BIG DATA RISKS AND REWARDS NURS 6051
Sample Answer for BIG DATA RISKS AND REWARDS NURS 6051 Included After Question
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.
RESOURCES
Be sure to review the Learning Resources before completing this activity.
Click the weekly resources link to access the resources.
WEEKLY RESOURCES
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.
*Note: Throughout this program, your fellow students are referred to as colleagues.
A Sample Answer For the Assignment: BIG DATA RISKS AND REWARDS NURS 6051
Title: BIG DATA RISKS AND REWARDS NURS 6051
When nurses enter data, they document essential information for the health team’s understanding of the patient. The importance of this information is critical to understanding and treatment methods. This data and the value of technology are meaningful use to a clinical system (Glassman, 2018). Technologies can be beneficial to gathering and analyzing patient data in a clinical setting. According to Glassman (2018), nurses must engage themselves in their feedback on big data processes and technology support. Nurses having a voice and being at the table to use good data for improved outcomes is key to making effective positive changes (Thew, 2016). Nurse leaders are interested in how to use big data for advocacy in best practice management.
The lack of data standardization and understanding of what to do with all the big data is an obvious barrier. As overwhelming as this subject is, I empathize with the nurse leader’s role in how to make changes from a large influx of data. To untap the value of big data, big data analytics and data mining may offer some solutions for healthcare organizations. Data management systems will help compartmentalize data suitable for big data that comes with healthcare data entry. A potential benefit for leaders is nurse managers using data analytics to view consolidated daily reports concerning patient safety concerns Wang et al. (2018). Data mining are tools to convert data into valuable knowledge. McGonigle & Mastrian, 2022 find that “Data mining includes tools for visualizing relations in the data and mechanizes the process of discovering predictive information in massive databases” (p.537). Nurse managers would be interested in how data mining technology could benefit the interests of their departments and patient outcomes. A nurse manager in a medical unit may be interested in fall prevention methods. Lee et al. (2011) further describe not all falls can be unavoidable, but reducing injuries and avoiding future falls align with desirable goals that healthcare providers and organizations could use from incident reporting system data. Incident data documentation reported by nurses would serve as data to establish fall prevention measures, guidelines, policies, and interventions. Big data could benefit this clinical area of interest through its abilities in data collection measures, methods, and analysis.
Some challenges of using big data are the need for data standardization and the failure of how data can interact (Thew, 2016). In the example of incidents of falls, accurate fall prediction models may use data from the incident reporting systems. Data that is hard to code or document may use the free text option, which can be a challenging variable. Misinterpretation can also add to the risks and challenges of big data.
Click here to ORDER an A++ paper from our Verified MASTERS and DOCTORATE WRITERS: BIG DATA RISKS AND REWARDS NURS 6051
A Sample Answer 2 For the Assignment: BIG DATA RISKS AND REWARDS NURS 6051
Title: BIG DATA RISKS AND REWARDS NURS 6051
A researched mitigation strategy to combat resistance to using big data is accepting and assuming the risk. Since fall prevention is a
hot topic, I believe big data is a risk worth investing in. The link between evidence-based nursing knowledge and big data can intertwine in the improvement efforts in fall prevention programs. Stevens et al. (2017) described how “improving case management and implementation strategies that promote patient adherence to evidence-based strategies is crucial to successfully reducing falls” (p.77). The argument of why a nurse manager would advocate for specific methods concerning fall prevention measures would have supportive data rather than resorting to a person-to-person debate. In efforts to improve and understand healthcare to a greater degree, meaningful data is necessary (McGonigle & Mastrian, 2022). By using big data, there is an opportunity for improvements in several aspects of healthcare.
Glassman, K. S. (2017). Using data in nursing practice Links to an external site. Links to an external site. American Nurse Today, 12(11), 45–47. Retrieved from https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdfLinks to an external site.
Lee, T., Liu, C., Kuo, Y., Mills, M. E., Fong, J., & Hung, C. (2011). Application of data mining to the identification of critical factors in patient falls using a web-based reporting system. International Journal of Medical Informatics, 80(2), 141–150. https://doi.org/10.1016/j.ijmedinf.2010.10.009
Links to an external site.
McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning
Stevens, J. A., Smith, M. L., Parker, E. M., Jiang, L., & Floyd, F. D. (2017). Implementing a Clinically Based Fall Prevention Program. American Journal of Lifestyle Medicine. https://doi.org/10.1177/1559827617716085
Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs, and Links to an external site. Links to an external site. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Links to an external site. Links to an external site. Technological Forecasting and Social Change, 126(1), 3–13.
A Sample Answer 3 For the Assignment: BIG DATA RISKS AND REWARDS NURS 6051
Title: BIG DATA RISKS AND REWARDS NURS 6051
I appreciate your comments here. Healthcare informatics helps decrease discrepancies between caregivers, assists staff to effectively problem solve, facilitates data analysis, and allows nurses to generate plans and improve patient outcomes. Technology also increases nurses’ ability to focus their attention directly on patients and patient care as well as increase accuracy of interventions, medication administration, etc., (Laureate Education, Inc. 2018). I’m sure you utilize informatics and technology continuously in nearly all tasks performed daily. One goal is for organizations to review data to streamline, and cost-save. I am looking forward to the next generation of medical technology as I believe it can only enhance nursing performance and patient outcomes. What specific data collection would allow you to be more effective and efficient in your nursing role? Thanks, Dr. Howe
In relation to fall prevention, I would suspect data collection would be from fall risk assessments and education intervention documentation. That would be the usable and practical information that technologies could provide to strategize where the areas of improvement could be made in nursing interventions. Data synthesis could help these nursing performance enhancements and improve patient outcomes of safety reduction measures.
There is much we can talk about concerning the positive part of big data. Big data in healthcare has great significance especially in the prediction of possible outcome of diseases prevention of co-morbidities, mortality and taking care of medical treatment expenses (Pastorino et al., 2019). In the era of technology, more people are in need of relevant information especially that touches on patients regarding their healthcare options or choices as well as how they will be part of their health decision-making process. In essence, the use of big data will help to equip patients with relevant and timely information to assist them be greatly involved in arriving at decisions that directly impact their care and treatment.
Reference
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. doi: 10.1093/eurpub/ckz168
Click here to ORDER an A++ paper from our Verified MASTERS and DOCTORATE WRITERS: BIG DATA RISKS AND REWARDS NURS 6051
A Sample Answer 4 For the Assignment: BIG DATA RISKS AND REWARDS NURS 6051
Title: BIG DATA RISKS AND REWARDS NURS 6051
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.
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
A Sample Answer 5 For the Assignment: BIG DATA RISKS AND REWARDS NURS 6051
Title: BIG DATA RISKS AND REWARDS NURS 6051
Big Data refers to the collection of data from a variety of sources such as electronic health records, medical imaging. payor records, pharmaceutical research, wearables, Patient controlled analgesia, and medical devices.
Health care providers have digital access to huge amounts of data at their fingertips. They can provide care in real time while obtaining the necessary data through technology and physical monitoring devices. An example would be a patient wearing a cardiac halter monitor and, a provider being able to retrieve data to aid in treating the patient. This would be an example an of machine learning algorithms which can trigger an alert and interventions can be made as needed (Beam & Kohane, 2018). A nurse can review a patient’s electronic medical health record. And determine whether a patient has any medication allergies prior to administering a life-saving drug.
I believe one of the most important benefits to big data while increasing efficiencies and help sharpen our understanding of the best practices associated with any disease or injury (Alemi, 2020). For example, a health care provider may follow a cardiac patients lab over an extended period, while looking for trends, and tailoring their care plan according to the patients needs. With these advances a patient can track their own results as well.
Challenges of Using Big Data in a Clinical setting
One challenge of usage of Big Data system is the ability of capturing all points of interaction between patient and the healthcare system. There is a limited number of operational national health information exchange (Househ et al., 2017).
Good job on your post, You addressed some valid points regarding data size. When data capacities are so large, it becomes difficult to determine which data points are valuable and insightful. It can create difficulty for nurse leaders who want to analyze, compute data and discover new knowledge to reveal patterns, trends, and associations, especially relating to human behavior and interactions that can improve the quality of care their staff provides. Another challenge is ensuring that the significant data insights are in the hands of the right people so that they can work honestly and critical information is not misused. Also, there can be challenges that may arise due to missing data or incomplete data.
Big Data can help healthcare providers meet these goals in unprecedented ways. The potential of Big Data in healthcare relies on the ability to detect patterns and to turn high volumes of data into actionable knowledge for precision medicine and decision-makers. In several contexts, the use of Big Data in healthcare is already offering solutions for improving patient care and generating value in healthcare organizations. By increasing earlier diagnosis and the effectiveness of information on health and access to health services and quality of treatments through the discovery of early signals. Overall, Big Data and predictive analytics can contribute to disease intervention and reduce the probability of adverse reactions. The major challenge with big healthcare data is sorting and prioritizing information.
A Sample Answer 6 For the Assignment: BIG DATA RISKS AND REWARDS NURS 6051
Title: BIG DATA RISKS AND REWARDS NURS 6051
“Big data analytics has grown and evolved to 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 et.al., 2018). Clinical systems will be able to benefit largely from the continuous growth and usage with big data analytics. According to Mcongigle & Mastrian (2022), one of the greater benefits of using data mining and big data is that this gathered data can be used as predictive and proactive data. This means that clinical systems can create predictions on patient care,economics, financing, and essentially any other important topic. With the ability to make predicitions using big data, clinical systems will be able to make beneficial decisions for their success.
A potential challenge to the use of big data analytics as part of the clinical system is the lack of understanding of how to properly use and interpret this data. Without understanding the proper use of big data, incorrect interpretation can lead to errors of judgment and questionable decisions made within the clinical systems (Wang et. al., 2018). Because of this, thorough training and education will be important to provide to the individuals who will be working directly with the incoming data the clinical systems plan to utilize.
According to coursera.org (2023), electronic health records (EHR’s) are the most commonly seen use of big data in healthcare. This is something that I have frequently experienced or observed, and believe that it is one of the benefits of big data analytics in clinical systems. “Pairing the big data produced by EHRs with advanced analytics techniques like machine learning, medical researchers can create predictive models with various applications, such as predicting post-surgical complications, heart failure, or substance abuse”, (coursera.org, 2023). I have seen and used these predictive applications during my practice, and have seen them be beneficial. These systems assist the healthcare provider in quick identification of issues, and allow them to make sound decisions based on factual data to improve outcomes.
coursera.org. (2023). Big data in health care: What it is, benefits, and jobs. https://www.coursera.org/articles/big-data-in-healthcare
McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning
Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizationsLinks to an external site.. Technological Forecasting and Social Change, 126(1), 3–13.