NURS 6051 BIG DATA RISKS AND REWARDS

Sample Answer for NURS 6051 BIG DATA RISKS AND REWARDS 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. 

NURS 6051 BIG DATA RISKS AND REWARDS
NURS 6051 BIG DATA 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. 

 

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A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

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. 

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.2010.10.009Links 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 2 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Introduction

 

According to Segal (2022), “big data refers to the large diverse set of information that grows at an ever-increasing rate”. This comprises of an amount of data, and the rate at which it is generated and captured including electronic health records (EHRs) medical imaging, genomic imaging, payor records, wearable and medical devices pharmaceutical research, etc. Big data can greatly impact any healthcare system and patient outcome when the relevant person views and compiles the information (Shilo,2020). The pledge of big data has brought great vision in health care research for treatment and innovation, personalized medicine, and optimal patient care that can reduce costs and impact client outcomes.

The EHR can produce outstanding data, software used by doctors and nurses and health care facilities in general for their daily activity. EHR is the big change health care need for progress and strengthens patient and clinician relationships. The Patient Protection and affordable care act, an electronic health record is being broadly adopted by most hospital care organizations large or small (Healthcare. gov,n.d). While there are benefits to EHRs, improving accessibility to patient data can create a threat to patient safety and increase the risk of Judicial liability for clinicians (Public Health,2021). Change in any environment required a new mindset and to be adaptable to ideas (McGonigle & Mastrian,2022).

The benefits of big data

The use of big data in health care, in fact, can help at different levels by (1) increasing early diagnosis and effectiveness and quality of management with trends to detect early signs of disease so intervention can be done; (2) looking for a strategy to prevent disease and identification of risk factors ;(3)improvement of pharmacovigilance and patient safety through the ability of access of health record by the client from the comfort of their home;(4) predict the outcomes;(6)finally big data can help identify and prompt intervene on high risk and high-cost patient and set up effective ways to manage these data to facilitate enabling detection of response to treatment and create a health care plan to meet every individual (Shilo,2020). Another benefit is that patients can talk to their providers via the patient portal, and you do not have to pay for that.

Risk of big data

One potential challenge for using EHRs is the interoperability between clinical systems. A full picture of a patient’s data is seen when various systems can communicate effectively. Diaz et al., (2023) note that big data is fueling the economy and how it interacts with various systems. My organization challenges the EHR implementation through planning, strong leadership, and involving all the stakeholders in the EHRs process.

Another potential challenge is data security, big data contains personal information and health history. Therefore, health system data should be secure and highly protected from data breaches such as hacking, cyberthief, or data fishing that can lead to data being stolen and sold to others.

Strategy to Mitigate the Risk

One strategy to mitigate the risk in data security is through using cloud technology in data storage. Cloud storage is often highly protected by healthcare organizations and cloud service providers (Wang et al.,2018). This gives you the benefit of data security since there are different data security layers that data theft must pass through to reach the data. 

Conclusion

In conclusion, technological progress is changing our lives in every industry including health care. Big data analytics promises to improve the healthcare industry by helping program business and operational systems and improving research to improve our lives. Big data is a priority for us as healthcare professionals because it aims to give our clients the best care by capturing the necessary data to improve the system.

References

Diaz, J. Marcolis, C. Washburn, R. (2023) How modern data platform fuels success How the Modern Data Platform Fuels Success | CDWLinks to an external site.

Healthcare.gov(n.d) the patient protection and affordable care act Patient Protection and Affordable Care Act – Glossary | HealthCare.govLinks to an external site.

McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge(5th ed.). Burlington, MA: Jones & Bartlett Learning.

Public Health (2021) The advantages and disadvantages of electronic health record Advantages and Disadvantages of Electronic Health Records – Public HealthLinks to an external site.

Segal, T. (2022) what is big data? Definition of how it works and uses What Is Big Data? Definition, How It Works, and Uses (investopedia.com)Links to an external site.

Shilo S, Rossman H, Segal E. Axes of a revolution: challenges and promises of big data in healthcare. Nat Med. 2020 Jan;26(1):29-38. doi: 10.1038/s41591-019-0727-5. Epub 2020 Jan 13. PMID: 31932803.

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

A Sample Answer 3 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

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 

A Sample Answer 4 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

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. 

 

 

Reference 

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.2015.12.019Links to an external site. 

A Sample Answer 5 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

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. 

References 

McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning. 

Reid, L., Maeder, A., Button, D., Breaden, K., & Brommeyer, M. (2021). Defining nursing informatics: A narrative review. Studies in Health Technology and Informatics, 284, 108–112. https://doi.org/10.3233/SHTI210680 

A Sample Answer 6 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Just to add on what you have put across on the challenges: Considering the millions of data put out by every individual daily, it might be complicated to develop an appropriate way to properly understand how this information can help the nurses (Thew,2016). Data analytics is crucial in understanding big data, but most nursing leaders do not have the skills to properly analyze the information and come up with conclusive results that can help the nurses. Additionally, the nursing leaders do not have information that reflects on their nurses and patients (Thew,2016). This means they cannot understand whether the nurses are committed to their work and whether the patients will follow the instructions given to them. For most nursing leaders, this is a time and labor-intensive process when manually analyzing the information on their patients and nurses. 

Reference: 

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 

A Sample Answer 7 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Thanks for sharing on the topic of big data and how it affects the different aspects of healthcare. Big data impacts direct patient care as well as long term patient outcomes which is why it is vital that we understand what it is and why we use it (Duquesne University, 2022).  

Electronic Health Records are the primary way that we see big data used in healthcare which makes patient data more accessible and easier to share with others (Duquesne University, 2022). Electronic health record data can be generated, stored, cross referenced, and analyzed to yield valuable results which makes it possible for patients to receive consistent and reliable care at multiple facilities (Duquesne University, 2022). This data may also be used to make informed decision on the direction of a patients care in the future (Duquesne University, 2022). Some people have even said that machine learning algorithms may be used in the future to consider and evaluate more details of a patients EHR than any physician would be able to which may be able to detect patient risks and diseases earlier on resulting in better patient care (Duquesne University, 2022). Although this seems far-fetched, I do believe that there are many benefits to having patient records contained in one area that allows easy access for multiple providers across the care spectrum.  

Nurses must be involved in the data collection and assessment process in order to care for their patients well (American Nurse, 2021). Nurses are a key aspect of patients receiving quality and safe care. At the same time, we cannot ensure that these big data programs are working efficiently and safely without nurses being involved in the process. Nurses must constantly be evaluating what can be improved in the big data process in order to ensure that big data is continually effective and informative to patient care.  

Thanks for sharing on this topic!  

References  

American Nurse. (2021, March 12). Using data in nursing practice. https://www.myamericannurse.com/using-data-nursing-practice/ 

Duquesne University. (2022, June 2). What Is Big Data in Healthcare? Duquesne University School of Nursing. https://onlinenursing.duq.edu/blog/what-is-big-data-in-healthcare/ 

A Sample Answer 8 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

 Data is crucial in guiding critical decision-making processes in healthcare settings. Therefore, healthcare professionals use different strategies to collect and retrieve data. The importance of this information is critical to understanding and treatment methods. Besides, the data can be misused when accessed by wrong people (Mehta & Pandit, 2018). Thus, healthcare facilities have developed mechanisms that safeguard their data and any other health-related information. Technologies have transformed data gathering, analysis, and protection. At the same time, technology has also exposed data to various risks such as unauthorized access. Healthcare professionals are now compelled to work with informational technology experts to protect their data from unauthorized access (Dash et al., 2019). Nurses having a voice and being at the table to use good data for improved outcomes is key to making effective positive changes. Similarly, these healthcare workers are responsible for any wrong utilization of data. Some challenges of using big data are the need for data standardization and the failure of how data can interact. 

 

References 

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6(1), 1-25. 

Mehta, N., & Pandit, A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International journal of medical informatics, 114, 57-65. https://doi.org/10.1016/j.ijmedinf.2018.03.013Links to an external site. 

A Sample Answer 9 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

After the new Health Information Technology Act (HITECH) of 2009 went into effect, the electronic health record (EHR) became the largest application of big data in the healthcare industry. The HITECH act in the U.S. have been the reason why 80% of acute care hospitals that uses the EHR are certified (Ross, 2014, p. 97). The one benefit of the EHR program is the ability of the platform to absorb large amounts of data such as a patient demographics, medical history, allergies and laboratories values. This makes it easy for clinicians to improve patient quality of care by tracking progress and identifying potential problems early in their medical history. If a clinician attempts to order norco for pain, the EHR will display a best practice advisory (BPA) alert and flag the patient codeine allergy; this will redirect the clinician to considering another pain medication that would not put the patient at risk for an adverse drug reaction. Adverse drug events are estimated to occur in 30% or more of hospital stays and cost billions of dollars (Ross, 2014, p. 98). This is a great benefit big data have provided in the development of the EHR program. 

            The major challenge with EHR is keeping patient health information safe by preventing access to unauthorized individuals. At my facility, the IT department have assigned employee education modules on cyber-attacks. For example, an employee received an email from an IT associate about a Hospital EHR update and upon request, gave their login name and password. Shortly after the information was given, the cyber attacker was able to login into the EHR, steal approximately 50 patient’s information and changed all the employee direct deposit bank accounts to an off shore financial institution in the Caribbean. Luckily, the IT department was notified immediately and was able to prevent the massive transfer of money, but was not successful in protecting the patient’s healthcare data. After this sentinel event, all employees are quarterly required to take education modules on the best practices to mitigate the challenges of a cyber-attack.

It is important to never give your password out and to always encrypt your emails. The new tiger connect system at my facility have features to encrypt your passwords and email before sending a message. In order to hold employees accountable, leadership have started to audit employees to ensure their following the safety protocols. Sometimes fake emails will be sent out to employees to ensure everybody understand there is never a right time to give their login information and the IT associates will never ask for this information.  At the hospital, there are policies and procedures that serve to maintain patient privacy and confidentiality; for example, employees must not share their ID with anyone, always log off when leaving a computer and only use their own ID to access patient digital records (Jamshed, 2015, p. 75). We use a new device called WaveID, where your password automatically log in after waving your employee ID over a keyboard magnet. It is a convenient and easy for an individual to steal your badge, which is why it is important to follow the policy in place and mitigate the risk of another cyber-attack. 

 References: 

Jamshed, N., Ozair, F., Sharma, A., & Aggarwal, P. (2015). Ethical issues in electronic health records: A general overview. Perspectives in Clinical Research, 6(2), 73–76. https://doi.org/10.4103/2229-3485.153997Links to an external site. 

Ross, M. K., Wei, W., & Ohno-Machado, L. (2014). “Big data” and the electronic health record. Yearbook of Medical Informatics, 23(01), 97–104. https://doi.org/10.15265/iy-2014-0003Links to an external site. 

Kruse, C. S., Smith, B., Vanderlinden, H., & Nealand, A. (2017). Security techniques for the electronic health records. Journal of Medical Systems, 41(8), 1–10. https://doi.org/10.1007/s10916-017-0778-4Links to an external site. 

A Sample Answer 10 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Thanks for your comments here.  With all the advanced technology available, we put our systems at high risk for the possibility of stolen information from hackers. Maintenance of a system is very important. It is difficult to know what extent PHI is protected from hackers. The HIPPA rule requires specific requirements and rules to safeguard electronic protected health information to ensure its confidentiality, integrity, and security. A few safety measures built into electronic health record (EHR) systems to protect the medical record include: “Access control” tools like passwords and PIN numbers, to limit access to patient information to authorized individuals, like the patient’s doctors or nurses and “Encrypting” stored information. This means health information cannot be read or understood except by someone who can “decrypt” it, using a special “key” made available only to authorized individuals. How is your workplace protecting data? Thanks in advance, Dr. Howe 

I appreciated your outlook on the discussion this week. You highlighted some meaningful use for EMRs on quality and safety. An opportunity for nurses to add to the topic of adverse drug events could be in their partnership with the vendors of EMR systems to incorporate narrative-style documentation in addition to flow sheet data from adverse events (Glassman, 2018). The general theme of big data benefits seems centered around involvement and having the data work for a greater purpose. I can relate to the incident you describe at your workplace facility, and I empathize as I have had a similar experience in the healthcare organization I use. Within our local community, there is a monopoly and lack of healthcare access and competition. With only one healthcare facility within a 50-mile radius for a higher level of care opinion, it recently fell victim to a mass cyber-attack. With a recent hack in security, I have witnessed the fallout in trust in the patient relationship with the organization, employees, and providers. A heightened level of disruption has intimately affected numerous community members and me. Getting a letter for free identity theft monitoring was quite unsettling as the solution proposed by the organization.

As a patient within a healthcare system and an employee, I felt angry and unsettled; I can only imagine those members who lack an understanding of cyber security. Building a culture around the responsibility of cybersecurity has to stem from education and collaboration efforts like the ones you describe and then some. According to Niki et al. (2022), “cybersecurity in healthcare is not a duty or an obligation but an act of responsibility. When patients and families entrust their lives to the health system and its professionals, their complete commitment to excellence in delivery is a basic expectation” (para 1). With this tremendous fallout effect, the lack of competition in rural hospitals and department infrastructure is desperate for innovative leadership (Austin B. Frakt, 2019). I think cybersecurity and better meaningful use would enhance patient safety and the patient and staff’s confidence in assuring their information is secure and used for its intended value. 

 

References 

Austin B. Frakt, P. D. (2019, June 18). The rural hospital problem. JAMA. Retrieved December 28, 2022, from https://jamanetwork.com/journals/jama/article-abstract/2735806 

Glassman, K. S. (2017). Using data in nursing practice Links to an external site. 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. 

Niki, B., Saira, G., Arvind, S., & Mike, D. (2022). Cyber-attacks are a permanent and substantial threat to health systems: Education must reflect that. DIGITAL HEALTH. https://doi.org/10.1177/20552076221104665Links to an external site. 

A Sample Answer 11 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Hi Victavian. Thank you for your insights in this week’s post. When you mentioned your facility having a security breach of its EHR, it brought back memories of my hospital corporation having its breach years ago. We also have to have mandatory education competencies completed regarding cyber security and the risks of phishing emails. Unfortunately, this happened at your facility, but it seems everyone responded quickly to help mitigate the adverse outcomes. Negi and Bhatt (2022) stated that EHR systems must follow the CIA triad of confidentiality (not disclosed to the public), integrity (only authorized people can access the data), and availability (must be accessible whenever needed) (p. 38). We must be diligent not to give hackers any wiggle room to cause a breach of such vital information. 

Kruse et al. (2017) report that HIPAA outlines three safeguards for protecting patients’ personal information. Technical safeguards limit access to information to only authorized people through practices like encryption. Physical safeguards include access badges that only work in locations you need to be to do your job. Administrative safeguards include policies, procedures, and audits that routinely ensure security (p. 8). Everyone needs to be on the same page that while the EHR is a commodity in the hospital, it must be respected and protected. 

References:  

Kruse, C. S., Smith, B., Vanderlinden, H., & Nealand, A. (2017). Security Techniques for the Electronic Health Records. Journal of Medical Systems, 41(8), p. 1-10. DOI 10.1007/s10916-017-0778-4 

Negi, L., & Bhatt, S. (2022, July). A Review on security schemes for Electronic Health Records [Conference session]. 2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT), Sonepat, India. DOI 10.1109/CCiCT56684.2022.00019 

Hi Victavian. I agree with you that the expanded use of electronic health records by healthcare organizations necessitates the continuous acquisition of knowledge and the development of relevant skills for maintaining the integrity and quality of protected health information. As an opportunity for integrating big data with clinical systems and procedures, the continued utilization of EHR by registered nurses in healthcare settings necessitates work-integrated learning to mitigate risks of regulatory sanctions and operational disruptions (McGonigle & Mastrian, 2022). Through work-integrated learning, registered nurses acquire relevant knowledge and develop skills for preventing unauthorized access to digital patient records using strategies like creating strong passwords, avoiding sharing access credentials, and maintaining the physical security of mobile devices. With nursing informatics competencies, registered nurses should recognize and mitigate the risk of cyberattacks as they continue to utilize EHR in healthcare organizations to prevent the manipulation and loss of patient data. The risk of unauthorized access to patient-centered data is attributed to the failure of registered nurses to comply with organizational policies and deficient knowledge regarding emerging information security threats (Reid et al., 2021). Work-integrated learning would help nursing informaticists and other registered nurses in healthcare organizations to audit staff compliance with information security protocols and strengthen existing policies to maintain the confidentiality of digital patient records. 

References 

McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning. 

Reid, L., Maeder, A., Button, D., Breaden, K., & Brommeyer, M. (2021). Defining nursing informatics: A narrative review. Studies in Health Technology and Informatics, 284, 108–112. https://doi.org/10.3233/SHTI210680 

Good insight on this week’s discussion post. Thank you for sharing on using big data in healthcare. Nurses and other healthcare workers interact with big data daily in the care of their patients. I agree that these range from electronic data records to online charting systems and other online documentation. Therefore, big data helps keep important information or documentation of the patients. They make work easier for healthcare workers and help them save time, allowing them to spend more quality time on the care of their patients. However, the use of big data in healthcare can also be disadvantageous to patients, healthcare workers, and the healthcare system due to breaches in privacy. Most of the private data on patients’ information, like details on health insurance, should always be kept confidential by healthcare workers.
On the contrary, this information can be hacked and private information stolen. Therefore, data analysts and nurse informaticists must ensure that the big data are well managed and protected from data piracy or hacking. While the lack of standardization makes it hard for changes to be implemented effectively, as you said, there is a solution to this problem: having good data, which is the key to these effective changes (Thew, 2016).
In order to do this, proper documentation is essential, and this is where the role of a nurse is the most important. Nurses are the ones who do most of the electronic health record documentation, which includes plans of care, physiological parameters, assessments, interventions, and progress evaluations which are critical to care integration and patient safety (Glassman, 2017). When the data is complete and concise, it will be easier for the analysts to organize the said data, which will contribute to improved patient care 

References:

Glassman, K. (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. 

Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs. Healthleaders.
https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs?page=0,1 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Thanks for the informative post. The electronic health record (EHR) system is a huge win for healthcare . Not only has it saved many hospitals money like you mentioned, but it has also assisted in providing better quality health care to patients which is the most important job of nurses. It has definitely made our jobs easier. It helps to have all or most of the information needed in one place, for easy access and fast delivery of care to patients. This is also dangerous in case this information gets hacked.  

Confidentiality and privacy is an issue like you mentioned. In the hospital where I work, the information technology (IT) team and  system warns us about corrupt emails and does training sessions by sending such emails to see how we react to them. We are warned not to click on any unknown links and be careful of emails coming from outside of the hospital. Also, not sharing ones user identification and password is one of the safest things to do.(Jamshed, 2015, p. 75). 

In addition, cyber-security is another great way to help with this confidentiality problem. (Niki et al., 2022)  EHR is one of the best contributions to nursing in my opinion in recent times. I hope it continues to get updated and more innovative contributions are made towards this in the future.  

 

References 

Jamshed, N., Ozair, F., Sharma, A., & Aggarwal, P. (2015). Ethical issues in electronic health records: A general overview. Perspectives in Clinical Research, 6(2), 73–76. https://doi.org/10.4103/2229-3485.153997 

Niki, B., Saira, G., Arvind, S., & Mike, D. (2022). Cyber-attacks are a permanent and substantial threat to health systems: Education must reflect that. DIGITAL HEALTH. https://doi.org/10.1177/20552076221104665 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

 It is true that the EHR program can absorb large amounts of data such as a patient demographics, medical history, allergies and laboratories values. The platform store big data that can be used in making critical decisions. The EHR program has transformed clinical and patient experiences. Healthcare professionals can access health information at ease. Since the HITECH act was effected in the U.S healthcare organizations have been on the run to introduce technology in their service delivery. The EHR program is among technologies that acute care hospitals are using to improve positive patient outcomes (Elhoseny et al., 2018). However, handling big data has been a challenge to other healthcare organization. Technological advancements have resulted to risks in handling big data. Unfortunately, some healthcare facilities have lost part of their data to wrong hands. Unauthorized access of this data is dangerous to patients and healthcare facilities. Cyber-attacks are also common when using technology (Nair et al., 2018). Healthcare organizations have developed security mechanisms to protect their data and technological vendors such as electronic health records. 

References 

Elhoseny, M., Abdelaziz, A., Salama, A. S., Riad, A. M., Muhammad, K., & Sangaiah, A. K. (2018). A hybrid model of internet of things and cloud computing to manage big data in health services applications. Future Generation Computer Systems, 86, 1383-1394. https://doi.org/10.1016/j.future.2018.03.005Links to an external site. 

Nair, L. R., Shetty, S. D., & Shetty, S. D. (2018). Applying spark based machine learning model on streaming big data for health status prediction. Computers & Electrical Engineering, 65, 393-399. https://doi.org/10.1016/j.compeleceng.2017.03.009Links to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Thanks for sharing on this topic of big data. There are many pros and cons of EHRs in teh situation of patient care settings. One of the biggest topics of a pro of EHRs is the improved quality of care that is provided to patients with its use (PrognoCIS, 2022). EHRs provide a better analysis of the patients condition and combines all medical interventions and care to give the best support to patients (PrognoCIS, 2022). Although these systems are expensive, they are vital to ensuring that patients receive comprehensive care.  

I agree with you that a major challenge that is faced with EHR is the the risk for information to be given to others or not kept safe. This is something that will always be a concern and a weak point when considering patient EHRs. Education is essential to ensuring that nursing and hospital staff understand the ways to mitigate risks of an attack on systems.  

Thank you for sharing on this topic!  

References  

PrognoCIS. (2022, April 21). The Pros and Cons of Electric Medical Record. prognocis.com. https://prognocis.com/pros-and-cons-of-ehr/ 

I appreciate the level of detail in your post. Sometimes I wonder how chaotic things will be if one day we have to manage patient data in workplace without the help of an EHR. The EHR is a device that improves outcomes for patients and clinicians by making the management and exchange of health information possible in a timely manner (Hoover, 2017). However, as you mentioned, the security of patient data is an issue that detracts from the benefits of using an EHR. An additional strategy I would recommend to secure patient data is using an antisoftwareprogram. Antisoftwares have a regularly updated virus database that enable them identify and eliminate malware introduced by malicious actors to obtain patient information (Kruse et al., 2017). Installing a good antisoftware program will ensure that most cyber criminals are unable to access the data. 

 

References  

Hoover, R. (2017). Benefits of using an electronic health record.Nursing2020 Critical Care, 12(1), 9-10.https://doi.org/10.1097/01.CCN.0000508631.93151.8d 

Kruse, C. S., Smith, B., Vanderlinden, H., & Nealand, A. (2017).Security techniques for the electronic health records.Journal of Medical Systems, 41(8), 1-9.https://link.springer.com/article/10.1007/s10916-017-0778-4 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

According to Maciera et al. (2017), nurses form the largest healthcare industry category. In the United States, about 2.8 million nurses are actively working with 61 percent in the hospital setting. Nurses are responsible for overall patient care 24 hours a day. On top of this care, they are required to document all their intervention, medications given, daily living activities, assessments, and many other things. 

     With the introduction of EHR, we can now collect and track a large amount of information and data. At the same time, it requires nurses to spend a long time in front of the computer screen, taking them away from the bedside, disrupting the nurse-patient caring encounter (McGonigle & Mastrian, 2017). Technology has its benefits and also downfalls. 

    The most significant benefit of EHR is its ability to quickly collect and store a large amount of information and data, which, in return, are readily accessible when needed. In my experience, it is especially beneficial in an emergency. When a patient comes in and is unable to communicate due to his or her condition, we can access all of the health and personal information we need to provide proper care. We can also contact the family for additional information. As we collect current data and assessments, the system will automatically upload them to the file. Any specialty involved in this patient’s care can remotely access this data and provide feedback or consult. This process dramatically improves patient care and outcomes. Real-time documentation is not optional anymore. With my facility being a level one trauma center, there are specific requirements to maintain this certification. Real-time documentation and feedback are among many elements (Nielsen, Peschel, & Burgess, 2014). 

    This particular example does not have many downfalls in my onion. The only problem with retaining and accessing the data and history is when the patient accesses a facility that is not part of our network and using a different EHR. The same scenario applies to patients whose first point of access was a facility not supported by our EPIC charting system. We are the only pediatric level one trauma center in the state, and therefore we receive many transferred patients from many other facilities with no access to their system. Physicians have to go through the paper chart to review the data, history, and assessment, which can be challenging and time-consuming with no standard documentation. Consulting specialties are unable to see this data in real-time.  

    To mitigate this complication, I propose creating a cloud where all the data could be uploaded by the sending facility and converted to receiving facility systems where they can access and review them in real-time. There is a system in place for imaging already and managed by Arkansas Trauma Repository (ATR). Sending facility uploads imagining to the cloud, and ATR stores it until requested by the receiving facility. All hospitals use the same system, and images are pushed over to a proper facility by ATR. It is a safe and secure system. We should be able to use a similar system for other necessary data essential for patient flow between hospitals. That would assure flowless and safe patient care transfer between facilities and providers. 

 References 

Nielsen, G., Peschel, L., & Burgess, A. (2014). Essential Documentation Elements: Quality Tool for the Emergency Department Nurse. Advanced Emergency Nursing Journal, 36(2), 199–205. Retrieved from https://web-a-ebscohostcom.ezp.waldenulibrary.org/ehost/detail
/detail?vid=10&sid=9603f15e-c0b4-4e6c-8bd5-341b2585f28b%40sdc-v-sessmgr01
&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=107854235&db=rzh 

Maciera, T. G. R., Smith, M. B., Davis, N., Yao, Y., Wikie, D. J., Lopez, K. D., & Keenan, G. (20017). Evidence of progress in making nursing pracrice visible using standardized nursing data: A systematic review. AMIA Annual Symposium Proceedings, 2017, 1205-1214. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977718/ 

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

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Hi Fatmata. Thank you for your post. I also work for a hospital corporation that utilizes an EHR system not used by other facilities in the Phoenix valley where I work. My facility also receives transferred patients, and it can be a hassle to ensure we receive copies of the paper chart or printouts of the computer chart from the system they use. Unit clerks must scan these papers into my facility’s new electronic record. There are many steps involved where nurses or other team members could lose information. I liked your proposal to use cloud storage for real-time access to health information. Shaikh discusses how “The demand is to make (the records) available on the cloud with the sufficient security measures that are transparent to the user and manageable by the cloud provider” (p. 1) and suggests that the use of blockchain technology would be beneficial to accomplish this. 

The healthcare system is one of the biggest data generators, and this data needs appropriate management. Nurse leaders are essential players in this game and can be champions for its use. Big data can potentially change healthcare delivery in America. The facility culture needs to embrace the data, implement competencies for all staff in the organization, and provide a structured way to support the use of the data (Thew, 2016). 

References: 

Shaikh, R. (2022, February). Blockchain Based Cloud Storage of Patients Health Records [Conference session]. 2022 IEEE Delhi Section Conference (DELCON), New Delhi, India. 10.1109/DELCON54057.2022.9753574 

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?page=0%2C1Links to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Technology is amazing and has dramatically improved many aspects of healthcare and life. Looking for patients’ information takes time away from their care and delays life-sustaining treatment. “When the system goes down, it’s like the apocalypse. Backup paper records must be kept, and data inputted later when the system is back up and running” (Androus, 2021). As nurses we do not like to lose valid time as it pertains to providing patient care as so much is already required of us. 

The use of EHR has done us good. “However, when not used appropriately, EHRs can reduce nurses’ use of their critical-thinking skills, increase reliance on workarounds to bypass forms, and lead to errors and lost documentation” (Pagulayan, 2018). When technology fails, it places stress in the workforce. Having all systems connected and uploaded to a cloud is a good idea. A synchronization would save some time. I would not be surprised if, years from now, that does not happen. 

 

References 

Androus, A. (2021, June 2). What Are Some Pros and Cons of Using Electronic Charting (EMR)? || RegisteredNursing.org. Www.registerednursing.org. https://www.registerednursing.org/articles/pros-cons-using-electronic-charting/ 

Pagulayan, J. (2018, September 27). Nurse documentation and the electronic health record – American Nurse. American Nurse. https://www.myamericannurse.com/documentation-electronic-health-record/ 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

The introduction of electronic health records (EHR) has allowed for the quick collection and storage of large amounts of information and data, which can be accessed when needed by providers and patients “The utilization of cloud storage enables users to gain access to their health report from a remote location.” (Gupta, et al, 2022). This is especially beneficial in emergency situations, where patients may be unable to communicate and doctors need to access their health and personal information to provide proper care. However, the use of EHR has also taken nurses away from the bedside and disrupted the nurse-patient caring encounter. In addition, when patients are transferred between facilities with different EHR systems, it can be difficult for doctors to access and review the necessary data and history. Your proposal of a cloud where data can be uploaded by the sending facility and converted for use by the receiving facility is a great idea! The information that I found on the Trauma Image Repository after reading your post was really interesting and would solve a lot of issues with continuity of care and also improve security “Paper records are easily lost or stolen, and could be completely destroyed by a flood, fire or another natural disaster. The lack of security surrounding these documents was a significant risk to patient safety.” (BIS, 2022).  

References 

Gupta, S., Sharma, H.K., Kapoor, M. (2022). Artificial Intelligence -Based Cloud Storage for Accessing and Predication. In: Blockchain for Secure 

Healthcare Using Internet of Medical Things (IoMT) . Springer, Cham. https://doi.org/10.1007/978-3-031-18896-1_13 

Sytems, B. I., & Nbaldwin. (2020, July 9). Top 5 advantages of cloud computing in Healthcare. Behavioral Information Systems, LLC. Retrieved 

December 30, 2022, from https://behavioralis.org/top-5-advantages-of-cloud-computing-in-healthcare/ 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Very informative post. Of the challenges ,another potential challenge is the issue of privacy and security. With so much sensitive data being collected and stored, there is a heightened risk of unauthorized access and disclosure. Another challenge posed by big data is the need for accurate and complete data sets (Pastorino et al., 2019). If data is missing or inaccurate, it can lead to incorrect conclusions being drawn about a patient’s condition or treatment options. Finally, big data can also be difficult to manage and process due to its sheer size and complexity. Thew (2016) states that “dealing with big data can understandably be challenging for chief nurse executives because of the large complex data sets they have to synthesize to come up with brilliant conclusions about how to run the organization.” Without the proper tools and infrastructure in place, big data can quickly become overwhelming. While big data has the potential to transform healthcare for the better, it is important to be aware of these challenges so that they can be addressed. 

References 

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/ckz168Links to an external site. 

Thew, J. (2016, April 19). Big data means big potential, challenges for nurse Execs. HealthLeaders. https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execsLinks to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

I enjoyed reading your post; rapid improvements in technology, big data, and the general rise in data-intensive operations pose several challenges for the healthcare industry in terms of storage, analysis, and financial performance. Due to the necessity to store various data types and access them for decision-making, healthcare firms are looking for better choices outside traditional storage servers and processes. Data storage includes data heterogeneity, data protection, data analysis, and infrastructures for data storage. Small and medium-sized enterprises (SMEs) make up the majority of hospitals, which means they regularly run into financial and data storage issues. These more minor facilities need more infrastructures to store big data. (Wang et al.,2018).) Although it is more costly not to implement big data because the age of big data is here, ignoring its benefits is to run the risk of missed opportunities. Organizations using big data are quickly reaping the rewards, as a survey of 2,022 managers worldwide indicated recently. Seventy-one percent of respondents agreed that organizations using big data will gain a “huge competitive advantage.” These managers also saw the need for big data: Fifty-eight percent responded that they never, rarely, or only sometimes have enough data to make critical business decisions. Furthermore, they’ve witnessed the benefits: 67 percent agreed that big data helped their organization innovate. 

Big data is a valuable tool for healthcare advancement. The challenge is to recognize the existence of these large volumes of information and to use them smartly and safely to multiples ends within healthcare is imperative, especially within small hospitals.  

 

 References: 

Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think (1st ed.). Eamon Dolan/Houghton Mifflin Harcourt. 

McGonigle, D., & Mastrian, K. G. (2021). Nursing informatics and the foundation of knowledge (5th ed.), Jones & 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 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Big data refers to a large and complex data set that involves multiple sets of integrated data sources that are combined to form one large set of data (HealthLeaders, n.d.). This data can easily become overwhelming and overpowering which is one reason why nurses and nurse leaders are needed when it comes to evaluating this data (HealthLeaders, n.d.). Big data, while overwhelming, also has the ability to change healthcare for the better (HealthLeaders, n.d.).  

Data is used in almost every part of the nursing practice. Nurses are constantly inputting information about their patients into EHRs. That information is compiling every day to create a big data group on every patient seen. The data is then sorted into like groups which allows the healthcare team to look over the data and decide how to best care for the patient (Glassman, n.d.). This is often seen as a pro of big data usage. Without this feature it could be much more time consuming and tedious for nurses to search and find information for each patient. Data could be easily missed because it wasn’t placed in the correct area without the use of EHRs. The ability for providers to look at a patient’s background and current complaints in the same place provides the opportunity for synthesized and well rounded patient care while ensuring that all the patient’s needs are met.  

A challenge often faced with big data is the overwhelming amount of information that needs to be sorted in order to get substantial results (HealthLeaders, n.d.). While this data supports better decision making, reducing costs, and the development of healthcare, it can be overwhelming to sort through and is often sorted manually (Magdalena & Julita, 2022). The data is often not standardized which creates another barrier when attempting to sort through the data and create improvements for healthcare (HealthLeaders, n.d.). On top of this, it is impossible to include all parts of healthcare that would need to be involved in order to truly create an environment of better patient care (HealthLeaders, n.d.).  

While sorting through these large amounts of data can be overwhelming and challenging, there are strategies that healthcare workers and healthcare data analysts can use to make this task lighter. Data mining is the process of finding patterns and anomalies within large sets of data (Current Big Data Challenges in Hospitals and Healthcare, n.d.). When correctly used, data mining enables its users to combine information from multiple databased which can then be examined, analyzed, and used to plan and create more effective healthcare solutions which is the main goal of big data collection (Current Big Data Challenges in Hospitals and Healthcare, n.d.). Artificial Intelligence has also been used as it was created to mimic human intelligence without bias or preconceived notions (Current Big Data Challenges in Hospitals and Healthcare, n.d.). AI, like data mining, is able to find repetitions or anomalies in the mountains of data that big data can produce (Current Big Data Challenges in Hospitals and Healthcare, n.d.). It is able to analyze large amounts of data that humans cannot simply due to the size of data that is present (Current Big Data Challenges in Hospitals and Healthcare, n.d.). On top of these tools, skilled data analysts are required to sort through the large amount of data that will be present in order to present data that can be used for next steps (Current Big Data Challenges in Hospitals and Healthcare, n.d.). While this is no small task, and big data will continually be a time consuming part of healthcare, it is essential to use the tools and team members available to create programs that result in better patient care and better patient outcomes.  

References  

Current Big Data Challenges in Hospitals and Healthcare. (n.d.). Norwich University Online. https://online.norwich.edu/academic-programs/resources/data-challenges-in-healthcare 

Glassman, K. (n.d.). Using Data In Nursing Practice. myamericannurse.com. https://www.myamericannurse.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf 

HealthLeaders. (n.d.). Big Data Means Big Potential, Challenges for Nurse Execs. HealthLeaders Media. https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs 

Magdalena, & Julita. (2022, January 11). Key benefits and challenges of using Big Data in healthcare. MERIXSTUDIO. https://www.merixstudio.com/blog/big-data-in-healthcare/ 

In your post, you speak about going through huge amounts of data, which are potentially risky, especially when it comes to minimizing errors. One way to mitigate this challenge is to use data cleansing and validation techniques (Abouelmehdi et al., 2018). For example, data cleansing can involve identifying and removing duplicate records, while data validation can involve checking for missing values or inconsistencies. Other strategies that may be effective in mitigating the challenges of using big data in healthcare include data anonymization and security controls (Olatunji et al., 2022). Data anonymization involves stripping away identifying information from records, while security controls help to protect sensitive information from unauthorized access. When implemented correctly, these strategies can help to ensure that big data is used effectively and safely in healthcare. 

 

References 

Abouelmehdi, K., Beni-Hessane, A., & Khaloufi, H. (2018). Big healthcare data: Preserving security and privacy. Journal of Big Data, 5(1). https://doi.org/10.1186/s40537-017-0110-7Links to an external site. 

Olatunji, I. E., Rauch, J., Katzensteiner, M., & Khosla, M. (2022). A review of Anonymization for healthcare data. Big Data. https://doi.org/10.1089/big.2021.0169Links to an external site. 

I appreciated your outlook on the discussion this week .Electronic health records are the primary way we see big data used in healthcare and make patient data more accessible and easier to share with others. (Duquesne University, 2022). I agree with the introduction of Electronic Health Records; healthcare professionals can quickly create, collect, and store large amounts of information and data and can access them easily and quickly whenever providers and patients need it. However, here are some downfalls of using EHR when there have been instances where system failure occurred. When this happens, electronic operations are halted. Acc. to Larsen et al. (2019), “Electronic health record downtime is any period during which the EHR system is wholly or partially unavailable for use. 

References 

Duquesne University. (2022, June 2). What is Big Data in Healthcare? Duquesne University School of Nursing. 

https://onlinenursing.duq.edu/blog/what-is-big-data-in-healthcare/Links to an external site. 

Larsen, E., Hoffman, D., Rivera, C., Kleiner, B., Wernz, C., & Ratwani, R.M. (2019). Continuing Patient Care during Electronic Health Record Downtime. Applied Clinical Informatics, 10(3), 495-504. 

https://doi.org/10.1055/s-0039-1692678Links to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

The change from paper-based charts to electronic health records (EHR) was monumental in nursing. There was no longer a need to wait your turn for the chart you needed, no more missing pages, and no more writing cramps. But with all this data immediately available, there must be ways to manage it appropriately. I work for a vast, multi-state healthcare corporation, so I can easily see a patient encounter at any provider office, urgent care, or inpatient hospital under the company umbrella. Data mining helps make sense of all this information. Data mining is “the process of using software to sort through data to discover patterns and ascertain relationships” (McGonigle & Mastrian, 2022, p. 541). 

I work in behavioral health, where the patients are usually poor historians of their mental and physical illnesses. Having instant access to their history is essential to know how to predict their needs. Nurses can use data mining to investigate where the patient has presented in the health system. Frequently they have recently been to the emergency department before they come to the inpatient setting. Many of our patients are homeless and will “hospital hop,” so we can see if there is a pattern of going to facilities for housing and other basic needs. Suppose a patient has had verbal or physical aggression. In that case, they are flagged company-wide as a “threat alert,” so anyone who opens their chart will immediately see that they could potentially be dangerous. Arizona Medicaid, AHCCCS, will only pay for a determined amount of days in the behavioral health hospital setting per month and year. Seeing if and where the patient was recently hospitalized will determine whether their stay is covered. Glassman (2017) stated that “the quality of our nursing care and documentation informs the public and insurance companies through publicly reported measures” (p. 46) through the Centers for Medicare and Medicaid Services (CMS). 

A downfall to using big data in clinical systems is the financial implications. The EHR system my facility uses is Cerner. Most of our charting takes place on flowsheets, which makes the documentation go faster, as we can click boxes quickly. However, there are limited spaces to enter free text information that nurses can’t capture in a check box. The nurse must complete a narrative note if data doesn’t fit in the flowsheet. Depending on the party looking into the EHR, some can only see flowsheet data, and some can only see narrative notes. This practice creates a disjointed patient picture at times. If the company wanted to merge these capabilities, that would cost money. One of the most critical sections of the nurse’s shift documentation is the patient’s risk for suicide. In the past, the way we charted this was very clear, thorough, and easily understood. The creators of that section of the flowsheet decided they wanted more money for inclusion in the Cerner system, and Cerner determined they didn’t want to pay it. Now that section of the flowsheet is not as user-friendly as it once was. 

The use of cloud technology is a potential solution to help mitigate the financial burdens associated with big data. “The needs to store different formats of data and access to them for decision making have pushed healthcare organizations seeking better solutions other than traditional storage servers and processes” (Wang et al., 2018, p. 10). The cloud is usage-based and cheaper technology for information storage. Modi and Feldman (2022) suggest that corporations need to take inventory of big data technology’s cost vs. value relationship. “Current users of EHR systems focus on value in terms of improving workflows, and, as a result, better clinical outcomes…For patients, it could mean improved health, for providers, it could increase efficiency of care, and for the government it could correspond with improvements in population health through timely public health reporting” (p. 2). 

References: 

Glassman, K. S. (2017). Using data in nursing practice. American Nurse Today, 12(11), p. 45-47. https://www.myamericannurse.com/wp-content/uploads/2017/11/ant11-Data-1030.pdfLinks to an external site. 

McGonigle, D., & Mastrian, K. G. (2022). Nursing Informatics and the Foundation of Knowledge (5th edition). Jones & Bartlett Learning. 

Modi, S., & Feldman, S. S. (2022). The Value of Electronic Health Records Since the Health Information Technology for Economic and Clinical Health Act: Systematic Review. JIMR Medical Informatics, 10(9), p. 1-23. http://dx.doi.org/10.2196/37283Links to an external site. 

Wang, Y., Kung, L., & Byrd, T. A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting & Social Change, 126(1), p. 3-13. http://dx.doi.org/10.1016/j.techfore.2015.12.019Links to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Statistics make all aspects of the hospital better by comparing and improving on risk management issues.  In the healthcare industry various sources of big data include hospital records, medical records of patients, results of medical examinations, and devices that are part of Internet of things, (Dash et al, 2019).  There are various challenges associated with steps in handling big data which can only be surpassed by using high-end computing solutions for big data analysis, (Dash et al, 2019).  To provide solutions for improving public health, healthcare providers are required to be fully equipped with appropriate infrastructure to systematically generate and analyze big data (Dash et al, 2019). 

Reference 

Dash, S., Shakyawar, S.K., Sharma, M. et al.  (2019).  Big data in healthcare: management analysis and future prospects.  J Big Data 6, 54.  https://doi.org/10.1186/s40537-019-0217-0 

Big data is becoming increasingly more prevalent, and it affects the way nurses learn, practice, conduct research and develop policy (Topaz & Pruinelli, 2016, p. 165). Big data have open up multiple ways to store electric health record (EHR) and develop evidence-based risk assessments for helping nurses identify signs of suicidal ideation. Over 800,000 people die of suicide every year and it estimated that for each suicide, there may been greater than 20 other attempted suicides (Berrouihuet, 2019, p. 2). It is an unfortunate that Cerner is not willing to pay the extra amount to make it easier for nurses to document the suicide risk assessment. The EHR used at my facility is called EPIC, and the clinicians have a system to use in the combination of the risk assessment. It is a clinical decision-support system (CDSS) that help clinicians identify repeated suicidal attempt and suicide death within a period of time (Berrouiguet, 2019, p. 1). In addition, there a notepad feature on EPIC that allows 50 words to add if the patient mention an assessment option that is not listed. I would challenge CERNER on better suicide risk assessment and what can be done to ensure data is not missed because of healthcare charting limitations.   

References: 

Topaz, M., & Pruinelli, L. (2016). Big data and nursing: implications for the future. Studies in Health Technology and Informatics, 232, 165–171. https://doi.org/10.3233/978-1-61499-738-2-165Links to an external site. 

Berrouiguet, S., Billot, R., Larsen, M. E., Lopez-Castroman, J., Jaussent, I., Walter, M., Lenca, P., Baca-García, E., & Courtet, P. (2019). An approach for data mining of electronic health record data for suicide risk management: Database analysis for clinical decision support. JMIR Mental Health, 6(5), 1–12. https://doi.org/10.2196/mental.9766Links to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

          I agree with your post and your perception of Big data. Using cloud technologies is a potential approach to lessen the financial difficulties big data 

brings technologies. It would be very beneficial to use cloud technology for it simplifies connectivity and collaboration within an organization, which gives 

more employees access to relevant analytics and streamlines data sharing (Staff, 2022). In the medical field, it is elaborated that cloud computing is the 

practice of implementing remote servers accessed via the internet to store, manage and process healthcare-related data (Dhilawala, n.d). As the world 

enhances, Nursing informatics had created innovations for better clinical care and room for improvement to enhance patient care.  

References 

Dhilawala, A. (n.d). 9 Key Benefits of Cloud Computing in Healthcare 

https://www.galendata.com/9-benefits-cloud-computing-healthcare/Links to an external site. 

Staff, T. T. (2022). Big Data in the Cloud: Why Cloud Computing is the Answer to Your Big Data Initiatives. Thorn Technologies.  

https://thorntech.com/big-data-in-the-cloud/Links to an external site. 

 A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Healthcare facilities are seeing the importance of cloud abilities and their functionalities. While cloud computing can offer different service models while facilitating a competitive advantage Cloud computing in healthcare faces several challenges such as patient satisfaction, confidentiality security, data volume and investment value. IT Research is needed to abolish the weaknesses and strengthen to strengthen their strengths (Sultan, 2014). While examining and understanding the implications of cloud computing and contribute to theoretical advancement and real-world success of cloud applications.   Stakeholders and policymakers must understand how necessities may affect the decision to adopt cloud computing. The main challenges noted with cloud commuting is patient confidentiality. Therefore, proper guidelines and development environments are needed. An example of a cloud computing system is Collaborative care solution. This system aids in providing simplified access to health data and information. It also allows providers to connect with their patients and make the necessary medication adjustments to their medication regime as needed. For progress to be made in the cloud computing healthcare organizations must evaluate the benefits and risks of cloud computing service (Rajabion et al., 2019). 

References 

Rajabion, L., Shaltooki, A., Taghikhah, M., Ghasemi, A., & Badfar, A. (2019). Healthcare big data processing mechanisms: The role of cloud computing. International Journal of Information Management, 49, 271–289. https://doi.org/10.1016/j.ijinfomgt.2019.05.017Links to an external site. 

Sultan, N. (2014). Making use of cloud computing for healthcare provision: Opportunities and challenges. International Journal of Information Management, 34(2), 177–184. https://doi.org/10.1016/j.ijinfomgt.2013.12.011Links to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Understanding how big data can benefit or challenge nurses in the clinical system can be explained by knowing where big data is being utilized. As the infection control nurse, I used complex health information to collect data to report infections on a local, state, and national level. This can benefit healthcare organizations by seeing how many infections they have compared to other facilities at the local, state, and national levels, and create measurable goals to obtain throughout the year which can be supported by data obtained. Utilizing electronic medical records to obtain the data needed to report these findings is considered the data layer and is the first layer of big data in the clinical system and is used by all clinical staff (Wang et al., 2018). The one challenge that I have encountered with the infection control nurse is the time it takes to manually retrieve this data out of the EMR that is needed to report. According to Thew collecting, analyzing, and synthesizing data can be time-consuming and labor-intensive (2016). However, in the future when incorporating technological advancements into the healthcare system synthesis of data, the predictive analysis will help improve the time it takes to manage this type of data collection (Carroll, 2019). Overall, advancing technologies will help overcome the challenges of big data, and continue to improve the quality of healthcare with the data that is collected. 

References: 

Carroll, Whende. (2019). The synthesis of nursing knowledge and predictive analytics. Nursing 

 management. 50. 15-17. 10.1097/01.NUMA.0000553503.78274.f7. 

 

Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execs Links to an 

external site.. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-Links to an external site. 

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.. Technological 

Forecasting and Social Change, 126(1), 3–13.

Great post! I also agree that one of the positives about big data is the ability to bring all that information together to show us patterns or trends and compare that to other facilities; when it comes to treatments, it can help create targeted personalized treatment plans for patients (Wang et al., 2018). We should also be able to make advancements in population health, as more data comes in about different groups (Thew, 2016). I look forward to seeing when the synthesizing of this data will become more manageable so that we can reap the benefits of big data in a variety of fields within healthcare, such as patient care, infectious disease, and more.  

 

References: 

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

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 For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

I can only imagine the data analytical skills needed to crunch numbers on nosocomial infections that arise at your facility. The infection control nurse (ICN) uses the electric health record (EHR) to predict and prevent hospital acquired infections (HAI) by using data is the life line of their career. Having ICN organize mass data allows the hospital to develop efficient clinical workflows and facilitate decision-making processes to improve patient safety (Huang et al., 2021, p. 2369). During my department monthly meeting, a ICN reported a 10% rise of clostridium difficile (C-Diff) after going 6 months without any occurrences. The nurse leaders (NL) collaborated with the ICN and the hospital protocol changed from sending one stool sample for diarrhea after 3 occurrences to sending one stool sample after one occurrence. Evidence-based research showed a  31% reduction in the mean monthly number of C. Difficile test performed and a 56% reduction in C. difficile diagnoses after sending one stool sample after one occurrence (Lenz et al., 2020, p. 136). It is amazing to have ICN who specialize in implementing best practices using evidence-based research (EBR) and data from the EHR for halting the spread of bacteria and deliver top care to patients who have contracted C-diff. 

References 

Huang, F., Brouqui, P., & Boudjema, S. (2021). How does innovative technology impact nursing in infectious diseases and infection control? a scoping review. Nursing Open, 8(5), 2369–2384. https://doi.org/10.1002/nop2.863 

Lenz, A., Davis, G., Asmar, H., Nahapetian, A., Dingilian, J., & Nathan, R. V. (2020). Using a nurse-initiated bedside tool to decrease inappropriate testing for clostridioides difficile in hospital settings. Journal of Infection Prevention, 22(3), 136–139. https://doi.org/10.1177/1757177420976815 

I recognize the difficulty you describe in manually extracting data from the EMR, and I agree with you. There is a tremendous amount of pressure placed on nurses to produce and evaluate data. This is a vital and important job role, but it is difficult and time-consuming. Because of the extensive quantity of paperwork that is necessary, we are unable to spend as much time with our patients as we would want, which often results in a sense of being unsatisfied (Wang et al., 2018). The meaning of “big data” in the healthcare industry encompasses a wide range of concepts. The process of collecting, cleaning, processing, maintaining, and analyzing such enormous amounts of data is complex (Glassman, 2017). As a result, preventing burnout among medical professionals should be a top priority for many organizations. 

 

Reference 

Glassman, K. S. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45–47. Retrieved from https://www.myamericannurse.com/using-data-nursing-practice/Links to an external site. 

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, 3-13. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

 Thank you for the role you play in reporting critical data. Your role appreciated. 

                “The adoption of a Big Data approach would allow the implementation of personalized and precise medicine based on personalized information, delivered in real-time and tailored to individual patients”(Batko & Ślęzak, 2022). “In health care, big data is generated by various sources and analyzed to guide decision-making, improve patient outcomes, and decrease health care costs, among other things”(Coursera, 2022). 

                I agree that obtaining infection collection data can be challenging. It is essential that nurses not only document infection relation conditions accurately but also report to the infection control nurse. For instance, at my hospital, Covid19 cases were underreported, so nurses made it their duty always to call the infection control nurse and ask if they knew how many people were positive on the unit. Therefore, a system is needed that automatically ports all infection relation n data in one place for easy accessibility and retrievability to prevent tedious data searches. 

References 

Batko, K., & Ślęzak, A. (2022). The use of Big Data Analytics in healthcare. Journal of Big Data, 9(1). https://doi.org/10.1186/s40537-021-00553-4 

Coursera. (2022, October 20). Big Data in Health Care: What It Is, Benefits, and Jobs. Coursera. https://www.coursera.org/articles/big-data-in-healthcare

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Thank you for your post! One benefit could be that you as an infection control nurse can use complex health information to collect data on infections and report it on a local, state, and national level. This data can be useful for comparing the number of infections at different facilities and identifying areas for improvement. The use of electronic medical records (EMR) can help streamline the process, but it can still be challenging to retrieve as you stated “Real-time big data analytics is a key requirement in healthcare. The lag between data collection and processing has to be addressed.” (Raghupathi, W., Raghupathi, V, 2014). In the future predictive analysis could help overcome these challenges and improve the efficiency of data management. Big Data has the potential to greatly improve the quality of healthcare through better data collection and analysis “Big Data Analytics in healthcare allows to analyze large datasets from thousands of patients, identifying clusters and correlation between datasets, as well as developing predictive models using data mining techniques” (Batko, Slezak, 2022).  

References 

Batko, K., & Ślęzak, A. (2022). The use of Big Data Analytics in healthcare. Journal of big data, 9(1), 3. https://doi.org/10.1186/s40537-021-00553-Links to an external site. 

4 

Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and potential. Health information science and systems, 2, 3. 

https://doi.org/10.1186/2047-2501-2-3 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

 

The benefit of big data. 

Healthcare systems worldwide are experiencing enormous challenges. The challenge is to increase health outcomes while keeping costs under control. Big Data can assist healthcare professionals in achieving these aims in this situation in novel ways. Collecting individual data elements can reveal new approaches to improving health by providing insights into the causes and outcomes of disease, better drug targets, disease prediction, and prevention.(Dash et al., 2019; Pastorino et al., 2019; Wang et al., 2018) 

The fundamental advantage of Big Data in healthcare is that it provides analysis and relevant insights from data. These help to personalize, ensure consistency, and eliminate the absence of data relating to symptoms among patients. Data collection also improves forecasting capacity and the prevention of outbreaks. Doctors can observe that other patients have the same unrelated symptoms in different places with extensive data. After more inspection, the pattern shows everywhere, from a rare sickness to a spreading epidemic. The use of big data in healthcare can have a variety of effects. This includes expanding opportunities for disease prevention through identifying risk factors for disease and improving pharmacy vigilance and patient safety. The capacity to make more informed medical decisions based on information directly delivered to the patient and increase earlier diagnosing, according to the European Commission’s Study on Big Data in Public Health, Telemedicine, and Healthcare, is through the advancement of big data. 

The potential of big data in healthcare is enormous for the benefit of patients and the healthcare system, depending on our capacity to recognize patterns and transform massive amounts of data into knowledge that decision-makers can use for precision medicine. Big Data’s usage in healthcare already provides solutions for enhancing patient care and creating value for healthcare organizations in several scenarios. 

Medical records of patients, hospital records, test findings, and records of treatment-related equipment are some examples of significant data sources in the healthcare sector. Biomedical research is crucial since it produces some enormous data that is crucial to public healthcare provision. Effective administration and analysis are required to extract useful information from this data. Using high-end computing solutions for big data analysis is the only way to overcome some obstacles connected with each step of processing big data, notwithstanding its usefulness (Dash et al., 2019). The analysis of big data will automatically need advancement in the health sector; therefore, there is a higher possibility for health experts to figure out how to handle the problem using the recorded data concerning the patients treated in particular hospitals. Another way of looking at it is that the challenges experienced by big data by health experts will urge them to find a solution to those challenges to improve the services that big data offers. This kind of urge will help them become innovative. 

Challenges of big data in healthcare 

The use of Big Data in healthcare poses new ethical and legal challenges because of the personal nature of the information enclosed. Ethical and legal challenges include the risk of compromising privacy and personal autonomy and the effects on public demand for transparency, trust, and fairness while using Big Data. In addition, data heterogeneity, data protection, analytical flows in analyzing data, and the lack of appropriate infrastructures for data storage emerged as critical technical and infrastructural issues that might endanger Big-Data-driven healthcare.The majority of hospitals are small and medium-sized businesses (SMEs), and thus frequently experience financial and data storage problems. Healthcare businesses are confronting various issues related to storage, analysis, and financial performance as a result of the quick advancements in technology, big data, and the overall increase in data-intensive operations. Healthcare businesses are looking for better options outside conventional storage servers and processes due to the need to store various types of data and retrieve them for decision-making.(Wang et al.,2018). 

This approach requires, however, that all the relevant stakeholders collaborate and adapt the design and performance of their systems. In addition, they must build the technological infrastructure to house and converge the massive volume of healthcare data and invest in human capital to guide citizens into this new frontier of human health and well-being. 

Strategies to mitigate the challenges of Big data use. 

Implementing a quality improvement plan is one method that could help to alleviate the difficulties of employing big data in the healthcare context. Plans for quality improvement can make the environment for patients safer and help caregivers recognize any mistakes they might be making (HealthITAnalytics, 2018). By reinforcing particular rules, caregivers can lower medical errors. For example, when clinicians are completing risk scores for patients, each score should have specific criteria that allow more accurate scoring to be done. Decreasing charting errors can promote accurate data and overall more specific analysis of information. 

Big data and healthcare are essential for tackling the hospitalization risk for specific patients with chronic diseases. It can also help prevent deterioration. By drilling down into insights such as medication type, symptoms, and the frequency of medical visits, among many others, healthcare institutions can provide proper preventative care and, ultimately, reduce hospital admissions. Not only will this level of risk calculation result in reduced spending on in-house patient care, but it will also ensure that space and resources are available for those who need them most. This is a clearcut example of how analytics in healthcare can improve and save people’s lives. As a result, big data for healthcare can improve the quality of patient care while Making the organization more economically streamlined in every vital area. 

 

 

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/s40537-019-0217-0Links to an external site. 

 HealthITAnalytics.(2018). Using Big Data Analytics for Patient Safety and Hospital 

Acquired Conditions. https://healthitanalytics.com/features/using-big-data-analytics-for- patient-safety-hospital-acquired-conditions. 

 

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/ckz168Links to an external site. 

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.2015.12.019Links to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

          I empathize with your discussion post and explanation of the usage of Big Data problems in healthcare owing to the potential of breaching privacy. 

The most challenging task regarding this huge heap of data that can be organized and unorganized, is its management. Given the fact that big data is 

unmanageable using the traditional software, we need technically advanced applications and software that can utilize fast and cost-efficient high-end 

computational power for such tasks (Dash et al., 2019). Big Data is very huge that it is described as a term used to describe massive volumes of information 

created by the adoption of digital technologies that collect patients’ records and help in managing hospital performance, otherwise too large and complex 

for traditional technologies (Calzon, 2022). Access to the patient’s sensitive information can occasionally be accessed by all employees of the healthcare 

company, leaving the patient’s health information without security. Overall, understanding the Big Data problems will help healthcare professionals treat 

their patients better, which will lead to better patient outcomes. 

References 

Calzon, B. (2022). 21 Examples of Big Data In Healthcare With Powerful Analytics. BI Blog | Data Visualization & Analytics Blog | Datapine.  

https://www.datapine.com/blog/big-data-examples-in-healthcare/Links to an external site. 

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/s40537-019-0217-0Links to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Big data in healthcare describes the massive volumes of information created due to the adoption of digital technologies that collect patients’ records and information and assist in the management of hospitals’ performance. Patient portals, electronic health records (EHRs), wearable devices, and research studies as well as government health agencies are sources of big data in health care. Big data provides benefits as well as the challenges that it may contain (Abouelmehdi et al., 2018). One benefit of using big data in healthcare is increased efficiency in care delivery across all care settings, including acute care and emergency department as well as monitoring of patients with chronic conditions like diabetes and hypertension. For instance, nurse administrators and public health nurses can use big data to assess or evaluate the trend in patient admission rates and prevalence of certain public health concerns like the comorbidities. Through analysis of admission rates, the nurse administrators can determine the level of staff needed (Dash et al., 2019). For instance, predictive analytics allow nurse administrators to make effective decisions concerning most efficient staff level that can offer better care.   

Conversely, one challenge of big data in health care, especially in nursing, is data security. Recent incidents of increased cyber espionage and hacking implore healthcare administrators to develop better database security measures, including firewalls and anti-malware software to reduce the severity of these data theft events (Pastorino et al., 2019). Encryption of sensitive patient data, restriction and tracking of access to data and applications are some of the best strategies to mitigate security breaches that have the ability to compromise data security (Sivarajah et al., 2018). The implication is that providers and organizations should have policies and processes that lead to the implementation of these measures to prevent and reduce data security vulnerabilities in healthcare settings. 

References 

Abouelmehdi, K., Beni-Hessane, A., & Khaloufi, H. (2018). Big healthcare data: preserving 

security and privacy. Journal Of Big Data, 5(1), 1-18. 

https://doi.org/10.1186/s40537-017-0110-7 

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: 

management, analysis and future prospects. Journal of Big Data, 6(1), 1-25. https://doi.org/10.1186/s40537-019-0217-0 

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 

Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of Big Data 

challenges and analytical methods. Journal of Business Research, 70, 263-286. https://doi.org/10.1016/j.jbusres.2016.08.001 

Thanks for your comments here. One of the largest problems with healthcare information security has always been inappropriate use by authorized users.  How do HIPAA and the HITECH Act help to curb this problem? Thanks in advance, Dr. Howe 

I enjoyed reading your post. I agree that a challenge to overcome is data security. At my company in recent months, we had a security breach that shut our entire computer systems down for 3 days, and in other areas of the nation 2 weeks of electronic medical record blackout. Healthcare administrations need to work cohesively together with our IT department to maintain firewalls, and anti-malware to reduce data theft events (Pastorino et a., 2019). The other challenge we may face is utilizing cellular devices to forward patient information. There are certain CMS regulations and company policies that specify the use of personal devices and work devices. I have a work cell phone that I utilize that meets appropriate standards to prevent breaking any ethical or privacy laws. According to the university of Miami school of medicine, utilizing a cellular device can be a convenient and effective way of communication between colleagues but can quickly cause legal issues if not utilized appropriately or by the standards that have been set by CMS (2022). Overall, we can overcome all of these challenges together as we create policies and procedures that uphold standards to protect health information at all costs. 

References: 

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 

University of Miami Miller School of Medicine . (2022). Text Messaging and PHI. Uhealth Privacy Office. Retrieved June 14, 2022, from http://hippa.med.miami.edu/awareness/newsletter-articles/text-messaging-and-phiLinks to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

 One potential benefit of using big data as part of a clinical system is the ability to identify patterns and trends that may not be apparent with smaller datasets. This can allow for the development of more targeted and personalized treatment plans for patients, which can improve patient outcomes and reduce the overall cost of healthcare (Wang et al., 2018). For example, big data may help us learn about diseases affecting large groups of people, and suggest interventions so that we can make advances in population health by better managing disease and risk across the care continuum (Thew, 2016). 

One potential challenge or risk of using big data as part of a clinical system is the issue of data privacy and security. With the increasing amount of personal and sensitive data being collected and stored, there is a risk that this data could be accessed or misused by unauthorized parties (Abouelmehdi et al., 2018). One strategy to mitigate the challenges and risks of using big data in a clinical system is the implementation of strong security protocols, such as the use of encryption and secure access controls. Additionally, it is important to have clear policies and procedures in place for handling and protecting patient data, as well as educating staff on the importance of data privacy and security. It is also important to regularly review and update these policies and procedures to ensure that they are effective in protecting patient data. I see this in my hospital regularly, as staff is required to use two-factor authentication to log into hospital systems when not in the physical facility, and through e-learnings and other training, we are regularly reminded about the risks of phishing and how vulnerable our data is if we are not careful. 

 

References: 

Thew, J. (2016, April 19). Big data means big potential, challenges for nurse execsLinks to an external site. Links to an external site.. Retrieved from https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execsLinks to an external site. 

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.  

Abouelmehdi, K., Beni-Hessane, A. & Khaloufi, H. (2018) Big healthcare data: preserving security and privacy. J Big Data5, 1. https://doi.org/10.1186/s40537-017-0110-7 

I appreciate your comments to this discussion. Healthcare facilities are faced with remarkable challenges when it comes to security, privacy, confidentiality and so on, therefore, patients as well as all employees must know that such information should not be shared. Many organizations require employees to attest to corporate compliance yearly, and the descriptions of fraudulent actions are described along with the penalties for committing these acts. However, employees still engage in such behaviors. How can nursing administrators encourage corporate security compliance? Thanks, Dr. Howe 

Corporate security compliance can be encouraged in different ways. There should first be a clear security policy that includes consequences for not following the policy. This policy should be reviewed during orientation for new hires and yearly for all employees. There can be requirements for two-factor authentication, strong passwords, and only allowing access to the data you need for your job. Disciplinary action should be taken if security protocols are not met. My hospital does these items and I believe they are a strong basis for security in a facility. 

Big data has a remarkable ability to change the world. Its benefits must be considered as a function of managing its risks. Truly expert handling of big data brings the reward of being able to react to world-changing events, both big and small, at an unprecedented rate and scope. I agree, Organizations that manage big data should monitor security devices, servers, and application logs because healthcare providers are among the most targeted organizations regarding cybersecurity breaches. This sector accounts for nearly four out of the five industrial breaches. The costs of these security violations amounted to $4 billion in 2019. Encryption of sensitive patient data restriction and tracking of access to data and applications are some of the best strategies to mitigate security breaches that can compromise data security (Sivarajah et al., 2018). So, it is crucial to choose well-trusted vendors for big data in healthcare technology and implement encryption and other security measures. Securing all the connected devices on the hospital network is also essential. When necessary, strict access to some applications to predefined devices only and limit the authorized personnel. I agree that hospitals must educate their staff on data usage and how to access data safely. 

References 

Sivarajah, U., Kamal, M.M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of Big Data 

Abouelmedhi, K., Beni-Hessaane, A. & Khaloufi, H. (2018) Big healthcare data: preserving security and privacy. J Big Data5, 1. https://doi.org/10.1186/s4053-017-0110-7Links to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Health data analytics now includes intelligent methods to capture, integrate, and analyze in real-time heterogeneous unstructured and structured data from clinical and personal health sources to provide predictive, personalized, and patient-centered healthcare intelligence. The technological phenomenon where computer networks are used to produce huge amounts of data which can be stored, organized, and processed into meaningful and coherent information (Dewey, 2022). In healthcare systems, there is involvement of a vast range of health-related information related to patients and their dynamics, such as biodata which are stored to improve efficiency, reduce redundancy, reduce repetition of work and save on time. Big data has also been seen to help in simultaneous access of information, at first hand. This has made information consistent, and has reduced the margin of errors at work. 

 One potential threat of big data is that of cyberbullying and susceptibility to privacy violations. This can be done by hackers, or even by people who have access to patients’ information for instance, then go ahead and share it. This is already infringement of privacy. Many a times, HIPPA rules are involved in big data system or any technological involvement in the patients’ data, but there seems to be no repercussions when there is breakage into data. This is a public concern, as no one wants their data breeched and out there (Guo et al., 2020). 

 In mitigating cyberbullying, hacking and security violations, blockchain is among the most utilized technologies in addressing EHR challenges. Blockchain is a high standard technological advancement which has the intrinsic ability to provide security  via decentralization and cryptography. A big number of health care setups who utilize blockchain to minimize security and privacy violation have reported good feedback on security maintenance. Newer technologies like clouds which use Attribute-Based Encryption (ABE) together with Identity-Based Encryption (IBE) to encrypt data are continuously being used to ensure there is fine access, control, monitoring and implementation of these systems. 

References; 

Dewey, J., PhD. (2022). Big data. Salem Press Encyclopedia.  

 Guo, H., Li, W., Meamari, E., Shen, C.-C., & Nejad, M. (2020). Attribute-based multi-signature and encryption for EHR management: A blockchain-based solution. International Conference on Blockchain and Cryptocurrency (ICBC), (978-1-7281-6680-3). Retrieved December 27, 2022, from https://doi.org/10.1109/ICBC48266.2020.9169395Links to an external site. 

Wang, C.J., Ng, C.Y., & Brook, R. H. (2020) Response to COVID-19 in Taiwan: Big Data Analytics, New Technology, and Proactive Testing. Journal of the American Medical Association. doi:10.1001/jama.2020.3151 

BM (n.d.). What is blockchain technology? https://www.ibm.com/topics/what-is-blockchainLinks to an external site. 

Health Care Industry Cybersecurity Task Force. (2017). Report on Improving Cybersecurity in the Health Care Industry. Public Health Emergency. Retrieved 

from https://www.phe.gov/Preparedness/planning/CyberTF/Documents/report2017.pdfLinks to an external site. 

Weintraub, R. & Borenstein, J. (2017).  11 things the healthcare sector must do to improve cybersecurity. Harvard Business Review. Retrieved from https://hbr.org/2017/06/11-things-the-health-care-sector-must-do-to-improve-cybersecurityLinks to an external site. 

Great post!  Big data offers many great benefits such as increasing earlier diagnosis and the effectiveness and quality of treatments, but it also has many challenges. Just like you, I believe that a big challenge of using big data is data security. In the last 5 years, the surge of data breaches has gone up tremendously. Yahoo, Facebook, Dropbox, Equifax, Twitter and Google are just some of the high-profile companies that are known to collect big data, but also share unwanted tag of experiencing data breach (Abouelmehdi, 2017). There are many ways organizations can implement security measures to protect their big data analytics tools. One of the most common security tools is encryption which would allow data to be completely protected. In addition, building a strong firewall is also another useful big data security (Zhang, 2018). Organizations can prevent attacks before they happen by creating strong filters that avoid any third parties or unknown data sources. 

 

References 

Abouelmehdi, K. (2017). Big data security and privacy in healthcare:   

          https://doi.org/10.1016/j.procs.2017.08.292Links to an external site. 

Zhang, D. (2018). Big data security and privacy protection. https://doi.org/10.2991/icmcs-18.2018.56 

According to McGonigle and Mastrian (2022), “In addition to complying with federal HIPAA and HITECH guidelines regarding the privacy of patient information, healthcare systems need to be vigilant in the way that they secure information and manage network security”. It is crucial to protect confidential information. When utilizing cloud computing, it is abundantly evident that healthcare businesses need to exercise an elevated level of vigilance regarding the security of their data. However, the best recommendation is to provide training to employees on proper security procedures may be the most effective line of protection. 

The authentication processes can be difficult and time consuming, but on the bright side, they result in a reduction in the overall performance efficiency of doctors. 

 

References 

Healthcare Big Data and the Promise of Value-Based Care. (2018, January 1). nejm catalyst. Retrieved December 26, 2022, from https://catalyst.nejm.org/doi/full/10.1056/CAT.18.0290Links to an external site. 

McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning 

Wider. (2022, November 21). Healthcare Innovation. Cybersecurity. Retrieved December 29, 2022, from https://www.hcinnovationgroup.com/cybersecurity/privacy-security/news/21287852/report-highlights-hhs-data-and-cybersecurity-challenges 

          Information has been the key to a better organization and new developments. The more information we have, the more optimally we can organize ourselves to 

deliver the best outcomes. That is why data collection is an important part for every organization. We can also use this data for the prediction of current trends of 

certain parameters and future events. As we are becoming more and more aware of this, we have started producing and collecting more data about almost everything 

by introducing technological developments in this direction. Today, we are facing a situation wherein we are flooded with tons of data from every aspect of our life 

such as social activities, science, work, health, etc. In a way, we can compare the present situation to a data deluge. The technological advances have helped us in 

generating more and more data, even to a level where it has become unmanageable with currently available technologies. This has led to the creation of the term 

‘big data’ to describe data that is large and unmanageable (Dash et al., 2019). Big data in healthcare is very essential because it provides better care for the patients 

and educates the patients on their ongoing progress. Big data allows healthcare providers and health administrators to drill down and learn more about their patients 

and the care they provide to them. Collecting high-quality data requires optimization of data collection tools in health care and proper use of such tools by patients 

and providers alike (Tulane University, 2022). 

          When it comes to data accuracy, it aids in monitoring patient health advancements and improving patient care in healthcare organizations. In several contexts, 

the use of Big Data in healthcare is already offering solutions for the improvement of patient care and the generation of value in healthcare organizations. This 

approach requires, however, that all the relevant stakeholders collaborate and adapt the design and performance of their systems. They must build the technological 

infrastructure to house and converge the massive volume of healthcare data, and to invest in the human capital to guide citizens into this new frontier of human 

health and well-being (Pastorino et al., 2019). An example of Big data, is EHR which is good at providing accurate, up-to-date, and complete information about 

patients at the point of care; enabling quick access to patient records for more coordinated, efficient care; securely sharing electronic information with patients and 

other clinicians ( HealthIT.gov, n.d.). In the field of healthcare, big data refers to collecting, analyzing, and leveraging consumer, patient, physical, and clinical data 

that is too vast or complex to be understood by traditional means of data processing (Mercury Healthcare, n.d.). 

           Despite the advancements and benefits of Big data, it has its cons. The term “big data” has become extremely popular across the globe in recent years. 

Almost every sector of research, whether it relates to industry or academics, is generating and analyzing big data for various purposes. The most challenging task 

regarding this huge heap of data that can be organized and unorganized, is its management. Given the fact that big data is unmanageable using the traditional 

software, we need technically advanced applications and software that can utilize fast and cost-efficient high-end computational power for such tasks (Dash et al., 

2019). Despite the size of big data, the security of patient information can be breached. The patient’s vital information can be accessible at times, however, both 

authorized and unauthorized members of the healthcare organization have privy to it, resulting in a lack of security for the patient’s health information. By failing to 

keep patient records private, your organization could face substantial penalties under HIPAA’s Privacy and Security Rules, as well as potential harm to its reputation 

within your community. Most importantly, patient safety and care delivery may also be jeopardized (AHA, n.d.). 

         Based on my working experience, data collecting makes working much more convenient and saves lots of time in giving patients the care they need. One 

strategy that may effectively mitigate the lack of security of patient data is gaining cloud technology in healthcare organizations. The goals of cloud computing in 

the medical field are to improve the quality, safety and efficiency of medical services, to better engage patients and family, improve the coordination of care, and to 

maintain patient privacy and security. Today, the majority of hospital and healthcare facilities have abandoned the practice of paper record-keeping when it comes to 

health records and are turning to cloud storage in healthcare. Electronic health records are stored in the cloud and updated electronically by physicians, nurses and 

other healthcare providers (Dhilawala, n.d.). Data may be limited in this way to only the caregivers and the nurse who is now providing direct care. Before 

accessing data, cloud technology or the development of double authentication should be used. As the name suggests, ‘big data’ represents large amounts of data that 

is unmanageable using traditional software or internet-based platforms. It surpasses the traditionally used amount of storage, processing and analytical power  (Dash 

et al., 2019). Even though Big data has its pros and cons, it has really helped the healthcare industry to keep improving patient care.  

References 

American Hospital Association. (n.d.). The importance of cybersecurity in protecting patient safety | Cybersecurity | Center  AHA. 

https://www.aha.org/center/cybersecurity-and-risk-advisory-services/importance-cybersecurity-protecting-patient-safetyLinks to an external site. 

Dhilawala, A. (n.d.). 9 Key Benefits of Cloud Computing in Healthcare 

https://www.galendata.com/9-benefits-cloud-computing-healthcare/Links to an external site. 

HealthIT.gov. (n.d.). What are the advantages of electronic health records? 

https://www.healthit.gov/faq/what-are-advantages-electronic-health-recordsLinks to an external site. 

Mercury Healthcare. (n.d.). What is Big Data in Healthcare? Links to an external site. 

https://www.mercuryhealthcare.com/faq/what-is-healthcare-big-dataLinks to an external site. 

Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019a). 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/ckz168Links to an external site. 

Tulane University. (2022). Big Data in Health Care and Patient Outcomes. School of Public Health. 

https://publichealth.tulane.edu/blog/big-data-in-healthcare/Links to an external site. 

References 

American Hospital Association. (n.d.). The importance of cybersecurity in protecting patient safety | Cybersecurity | Center  AHA. 

https://www.aha.org/center/cybersecurity-and-risk-advisory-services/importance-cybersecurity-protecting-patient-safetyLinks to an external site. 

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/s40537-019-0217-0Links to an external site. 

Dhilawala, A. (n.d.). 9 Key Benefits of Cloud Computing in Healthcare 

https://www.galendata.com/9-benefits-cloud-computing-healthcare/Links to an external site. 

HealthIT.gov. (n.d.). What are the advantages of electronic health records? 

https://www.healthit.gov/faq/what-are-advantages-electronic-health-recordsLinks to an external site. 

Mercury Healthcare. (n.d.). What is Big Data in Healthcare?  

https://www.mercuryhealthcare.com/faq/what-is-healthcare-big-dataLinks to an external site. 

Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019a). 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 

Tulane University. (2022). Big Data in Health Care and Patient Outcomes. School of Public Health. 

https://publichealth.tulane.edu/blog/big-data-in-healthcare/ 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

The Use of Big Data in Clinical System 

Big data is increasingly being applied in clinical systems to help improve patient care. This is due to the benefits that big data has had on clinical systems. This paper will discuss the possible benefits, challenges, and a strategy that can be used to mitigate the risks posed by big data to clinical systems. 

The Benefits of Using Big Data as Part of a Clinical System 

 A potential benefit of using big data in a clinical system is that it can help improve patient care. According to research, big data has been helpful in building holistic care strategies for patients in order to achieve patients’ well-being in an effective way (Dash et al., 2019). This is because big data empowers patients to take an active part in their own healthcare. Furthermore, big data can help identify patterns in patient behavior that may indicate a need for preventive care or early detection of diseases. For instance, if big data is used to monitor patient health over time, it may be possible to detect patterns in how patients respond to treatment and identify which patients are at risk for developing certain diseases. This information can then be used to make better decisions about how to treat those patients. In addition, big data can help healthcare providers identify potential risks and issues early on in a patient’s illness in order to prevent more serious complications (El Naqa et al., 2018). Finally, using big data in clinical systems can help make it easier for doctors and nurses to identify optimal care plans for patients based on their individual needs. By collecting and analyzing data from multiple sources, it is possible to create a comprehensive picture of a patient’s health that can be used to improve care. 

Challenges of Using Big data as Part of a Clinical System 

One potential challenge of using big data in clinical systems is that it can be difficult to collect and analyze the data in a way that is effective and efficient (El Naqa et al., 2018). For instance, it may be difficult to find a way to use big data to monitor a patient’s health over time. Additionally, it may be difficult to ensure that the data is accurate and reliable. If the data is not accurate or reliable, it may not be useful in making decisions about a patient’s care. Finally, big data may be too complex or time-consuming to use in some cases. If the data is too complex, it may be difficult for doctors and nurses to understand it (Mayo et al., 2017). If the data is too time-consuming, it may be difficult for doctors and nurses to use it in their decision-making. 

Propose at least one strategy you have experienced, observed, or researched that may effectively mitigate the challenges or risks of using the big data you described. 

One strategy that may mitigate the challenges or risks of using big data in clinical systems is to use a data mining tool. Data mining tools can help doctors and nurses to find patterns in the data that may be useful in making decisions about a patient’s care (Bartschat et al., 2019). It can also help to ensure that the data is accurate and reliable. Additionally, data mining tools can be used to simplify the data so that it is easier for doctors and nurses to understand it. 

References 

Bartschat, A., Reischl, M., & Mikut, R. (2019). Data mining tools. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 9(4), e1309. 

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of Big Data, 6(1), 1-25. 

El Naqa, I., Kosorok, M. R., Jin, J., Mierzwa, M., & Ten Haken, R. K. (2018). Prospects and challenges for clinical decision support in the era of big data. JCO clinical cancer informatics, 2, 1-12. 

Mayo, C. S., Matuszak, M. M., Schipper, M. J., Jolly, S., Hayman, J. A., & Ten Haken, R. K. (2017). Big data in designing clinical trials: opportunities and challenges. Frontiers in Oncology, 7, 187. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Thank you for the informative dive into big data in clinical systems and how this technology can augment patient care quality. In the paper, you have highlighted the potential of the technology in consolidating holistic approaches to patient care by providing insights that will enable patients actively take part in their care and make better decisions from both healthcare providers and patients alike. You have also highlighted the barriers to using big data, mainly in collecting and analyzing data for healthcare providers. Understandably, analyzing big data can be challenging for healthcare providers for several reasons, probably due to the sheer volume of data that needs to be analyzed (Pramanik et al., 2022). Healthcare providers need the right tools and expertise to make sense of all this data and extract useful insights. Analysis can be time-consuming, as it often requires complex algorithms and advanced statistical techniques. 

In addition to data mining tools, healthcare centres can also use specialized software and tools. These can include data visualization software, machine learning algorithms, and statistical analysis tools (Ngiam & Khor, 2019). These tools can help to organize and process large amounts of data and provide insights and trends that may not be immediately obvious. It is also important for healthcare providers to clearly understand their goals and objectives when analyzing big data and to work with a team of experts with experience in data analysis and healthcare (Pramanik et al., 2022). By using these strategies, healthcare providers can more effectively draw useful insights from their data and use these insights to improve patient care and outcomes. 

References 

Ngiam, K. Y., & Khor, I. W. (2019). Big data and machine learning algorithms for healthcare delivery. The Lancet Oncology, 20(5), e262–e273. https://doi.org/10.1016/s1470-2045(19)30149-4 

Pramanik, P. K. D., Pal, S., & Mukhopadhyay, M. (2022). Healthcare Big Data. Research Anthology on Big Data Analytics, Architectures, and Applications, pp. 119–147. https://doi.org/10.4018/978-1-6684-3662-2.ch006 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

The potential benefits of using big data in nursing practice include the extraction of insights to improve patient and population outcomes, the promotion of multidisciplinary collaboration, and the maintenance of cost efficacy. The utilization of big data in nursing practice creates room for accelerating evidence-based practice toward the attainment of positive patient outcomes (Hardy, 2018). Nursing practice necessitates the continuous acquisition of data from multiple sources to support positive patient outcomes and improve care quality. 

As a part of a clinical system, big data allows registered nurses to generate new evidence from multiple sources and broaden the existing knowledge base to improve patient and population outcomes. Through big data, registered nurses can extract numerous insights from the current best evidence to inform clinical decisions and provide patient-centered care services (Hardy, 2018). The utilization of big data creates room for the engagement of healthcare professionals from multiple disciplines to accelerate discovery, improve the quality of clinical decisions, and meet the care needs of increasingly diverse patient populations. 

The continued engagement of healthcare professionals from multiple disciplines in clinical decision-making processes promotes multidisciplinary collaboration for strengthening professional practice, lowering the risk of medical errors, and improving patient outcomes. The continuous analysis of data elements from the clinical system by the multidisciplinary team informs the elimination of redundant or conflicting roles to maximize cost efficacy during the provision of care services (Gibson et al., 2022). The promotion of multidisciplinary collaboration through the extraction of big data insights helps nurses and other professionals to remain committed to positive patient outcomes and deter the occurrence of adverse events to maintain cost efficiency in the continued operationalization of clinical systems. 

The expansive growth of health information technology and the utilization of big data in clinical systems are identified with challenges or risks like the exposure of protected health information to third parties and the risk of technical issues or problems delaying patient care decisions. The use of big data in clinical systems is characterized by the utilization of mobile devices like personal computers and tablets by registered nurses and other professionals to exchange patient-centered data and create room for collaborative decision-making processes (Higgins et al., 2018). The continued use of mobile devices by nurses and other professionals creates room for hackers to penetrate clinical systems, as well as access and manipulate protected health information for malicious intent. 

The manipulation of big data in clinical systems disrupts decision-making processes by registered nurses and contributes to missed or delayed care among diverse patient populations. The use of big data in clinical systems can be impeded by technical issues or problems contributing to delayed patient care decisions (McGonigle & Mastrian, 2022). The persistence of technical issues or problems in the collection and management of data deters the extraction of insights by registered nurses and other healthcare professionals as they make efforts to meet patient needs and enhance population outcomes. 

The proposed strategies for preventing unauthorized access to protected health data and maximizing information security are encryption and the creation of strong passwords (McGonigle & Mastrian, 2022). Through encryption, the data in transit from one healthcare professional to another remains shielded from interception by hackers and other persons with malicious intent in the continued operationalization of clinical systems. The protection of health data from hackers and other persons with malicious intent necessitates the creation of strong access credentials like passwords and user codes (Gibson et al., 2022). Regular update of passwords and user codes by registered nurses and other professionals is recommended for the preservation of data integrity and the improvement of healthcare consumer experiences. 

References 

Gibson, J., Jerde, M. J., & Shivers, N. (2022). Leveraging big data in nursing practice. Nurse Leader, 20(5), 461–464. https://doi.org/10.1016/j.mnl.2022.06.004 

Hardy, L. R. (2018). Using big data to accelerate evidence-based practice. Worldviews On Evidence-Based Nursing, 15(2), 85–87. https://doi.org/10.1111/wvn.12279 

Higgins, M., Simpson, R. L., & Johnson, W. G. (2018). What about big data and nursing? Statistics, computer science, and nursing work together to analyze data and inform patient care. American Nurse Today, 13(5), 29–31. 

McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Big data in healthcare refers to the large volumes of data generated by electronic health records, medical devices, and other sources, and it can provide valuable insights and inform decision-making in the healthcare sector (Lv & Qiao, 2020). Although there are several potential advantages to using big data in nurse leadership and patient care, there are also a number of concerns that need to be carefully controlled. The handling and use of big data also raise concerns about privacy, security, and ethical issues that must be carefully considered. Here, we will explore the risks and rewards of big data in nursing leadership and patient care, examining how big data can improve outcomes and the potential pitfalls that must be avoided. 

The Benefits 

Improving patient outcomes is one of the possible advantages of its incorporation in nursing and healthcare. Using related analytics to identify trends and patterns in patient data, nurses and other healthcare providers can predict and prevent adverse outcomes, such as hospital readmissions or complications (Mehta & Pandit, 2018). For example, big data could be used to identify patterns in patient data associated with an increased risk of certain conditions, allowing healthcare providers to intervene earlier and potentially prevent the onset of those conditions (Mehta & Pandit, 2018). Using big data to identify and address potential problems before they arise, nurses and other healthcare providers can improve patient outcomes and reduce the burden of illness on patients and the healthcare system. 

Another potential benefit of big data in nursing and healthcare is the ability to enhance efficiency and resource utilization. By using big data analytics to identify patterns in patient data, healthcare providers can optimize resource utilization and improve the efficiency of care delivery, reducing costs and improving patient satisfaction (SA, 2018). For example, big data could be used to identify patient data patterns associated with longer lengths of stay in the hospital, allowing healthcare providers to intervene and discharge patients sooner. This could reduce the burden on the healthcare system and allow providers to see more patients in each period, improving efficiency and resource utilization (Mehta & Pandit, 2018). In addition, big data could be used to identify trends in patient behavior or preferences, allowing healthcare providers to tailor their care delivery to meet patients’ needs better and improve their satisfaction with care. 

The Downside 

One of the risks is the potential for ethical concerns. For example, there is a risk that biased algorithms could be used to make decisions about patient care, leading to potential inequities or discrimination. For instance, if an algorithm is programmed using biased or unrepresentative data, it may unfairly discriminate against certain patient groups. There are also concerns about using data unethically (Shilo et al., 2020). Big data use in healthcare must be ethical, responsible, and consistent with the values and principles of the healthcare profession if we are to reduce these hazards. 

Ethics, Decision-Making and Optimal Care 

Creating and implementing ethical principles and norms that especially target big data could be a strategy to solve the drawbacks. The use needs to be transparent, accountable, and respectful of patients’ autonomy, according to these standards and guidelines. For instance, rules might be created to guarantee that its application is founded on morally solid ideas like respect for people, beneficence, non-maleficence, and fairness. Guidelines might also be created to establish clear procedures for the oversight and accountability of algorithms used in healthcare and to make sure that algorithms are trained on data that is representative and free from bias. 

Understandably, making decisions using this data has been challenging, owing to the need for some parameters needed by nursing leaders to arrive at decisions efficiently. This gap must also be addressed. One way may be to engage in data cleaning and preprocessing to ensure that the data is as complete and accurate as possible. This can involve identifying and correcting errors in the data, filling in missing values, and standardizing data formats. Cleaning and preprocessing the data, healthcare providers can help ensure that the data is as reliable and accurate as possible, which can, in turn, help improve the accuracy and reliability of decisions made based on that data. 

Another way to address the challenge of lacking crucial parameters in data is to incorporate additional data sources or to supplement the data with additional information. For example, healthcare providers could use external data sources, such as public health or social media data, to supplement their available data and provide a complete picture of the patient population. In addition, healthcare providers could use predictive analytics or machine learning techniques to fill in missing values or to estimate missing parameters based on other available data (Mehta & Pandit, 2018). By incorporating additional data sources or using predictive analytics, healthcare providers can help to improve the completeness and accuracy of their data, which can, in turn, help to improve the accuracy and reliability of decisions made based on that data. 

Conclusion 

Big data use in nursing and healthcare can have a substantial positive impact on patient outcomes, efficiency, and resource allocation. However, it also carries a range of risks that must be carefully managed, including privacy and security concerns and ethical issues. To maximize the benefits of big data in nursing and healthcare while minimizing the risks, it is important to implement strong privacy and security measures and to develop and implement ethical guidelines and frameworks to ensure that the use of big data is transparent, accountable, and respectful of patient’s rights and autonomy. By addressing these issues responsibly and ethically, healthcare providers can help to ensure that big data application is beneficial for patients and the healthcare system. 

References 

Lv, Z., & Qiao, L. (2020). Analysis of big healthcare data. Future Generation Computer Systems, 109, 103–110. https://doi.org/10.1016/j.future.2020.03.039 

Mehta, N., & Pandit, A. (2018). Concurrence of big data analytics and healthcare: A systematic review. International Journal of Medical Informatics, 114, 57–65. https://doi.org/10.1016/j.ijmedinf.2018.03.013 

SA, S. (2018). Big Data in Healthcare Management: A Review of Literature. American Journal of Theoretical and Applied Business, 4(2), 57. https://doi.org/10.11648/j.ajtab.20180402.14 

Shilo, S., Rossman, H., & Segal, E. (2020). Axes of a revolution: challenges and promises of big data in healthcare. Nature Medicine, 26(1), 29–38. https://doi.org/10.1038/s41591-019-0727-5 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Your post is insightful. I find it interesting that you highlighted bias as a challenge of using big data in healthcare. Bias is a common problem in the analysis of big data that occurs when one class is underrepresented (Tam and Kim, 2018). As a result of bias, the predictive model built is likely to make erroneous predictions because it does not have enough samples of the underrepresented group to correctly predict outcomes for the group. To eliminate bias in the use of big data for healthcare, I recommend using participatory science. Participatory science involves the inclusion of specific underrepresented patient groups in the design of predictive algorithms that benefit them (Norori et al. 2021). Through this process, the patients will be able to contribute to the elimination of bias by pointing out misconceptions that increase bias and identifying bias against their population. 

References 

Norori, N., Hu, Q., Aellen, F. M., Faraci, F. D., & Tzovara, A. (2021). Addressing bias in big data and AI for health care: A call for open science. Patterns, 2(10), 100347. https://doi.org/10.1016/j.patter.2021.100347 

Tam, S. M., & Kim, J. K. (2018). Big Data ethics and selection-bias: An official statistician’s perspective. Statistical Journal of the IAOS, 34(4), 577-588. https://doi.org/10.3233/SJI-170395 

 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

 

The use of big data as part of a clinical system helps identify patterns of care and provides a broader view of evidence-based practice. For example, the use of big data can enable practitioners to immensely benefit from nursing informatics and reduce readmission rates (Glassman, 2017). Big data analytics can also support more appropriate decisions concerning patient diagnosis, treatment, and disease prevention. Additionally, big data analytics can help practitioners significantly identify areas for improvement and determine which interventions have the greatest potential for success. However, the analysis of the large amounts of data collected can be time-consuming and costly, which is a significant hindrance to the use of big data analytics (Thew, 2016). Moreover, big data stored in a compromised or weak data security system may be limited in providing detailed, actionable insights into population health and healthcare outcomes. 

Healthcare systems can implement cyber-security measures such as strong and complex passwords, regular updates to security software, and using standard anti-viruses to mitigate the risk of a breach of privacy. Furthermore, healthcare systems can deploy encryption and data masking to ensure that data remain secure during transmission, storage, and analysis. In addition, healthcare systems can utilize secure cloud storage services as an additional layer of protection to store data. Such measures can help protect the confidentiality, integrity, and availability of patient data, allowing healthcare systems to benefit from the potential opportunities that big data offer. Moreover, it is important to ensure that all staff within the healthcare system are trained on cyber security protocols and understand their responsibility in protecting the collected data (Wang et al., 2018). By taking these proactive measures, healthcare systems can protect their data from cyberattacks and unauthorized access. 

 

References 

Glassman, K. (2017). Using data in nursing practice. https://www.americannursetoday.com/wp-content/uploads/2017/11/ant11-Data-1030.pdf 

Thew, J. (2016). Big data means big potential, challenges for nurse execs. Health Leaders. 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. Technological Forecasting and Social Change, 126(1), 3–13. https://doi.org/10.1016/j.techfore.2015.12.019 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

The use of big data technology is enabling care providers know more about their patients and offer more effective care. Yaqoob et al. (2016) defined big data as data that is difficult to manage using traditional data management methods due to its large size, complexity, and velocity. Collecting and processing such data to produce meaningful information requires specialized technologies. However, studies have shown that big data analysis provides more detailed and accurate information than other forms of data. Hence, big data is widely used in clinical systems to improve healthcare processes and patient care. In my facility, big data from wearables is used to deliver timely medical intervention despite the risk of information theft. 

Wearable technology is a facet of health information technology (HIT) that has improved the quality and timeliness of care offered to outpatients especially people with cardiac or respiratory illness. Wearable devices transmit patient data such as heart rate, blood pressure, and respiration rate to their care providers remotely (Wu & Luo, 2019). In my facility, we use this technology to track the condition of certain patients with heart and respiratory diseases remotely. A benefit of this technology is that it enables clinicians to intervene in the shortest possible time. When the heart rate of a patient with hypertension spikes or goes above the recommended level, the system sends an alert so that a medical practitioner can intervene by reaching out to the patient to recommend a solution or delivering care if necessary. Another benefit to using wearable technology is that it reduces the cost of in-patient care (Wu & Luo, 2019). 

Despite the obvious advantages of using wearable devices, the technology possesses some risks. A major risk with using wearable technology is patient data security. Cillers (2020) asserted that wearable devices are vulnerable to cyber attacks because the data is usually sent through unsafe public wifis and cell data. This means that the weakest security link is in the intermediary connection. Thus, while using these unsafe networks to transmit sensitive data, cyber criminals can intercept such data. This problem is much more prominent when the identity of the patient is sensitive. To mitigate this issue, Wang et al. (2016) recommend using additional layers of security to checkmate the weak link. This strategy involves connecting the wearable device to only trusted networks and regularly updating the software to stay up-to-date with the latest security. 

 

References 

Cilliers, L. (2020). Wearable devices in healthcare: Privacy and information security issues. Health information management journal, 49(2-3), 150-156. https://doi.org/10.1177/1833358319851684 

Wang, S., Bie, R., Zhao, F., Zhang, N., Cheng, X., & Choi, H. A. (2016). Security in wearable communications. IEEE Network, 30(5), 61-67. http://doi.org/10.1109/MNET.2016.7579028 

Wu, M., & Luo, J. (2019). Wearable technology applications in healthcare: a literature review. Online J. Nurs. Inform, 23(3). https://www.himss.org/resources/wearable-technology-applications-healthcare-literature-review 

Yaqoob, I., Hashem, I. A. T., Gani, A., Mokhtar, S., Ahmed, E., Anuar, N. B., & Vasilakos, A. V. (2016). Big data: From beginning to future. International Journal of Information Management, 36(6), 1231-1247. https://doi.org/10.1016/j.ijinfomgt.2016.07.009 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

I enjoyed reading your post. The idea of big data in the form of wearable technology to deliver timely medical information and interventions have improved healthcare today. Since the creation of remote telemetry monitoring, it has been proven to help provide high-quality patient care (Gieras, 2003). Although the wearable devices have made it easy to help healthcare professionals intervene when needed quickly and have improved healthcare it still poses some risk. One risk of utilizing any technology is data security. Most healthcare agencies have sensitive health information and according to Cilliers wearable devices are more venerable to cyber-attacks due to how the data is transmitted (2020). To overcome this obstacle the facility could connect the wearable device to a trusted and secure network that is being managed with regular updates on software and security methods. Overall, using big data will help healthcare providers offer improved monitoring and effective care. 

References: 

Cilliers, L. (2020). Wearable devices in healthcare: Privacy and information security issues. Health information management journal, 49(2-3), 150-156. https://doi.org/10.1177/1833358319851684Links to an external site. 

Gieras, I. A. (2003). The proliferation of patient-worn wireless telemetry technologies within the U.S. healthcare environment. 4th International IEEE EMBS Special Topic Conference on Information Technology Applications in Biomedicine, 2003., Information Technology Applications in Biomedicine, 2003. 4th International IEEE EMBS Special Topic Conference on, Information Technology Applications in Biomedicine, 295–298. https://doi.org/10.1109/ITAB.2003.1222536Links to an external site. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

 

Big data analysis has become a great way for organizations to get ahead of their competition in today’s markets. Big data provides nuanced information that is difficult to extract using traditional means of data management. However, advances in technology and scientific processes have led to the emergence of technologies and methods capable of exploring the potential of big data. In nursing practice, large amounts of patient data are collected to improve patient care. With the introduction of big data technology, nurses can collect and process such data more efficiently to extract insights that are central to providing quality evidence-based patient care (Hardy, 2018). However, while big data provides information that can be used to improve patient care, it also presents unique challenges that can derail its usage if not appropriately managed. 

A good example of big data in action in my workplace is in the use of clinical decision support (CDS) alerts. CDS alerts enhance health care by providing clinicians, patients, or other stakeholders with individual-specific information that is smartly filtered and delivered at the appropriate time (Olakotan & Mohd Yusof, 2021). This system helps ensure patient safety by sending alerts when adverse conditions are detected or reminding clinicians of a missed procedure. For patients with cardiovascular diseases, the system helps improve their outcomes by sending alerts when their heart rate exceeds a certain range to draw attention to the situation and precipitate prompt medical intervention. However, despite the many positives, CDS alerts can negatively impact the well-being of clinicians. Yoshida et al. (2018) pointed out that CDS alerts can lead to alarm fatigue and burnout in clinicians. The many alerts disrupt workflow. Hence, continuous bombardment with alerts from different patients increases stress levels and anxiety leading to burnout and numbness to incoming alerts. Such a situation can lead to negative outcomes for both care providers and patients. 

To enjoy the benefits of using the CDS alert system without compromising the well-being of the clinician or patients requires implementing certain strategies. Yoshida et al. (2018) recommend increasing the specificity of alerts by removing clinically inconsequential ones and tiering alerts according to severity. Doing so will reduce the frequency of alerts clinicians get. Also, tiering the alerts will give the clinician more room to maneuver and decide if immediate intervention is necessary or if it can be postponed. 

References 

Hardy, L. R. (2018). Using big data to accelerate evidence-based practice. Worldviews on Evidence-Based Nursing, 15(2), 85–87. https://doi.org/10.1111/wvn.12279 

Olakotan, O. O., & Mohd Yusof, M. (2021). The appropriateness of clinical decision support systems alerts in supporting clinical workflows: A systematic review. Health Informatics Journal, 27(2). https://doi.org/10.1177/14604582211007536 

Yoshida, E., Fei, S., Bavuso, K., Lagor, C., & Maviglia, S. (2018). The value of monitoring clinical decision support interventions. Applied Clinical Informatics, 9(01), 163-173. https://doi.org/10.1055/s-0038-1632397 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

Great insight on how to blend using big data strategically modified to be applicable with considering barriers. It sounds like the strategies you’ve identified align with using data in a valuable and meaningful way. McGonigle & Mastrian, 2022, state, “The data in big clinical datasets can get lost, diminishing their value. Therefore, it is imperative that KDD and AI be used to analyze these datasets to discover meaningful information that will influence healthcare practice” (p. 558). This was a great example of how technology was a facilitator. 

Facilitators and driving forces that keep technology use well-received by nursing can include knowledge and skills in evidence-based practice (McGonigle & Mastrian, 2022). These alerts are helping and influencing health care practice by nurses using this technology to provide safe quality care in the setting you describe clinically. You also mentioned alert fatigue, and the research indicates a strategy also to reduce alert fatigue is by attracting the attention of patients and clinicians instead of solely reducing the total number of alerts (Wan et al., 2020). Expanding the use of alert reminders to the patients themselves would take this one step further. Mobile alerts on patients’ cell phones can promote positive health behavior change, adherence to health regimes, and exposure to educational health information (Perri-Moore et al., 2016). I think nurses will learn how to adapt to a revolution of changes happening now and only more to come. 

References 

McGonigle, D., & Mastrian, K. G. (2022). Nursing informatics and the foundation of knowledge (5th ed.). Jones & Bartlett Learning 

Perri-Moore, S., Kapsandoy, S., Doyon, K., Hill, B., Archer, M., Shane-McWhorter, L., Bray, B. E., & Zeng-Treitler, Q. (2016). Automated alerts and reminders targeting patients: A review of the literature. Patient Education and Counseling, 99(6), 953-959. https://doi.org/10.1016/j.pec.2015.12.010 

Wan, P. K., Satybaldy, A., Huang, L., Holtskog, H., & Nowostawski, M. (2020). Reducing alert fatigue by sharing low-level alerts with patients and enhancing collaborative decision making using Blockchain technology: Scoping review and proposed framework (MedAlert). Journal of medical Internet research, 22(10), e22013. 

A Sample Answer For the Assignment: NURS 6051 BIG DATA RISKS AND REWARDS

Title: NURS 6051 BIG DATA RISKS AND REWARDS

The day-to-day operations of the institution help generate millions of data that, over the course of time, will require proper channels of transmission, storage, processing, assimilation, and utilization. This is because of the rapidly accelerating pace of technological advancement in the health care sector. Following on from the vast amount of data that is generated, some of its benefits include but are not limited to functioning as a pattern discovery aid with relation to the amount of variance or similarity in the cases that are seen by a specific health care organization, the data bank develops a pattern memory that helps the facility better prepare based on the statistical evidence that is derived from their previous encounter with a surge of disease only relative to the hospitals geographical location, and the data bank also functions as a pattern memory that helps the facility better prepare “The act of just gathering data in order to respond to a question posed by an end user is only one aspect of pattern discovery. Data mining technologies search through datasets to discover patterns that were previously unknown. The information that is predictive and proactive that is produced as a consequence of data mining analytics is therefore helpful in the creation of business intelligence, particularly in regard to how we might become better. (McGonigle, 2017, p477) 

Big data’s ability to improve continuity of care is another advantage of using it. From the moment a patient checks into the hospital until the moment they are discharged, the vast amount of data generated from laboratory testing, imaging, or other specialized tests ensures continuity of care. This is possible because every department and or axillary health care support system can access such data and proceed with their plan of care without having to redo the efforts of redoing labs and imaging s. Big data’s ability to improve continuity of care 

In order to simplify and streamline the nursing workflow that occurs inside EHRs, eliminating unnecessary duplication of effort would go a long way. The electronic health record (EHR) may be connected to various patient care equipment, such as heart monitors, vital sign monitors, and I.V. infusion pumps. A great number of them are, in essence, little computers that store and transmit their discrete data to the electronic health record (Glassman, 2017). Given the rapid pace at which technical advances in health care are being made, there are a number of additional concerns that need quick consideration. These include the dangers and difficulties involved with its use. Because the usefulness and operability of the system are dependent on continuous power supply, unplanned power interruptions during severe weather conditions offer a significant risk factor to the utilization of the large data warehouse. Cooperation on the part of the patient to embrace new development and the changes made to enhance their care also presents with a risk factor to the overall functioning of the parameters that have been put into place, which is another one of the challenges that comes with the use of the big data system. 

Another challenge that comes with the use of the big data system is how to keep the system running during moments of downtime or system upgrades. The fact that some of the characteristics that are most important to us as nurse leaders aren’t even included in the statistics is one of the things that causes the greatest aggravation for us as nurse leaders when we look at this data “Englebright adds. “For example, we do not have anything that can quantify the level of skill in nursing. We do not have anything that can assess the level of dedication shown by the nurses. We do not have anything that can determine whether or not the patient will really carry out the tasks that we have just spent a significant amount of time instructing them to carry out. (Thew, 2016) 

Using the following solutions is one of the strategies that, in my experience and/or observation, has the potential to successfully minimize the issues that are linked with big data. However, this list is not exhaustive. The usage of backup generators has shown to be a more effective means of handling unanticipated disruptions in the power supply while maintaining our commitment to provide our customers with continuous service. When the hospital expects a low population, such over the holidays, when operations inside the hospital might be managed by a skeleton team, planning downtime and/or system improvements should be scheduled. On the event that the main system and data bank of the organization suffer a failure, the idea of having a backup data storage in the cloud will also serve the goal of making the data easily accessible and retrievable in an efficient manner. 

 

Reference 

Glassman, K. S. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45–47. Retrieved from https://www.myamericannurse.com/using-data-nursing-practice/Links to an external site. 

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

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