NURS 6051 Discussion: Big Data Risks and Rewards
NURS 6051 Discussion Big Data Risks and Rewards
As technology advances, so does the ability to obtain and analyze large sets of data from numerous differing sources. The result of this voluminous information is called big data. Big data is the name given to the vast amount of datasets within the organization that are difficult to manage due to their lack of structure (McGonigle & Mastrian, 2018). The universal move from paper charting to the electronic health record (EHR) has allowed more efficient access to all aspects of current healthcare documentation along with older data via backup and storage media.
The daily use of an EHR provides a continual data set that can easily be probed and assimilated to produce information that can then be used to influence positive patient outcomes. Trends in the documentation found to be useful during the monitoring and management of patient care can be examined and used to direct change in future policies and procedures. Due to the universal language of most charting modules within a health system, the data can easily be searched and mined for a specific metric. An issue arises when a query wishes to retrieve charting details from an unstructured area, such as narrative charting entries.
As long as EHRs allow custom narrative entries, the ability to pull organized system-wide search results will be time and labor-intensive. The unformatted information must then be manually viewed, read, and sorted. Lack of integration is a prime example of how big data mining can be overwhelming and cumbersome within a clinical system (Wang et al., 2018).
One strategy used to mitigate the challenge of big data is using a checkbox flowsheet method of universal charting. The structured format of this technique provides organized, easily accessible, and easily interpreted results to the informaticist (Glassman, 2017). Although using the narrative approach can be more efficient at times by grouping together multiple assessment categories in one location, the information could be invisible and, therefore, unavailable for the requested project at hand.
NURS 6051 Discussion Big Data Risks and Rewards References
Glassman, K. S. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45–47. Retrieved from https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf
McGonigle, D., & Mastrian, K. (2018). Nursing Informatics and the Foundation of Knowledge (4th ed.). Jones and Bartlett Learning.
Wang, Y., Kung, L., & Byrd, T. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3-13. https://doi.org/10.1016/j.techfore.2015.12.019
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.
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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.
Thank you for your post. You have indicated that big data can help track and slow down diseases, but it is also disadvantageous due to the data breach risk. I agree with your arguments as they reflect the view of McGonigle & Mastrian (2022), who notes that big data analytics can provide a deep insight into clinical data, facilitating quick decision-making concerning disease prevention. Similarly, Glassman (2017) argues that big data analytics is prone to manipulation, which may lead to the loss of critical data or violation of privacy. Healthcare organizations should therefore employ stringent security measures to protect their clients’ information.
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.
*Note: Throughout this program, your fellow students are referred to as colleagues.
Hi Shanea. Over the past decade, there has been a greater emphasis on the involvement of registered nurses in the development and implementation of health information technology systems to maintain patient safety and improve the quality of care services. Today, electronic health records remain a great source of protected health information and clinical documentation during the provision of care services by registered nurses and other healthcare professionals (Reid et al., 2021). The rapid deployment of EHR by healthcare organizations has created room for registered nurses to create digital versions of patient medical records and transform them into valuable clinical knowledge for preventing adverse events like patient falls and nosocomial infections, among many others. One of the greatest risks of utilizing big data from the digital versions of patient medical records is to maintain the integrity and quality of information system output (McGonigle & Mastrian, 2022). For instance, the digital versions of patient medical records are prone to manipulation and misinterpretation due to weak information security measures and the lack of relevant knowledge and skills for maintaining data integrity and quality. Through regular education and training, registered nurses and other healthcare professionals develop the required nursing informatics competencies, like maintaining strong access credentials for clinical information systems and data encryption to prevent manipulation and unauthorized access.
Submission and Grading Information
NURS 6051 Discussion Big Data Risks and Rewards Grading Criteria
To access your rubric:
Week 5 Discussion Rubric
Post by Day 3 and Respond by Day 6 of Week 5
To participate in this Discussion:
Week 5 Discussion
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NURS 6051 Discussion Big Data Risks and Rewards Rubric Detail
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Content
Name: NURS_5051_Module03_Week05_Discussion_Rubric
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Excellent Good Fair Poor
Main Posting
Points Range: 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.
Points Range: 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.
Points Range: 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.
Points Range: 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
Points Range: 10 (10%) – 10 (10%)
Posts main post by day 3.
Points Range: 0 (0%) – 0 (0%)
Points Range: 0 (0%) – 0 (0%)
Points Range: 0 (0%) – 0 (0%)
Does not post by day 3.
First Response
Points Range: 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.
Points Range: 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.
Points Range: 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.
Points Range: 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
Points Range: 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.
Points Range: 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.
Points Range: 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.
Points Range: 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
Points Range: 5 (5%) – 5 (5%)
Meets requirements for participation by posting on three different days.
Points Range: 0 (0%) – 0 (0%)
Points Range: 0 (0%) – 0 (0%)
Points Range: 0 (0%) – 0 (0%)
Does not meet requirements for participation by posting on 3 different days.
Total Points: 100
Name: NURS_5051_Module03_Week05_Discussion_Rubric
NURS 6051 Discussion Big Data Risks and Rewards Grading Rubric Guidelines
| Performance Category | 10 | 9 | 8 | 4 | 0 |
| Scholarliness
Demonstrates achievement of scholarly inquiry for professional and academic decisions. |
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| Performance Category | 10 | 9 | 8 | 4 | 0 |
| Application of Course Knowledge –
Demonstrate the ability to analyze, synthesize, and/or apply principles and concepts learned in the course lesson and outside readings and relate them to real-life professional situations |
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| Performance Category | 5 | 4 | 3 | 2 | 0 |
| Interactive Dialogue
Replies to each graded thread topic posted by the course instructor, by Wednesday, 11:59 p.m. MT, of each week, and posts a minimum of two times in each graded thread, on separate days. (5 points possible per graded thread) |
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Summarizes what was learned from the lesson, readings, and other student posts for the week. |
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| Minus 1 Point | Minus 2 Point | Minus 3 Point | Minus 4 Point | Minus 5 Point | |
| Grammar, Syntax, APA
Note: if there are only a few errors in these criteria, please note this for the student in as an area for improvement. If the student does not make the needed corrections in upcoming weeks, then points should be deducted. Points deducted for improper grammar, syntax and APA style of writing. The source of information is the APA Manual 6th Edition |
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| 0 points lost | -5 points lost | ||||
| Total Participation Requirements
per discussion thread |
The student answers the threaded discussion question or topic on one day and posts a second response on another day. | The student does not meet the minimum requirement of two postings on two different days | |||
| Early Participation Requirement
per discussion thread |
The student must provide a substantive answer to the graded discussion question(s) or topic(s), posted by the course instructor (not a response to a peer), by Wednesday, 11:59 p.m. MT of each week. | The student does not meet the requirement of a substantive response to the stated question or topic by Wednesday at 11:59 pm MT. |