance” (cited in Thew, 2016).

In this generation, technology is getting better, the internet is getting smarter and health care is growing more electronically base. Today, cybercrime is becoming more successful by targeting computers and using it as a weapon for hackers to steal data. According to a video by Vinay, the most common challenge for big data in healthcare is data security (Vinay, 2014). It only takes a single hacker to get into an electronic record and collect valuable information regarding patients which causes a violation of the Health Insurance Portability and Accountability Act (HIPPA). The breach in healthcare data can cost a single hospital an average of 7 million U.S. dollars for litigation, fines and reputation damage (Jalali & Kaiser, 2018).  However, the risk of cybercrime is mitigated through adding security measures in computer software and application and continuous training of employees to become more aware of possible hackers. For instance, in our hospital has disabled some websites in our computers that could possibly be used by hackers to get into our data, our password in our work accounts requires to be changed every 12 weeks, and training is conducted every year to inform employees in identifying phishing baits by hackers through e-mail, phone calls, and text messages.

Big data are crucial in the health care profession in creating a plan of care to improve overall patient outcomes. These are sets of information nurses utilize in generating knowledge necessary for safe practice. However, these amounts of information can also be a threat to the entire health care field and patient population when breached and stolen. It is then imperative for the health care industry to protect these data and information by all means.

References

Jalali, M. S., & Kaiser, J. P. (2018, May 28). Cybersecurity in Hospitals: A Systematic, Organizational Perspective. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5996174/

Laureate Education (Executive Producer). (2012). Data, information, knowledge and wisdom continuum [Multimedia file]. Baltimore, MD: Author. Retrieved from http://mym.cdn.laureate-media.com/2dett4d/Walden/NURS/6051/03/mm/continuum/index.html

McGonigle, D., & Mastrian, K. G. (2018). Nursing informatics and the foundation of knowledge (Fourth). Burlington, MA: Jones & Bartlett Learning.Practices.

Vinay Shanthagiri. (2014). Big Data in Health Informatics [Video file]. Retrieved from https://www.youtube.com/watch?v=4W6zGmH_pOw.

Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs

RE: Discussion – Week 4
COLLAPSE

The utilization of big data has allowed health care teams to provide better patient outcomes. As explained by McGonigle and Mastrian (2017) “Big data does not just refer to size, but rather is an opportunity to find insights in new and emerging types of data and content, to make your business more agile, and to answer questions that were previously considered beyond your research” (pg. 481). A potential benefit of using big data as a part of a clinical system is being able to get broad and generalized information. For example, using the electronic medical record allows a nurse to look at past medical history, surgical history, vital signs, medications and active admission problems. “Big data analytics that is evolved from business intelligence and decision support systems enable healthcare organizations to analyze an immense volume, variety and velocity of data across a wide range of healthcare networks to support evidence-based decision making and action taking” (Wang, Kung and Byrd, 2018). For this reason, big data can help identify cures for diseases.

At the same time, big data has potential harm when used in a healthcare setting. Major over generalizations, false discoveries, and meaningless correlations have been reported which can cause medical and clinical error. In return, these errors may cause selection bias, missing values, sample size, interpretation problem, dependence problems and data handling methodology (Househ, Aldosari, Alanazi, Kushniruk and Borycki, 2017).

I would imagine a strategy to mintage these potential harms would be to train healthcare informaticists to analyze the data. There would also need to be a strict organizational guidelines to manage the large volumes of data.

References

Househ, M. S., Aldosari, B., Alanazi, A., Kushniruk, A. W., & Borycki, E. M. (2017). Big Data, Big Problems: A Healthcare Perspective.Studies In Health Technology And Informatics, 238, 36-39. Retrieved from https://search-ebscohost-com.ezp.waldenulibrary.org/login.aspx?direct=trye&db=mnh&AN=28679881&site=eds-live&scope=site

McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning.

Wang, Y. Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126(1), 3-13. doi:10.1016/j.techfore.2015.12.019 Big Data Risks and Rewards NURS 6051 Discussion

Rubric Detail

Select Grid View or List View to change the rubric’s layout.

Name: NURS_5051_Module03_Week04_Discussion_Rubric
Grid View
List View
Excellent Good Fair Poor
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.
40 (40%) – 44 (44%)
Responds to the discussion question(s) and is reflective with critical analysis and synthesis of knowledge gained from the course readings for the module.

At least 75% of post has exceptional depth and breadth.

Supported by at least three credible sources.

Written clearly and concisely with one or no grammatical or spelling errors and fully adheres to current APA manual writing rules and style.
35 (35%) – 39 (39%)
Responds to some of the discussion question(s).

One or two criteria are not addressed or are superficially addressed.

Is somewhat lacking reflection and critical analysis and synthesis.

Somewhat represents knowledge gained from the course readings for the module.

Post is cited with two credible sources.

Written somewhat concisely; may contain more than two spelling or grammatical errors.

Contains some APA formatting errors.
0 (0%) – 34 (34%)
Does not respond to the discussion question(s) adequately.

Lacks depth or superficially addresses criteria.

Lacks reflection and critical analysis and synthesis.

Does not represent knowledge gained from the course readings for the module.

Contains only one or no credible sources.

Not written clearly or concisely.

Contains more than two spelling or grammatical errors.

Does not adhere to current APA manual writing rules and style.
Main Post: Timeliness
10 (10%) – 10 (10%)
Posts main post by day 3.
0 (0%) – 0 (0%)
0 (0%) – 0 (0%)
0 (0%) – 0 (0%)
Does not 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.
15 (15%) – 16 (16%)
Response exhibits critical thinking and application to practice settings.

Communication is professional and respectful to colleagues.

Responses to faculty questions are answered, if posed.

Provides clear, concise opinions and ideas that are supported by two or more credible sources.

Response is effectively written in standard, edited English.
13 (13%) – 14 (14%)
Response is on topic and may have some depth.

Responses posted in the discussion may lack effective professional communication.

Responses to faculty questions are somewhat answered, if posed.

Response may lack clear, concise opinions and ideas, and a few or no credible sources are cited.
0 (0%) – 12 (12%)
Response may not be on topic and lacks depth.

Responses posted in the discussion lack effective professional communication.

Responses to faculty questions are missing.

No credible sources are cited.
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.
14 (14%) – 15 (15%)
Response exhibits critical thinking and application to practice settings.

Communication is professional and respectful to colleagues.

Responses to faculty questions are answered, if posed.

Provides clear, concise opinions and ideas that are supported by two or more credible sources.

Response is effectively written in standard, edited English.
12 (12%) – 13 (13%)
Response is on topic and may have some depth.

Responses posted in the discussion may lack effective professional communication.

Responses to faculty questions are somewhat answered, if posed.

Response may lack clear, concise opinions and ideas, and a few or no credible sources are cited.
0 (0%) – 11 (11%)
Response may not be on topic and lacks depth.

Responses posted in the discussion lack effective professional communication.

Responses to faculty questions are missing.

No credible sources are cited.
Participation
5 (5%) – 5 (5%)
Meets requirements for participation by posting on three different days.
0 (0%) – 0 (0%)
0 (0%) – 0 (0%)
0 (0%) – 0 (0%)
Does not meet requirements for participation by posting on 3 different days.
Total Points: 100
Name: NURS_5051_Module03_Week04_Discussion_Rubric

Did you find apk for android? You can find new Free Android Games and apps.