Big Data Means Big Potential Challenges for Nurse

Week 5 NURS 6051Trans Nursing Tech Respond to 2 students Module 3: Data-Information-Knowledge-Wisdom (DIKW) (Week 5) • • Learning Objectives Students will: Analyze benefits, challenges, and risks of using big data in clinical systems Recommend strategies to mitigate challenges and risks of using big data in clinical systems 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. Big Data Means Big Potential Challenges for Nurse

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. 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. 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. I did included the 2 students discussion, and MINE discussion as well at the end of this attach Rubric Detail Exit • Excellent 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. Main Post: Timeliness 10 (10%) – 10 (10%) Posts main post by day 3. Excellent 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. Big Data Means Big Potential Challenges for Nurse

Communication is professional and respectful to colleagues. Responses to faculty questions are fully answered, if posed. Response is effectively written in standard, edited English. 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 . Excellent 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. Participation 5 (5%) – 5 (5%) Meets requirements for participation by posting on three different days. Total Points: 100 Name: NURS_5051_Module03_Week05_Discussion_Rubric Learning Resources Required Readings McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning. • • Chapter 22, “Data Mining as a Research Tool” (pp. 477-493) Chapter 24, “Bioinformatics, Biomedical Informatics, and Computational Biology” (pp. 537-551) 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-Data1030.pdf 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-challengesnurse-execs 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. Required Media Laureate Education (Executive Producer). (2012). Data, information, knowledge and wisdom continuum [Multimedia file]. Baltimore, MD: Author.

Retrieved from http://mym.cdn.laureatemedia.com/2dett4d/Walden/NURS/6051/03/mm/continuum/index.html Laureate Education (Producer). (2018). Health Informatics and Population Health: Analyzing Data for Clinical Success [Video file]. Baltimore, MD: Author. See below the 2 students discussion to respond Student #1 SL RE: Discussion – Week 5 C OLLA PSE The healthcare organization generates large quantities of data for record-keeping and maximization of health care outcomes. However, big data is customized information that can improve patient outcomes (Wang et al., 2018). Big data involves a collection of captured information and is beyond the ability of the technology to manage it. In health settings, data regarding patients, such as behavior data, lab tests, and other details, can be collected and stored to be used later. Big data use modern techniques and technologies to allow the distribution, management, and analysis of personalized information to improve health care and reduce health costs. Potential benefit The main benefit of using Big data is that physicians can easily access information regarding a particular patient and recommend to them the best treatment (Dimitrov, 2016). For example, patients living far away from the hospital can use devices to inquire about their resulted lab values and diagnostics testing. This, in turn, empowers the patient and the physician to plan treatment based on this information. Another example is patient outcomes can be predicted based on the available data such as the length of stay, patients who may or not benefit from elective surgery, individuals at risk of medical complications, and threats in advancing certain diseases (Dash et al., 2019). Potential challenge Cyberattack of health care information is on the rise. More systems are at risk for ransomware attacks in recent years. Attackers use this information to steal identities more effectively as most often they are a c complete record of a person (Department of justice, 2015). HIPPA is something we all hear about daily; we do our best to ensure that we have not violated a patient’s privacy in many ways, from closing the door while bathing and asking questions to input information collected for research. Recently, my thoughts have wandered to the COVID 19 patients. Some of the patients I see do not require high flow oxygen or appear to be in any distress, and their lab values are mostly within the normal ranges yet are admitted to the hospital. My question is, why is it so that the CDC can track the survivability of COVID better or track treatment to improve patient outcomes. Because a patient being hospitalized is one way the CDC can get around consenting people for a study. Thew reminds us that having all patients’ medical data in one software system is more efficient for healthcare providers (2016). How do we protect that data? Strategy to mitigate the challenges of big data The best recommendation is that big data systems need to be packaged in a pull-down menu to allow continuous data acquisition and cleansing. The big data should also be fragmented regularly in Legacy IT systems with incompatible formats for security purposes. In conclusion, big data can allow sophisticated technologies to utilize clinical data repositories and make informed decisions. Eventually, rapid advances in systems and tools can help to address the main challenges highlighted above. A team of information technologists orchestrates all this. References 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 Department of justice. (2015). Prosecuting Computer Crimes [PDF]. justice.gov. Retrieved December 29, 2020, from https://www.justice.gov/sites/default/files/criminal-ccips/legacy/2015/01/14/ccmanual.pdf Dimitrov, D. V. (2016). Medical internet of things and big data in healthcare. Healthcare Informatics Research, 22(3), 156. https://doi.org/10.4258/hir.2016.22.3.156 Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. healthleadersmedia.com. https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challengesnurse-execs 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 Student #2 AG RE: Discussion – Week 5 C OLLA PSE Discussion Post: Big Data Risk and Rewards We are currently living in the everlasting peak of big data that has tremendously affected health information technology, especially in our sector of nursing. As nurses, we are in a profession that is suited for such a trending environment. Big Data Means Big Potential Challenges for Nurse

We are the largest professional group within the healthcare industry that has been a key player towards solving quality patient outcomes and safety (Glassman, 2017). Yet as we continue to be key components in patient driven solutions, embracing health information technology and informatics needs to be academically attained (Wang et al. 2018). The gain in informatics knowledge of big data has shown its risks and benefits. Analyzing these risks and benefits and strategizing how to continue improving on big data can lead to greater outcomes for the patients we care for. One potential benefit of using big data as part of our clinical system has been delivering patient education beyond the inpatient admission. Health information Technology for Economic and Clinical Health (HITECH) Act has promoted the adoption of respectfully using patient private data to be accessed in a portal between patient (outside of hospital) and the hospitals healthcare teams. Within this portal patients can continue to input health data such as vital signs, medications, symptoms, blood lab work, etc. (Glassman, 2017). This input of data aids in nurses being able to download and manage the download the knowledge so that they can seek out alerts on negative trends that might affect a patient’s plan of care when they come back for an appointment or test. This is a highly beneficial use of bug data as part of our clinical system because there is meaningful use of eHAR, patient care outcomes are carried out and continued after a hospital stay or appointment, and also improves care coordination of public/community health while maintaining patient privacy. In contradiction, there are potential challenges and risks that comes with health information technology as it continues to advance and change. One primary challenge is that although data is grand picking up quantitative data, it doesn’t know to decipher between the statistics and qualitative themes. “The frustration we often have as nurse leaders in looking at this data is [that] some of the variable we care about most aren’t even in the data” (Thew, 2016). Meaning themes like patient advocacy, autonomy, nursing competency, and commitment, the building blocks of nursing are difficult to recognize and pick up. These building blocks are components of effective and high- quality patient care. If data cannot pick up on these important key factors, how do we gather ample evidence-based research to know our interventions have been positively affecting a population? A strategy that could help in this potential challenge is through the input and contribution of nurses. Being part of the “selection process for new technology, providing feedback about technology support” (Thew, 2017), can improve our workflow on the units, can improve patient care outcomes. Nursing input towards research can improve big data, which can then be beneficial to us as we continue to increasingly use it on our units and healthcare organizations worldwide. References Glassman, K.S. (2017). Using Data in Nursing Practice. American Nurse Today, 12 (11), 45-47. Retrieved from https://www.myamericannurse.com/wpcontent/uploads/2017/11/ant11-Data-1030.pdf Thew, J. (2016, April, 19). Big data means big potential, challenges for nurse execs. Big Data Means Big Potential Challenges for Nurse

Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-bigpotential-challenges-nurse-execs 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. Retrieved from https://wwwsciencedirectcom.ezp.waldenulibrary.org/science/article/pii/S0040162516000500?via%3Dihub AND THIS IS MY DISCUSSION FOR TUTOR TO READ. Big Data Capabilities and Challenges Big data presents a lot of promises as well as challenges in the healthcare industry. On the one hand, my interaction with and research in big data revealed the potential benefits of improving operational efficiency as well as care outcomes. Pastorino et al. (2019) discuss the use of big data in precision medicine through intervening in high-risk and high-cost patients to ensure effective care and efficiency as well. This approach is useful in finding areas of underperformance and determining necessary improvements. For example, big data may be used, and can be beneficial to determine the average hospital duration and wait times for patients. Another big technology largely used today by many hospitals is the use of telemedicine where doctors can perform patient assessment at bed side using control remote robots while they are physically away in their office. Another is Radiology departments have been using the Picture Archiving and Communications System (PACS). This system electronically stores images and reports, instead of using the old methods of manually filing, retrieving and transporting film jackets which were used for storing x-ray films until late 1990s. The PACS is an example of Big data and technology created to expedite patient care based on fast diagnostic delivering report. This information can then be used to develop an intervention to enhance patient throughout and improve efficiency. On the other hand, a challenge that is faced in big data for clinical use is the problem of having different definitions and descriptions of different data objects. Hospitals measure their data and define it in different terms although there are some standards on care assessment. Thew (2016) identifies this as a source of frustration since data may not be defined the same way. An example that I have seen is the compatibility of data for the same measure but defined differently. Big Data Means Big Potential Challenges for Nurse

For example, fall rates may be expressed as a number such as 10 falls in one month. However, they should further be expressed as fall rates per 1000 bed days. If one department presents data defined in the number of falls and another as fall rates per 1000 bed days, analyses becomes more complex and challenging. Another major issue is the Cyber attack and whole system shutting down, and people stealing patient information. Strategies that can be apply to deal with the nuances of data definition, standards on data measurement and reporting should be implemented. Agencies such as the Centers for Medicare and Medicaid Services (CMS) have defined standards for some measures such as readmission rates. Standardizing data makes it easier to analyze through data mining and interpretation (McGonigle & Mastrian, 2017). Big Data Means Big Potential Challenges for Nurse

Therefore, standards should be extended to the different types of data used for clinical systems. Standardization will reduce the risk of errors in analysis and also increase analytical accuracy. References McGonigle, D., & Mastrian, K. G. (2017). Nursing informatics and the foundation of knowledge (4th ed.). Burlington, MA: Jones & Bartlett Learning. 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 Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Health Leaders. https://www.healthleadersmedia.com/nursing/big-data-means-big-potentialchallenges-nurse-execs THE END … Big Data Means Big Potential Challenges for Nurse