Discussion: Big Data Risks and Rewards

Discussion: 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 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.
RUBRIC
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.
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Solution
Big Data Risks and Rewards in Healthcare
The revolutionary report by the Institute of Medicine in 1999 titled To Err Is Human marked the beginning of the appreciation of big data and technology as its facilitator in healthcare. The report was the first to suggest that big data analytics through technology could be used to prevent human error in healthcare (Palatnik, 2016).
Since then, big data analytics such as electronic health records (EHRs) have transformed healthcare efficiency and quality for the better (McGonigle & Mastrian, 2017; Sweeney, 2017). According to Glassman (2017), big data analytics facilitated by technology is instrumental in shaping and guiding clinical decision making.
One potential benefit of using big data as part of a clinical system is that it helps with quick and accurate clinical decision making (Wang et al., 2018; McGonigle & Mastrian, 2017). The reason for this is that through big data, trends on various performance measures can be quickly and efficiently analyzed compared to if this were to occur manually (Wang et al., 2018). The results of data analysis are presented very quickly and even likely scenarios can be modelled and predicted
One potential challenge or risk of using big data is loss or theft (unauthorized access) of patient data. This is breach of patient confidentiality and has got far-reaching legal and ethical consequences. This is especially likely given the requirement that all facility EHRs be interoperable and accessible for an outside organization (Alotaibi & Federico, 2017).
One strategy that has been researched by the author and that can be used to effectively mitigate the risks of using big data such as the one above is the incorporation of a firewall into the EHR architecture for the organization. This will provide a first line of defense for attacks to the system from outside (Wang et al., 2018; McGonigle & Mastrian, 2017).
The firewall software will alert the nurse informaticist who is the guardian of the EHR system when there has been unauthorized access (or attempted access) from outside the organization. It will also actively prevent these kinds of attacks and breach of data.
References
Alotaibi, Y., & Federico, F. (2017). The impact of health information technology on patient safety. Saudi Medical Journal, 38(12), 1173–1180. https://doi.org/10.15537/smj.2017.12.20631
Glassman, K.S. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45–47. https://www.myamericannurse.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf
McGonigle, D., & Mastrian, K.G. (2017). Nursing informatics and the foundation of knowledge, 4th ed. Jones & Bartlett Learning.
Palatnik, A. (2016). To err is human. Nursing Critical Care, 11(5), 4. https://doi.org/10.1097/01.CCN.0000490961.44977.8d
Sweeney, J. (2017). Healthcare informatics. Online Journal of Nursing Informatics (OJNI), 21(1). https://www.himss.org/library/healthcare-informatics
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. https://doi.org/10.1016/j.techfore.2015.12.019

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