NURS 6051 Week 5 Discussion Big Data Risks and Rewards PATRICIA Essay

NURS 6051 Week 5 Discussion Big Data Risks and Rewards PATRICIA Essay

NURS 6051 Week 5 Discussion Big Data Risks and Rewards PATRICIA Essay

Discussion: Big Data Risks and Rewards

Big Data refers to high volume and highly diverse biological, clinical, lifestyle, and environmental data on health and wellness status. Data collection ranges from one person to large cohorts. Big data in clinical systems obtain information from numerous sources such as patient summaries, EHRs, clinical trials, genomic data, telehealth, pharmaceutical data, and mobile apps (Pastorino et al., 2019). Employing big data in a clinical system comes with several benefits since it helps discover disease risk factors in an individual patient or a specific population (Glassman, 2017). Using big data increases disease prevention opportunities and informs health promotion activities for patients and the community.

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Health professionals can analyze big data from a patient’s clinical data gathered from EHR and summaries in predicting the possible risk of a patient developing a lifestyle disease or a disease complication (Wang et al., 2019). From the risk prediction, the health can then plan appropriate health promotion interventions to lower the risk of having the disease or slow the progression of an existing condition.

However, using big data in a clinical system has its limitation, like the risk of a data breach.  Big data compromises the security of patient data from data breaches, system hacks, and ransomware (Pastorino et al., 2019). A data breach occurs due to ineffective administrative system safeguards to secure patient data. In addition, public cloud services increase the risk of system hacks causing a data breach.

The risk of a data breach in big data can be alleviated through staff training to enhance the organization’s data security measures. McGonigle and Mastrian (2017) assert that organizations can train staff on data security protocols and updates in the protocols. Furthermore, organizations can frequently evaluate the staff with access to sensitive patient data to avoid data breach or damage by hackers and malicious parties.

References

Glassman, K. (2017). Using data in nursing practice. American Nurse Today, 12(11), 45-47.

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

Pastorino, R., De Vito, C., Migliara, G., Glocker, K., Binenbaum, I., Ricciardi, W., & Boccia, S. (2019). Benefits and challenges of Big Data in healthcare: an overview of the European initiatives. European journal of public health, 29(Supplement_3), 23-27 https://doi.org/10.1093/eurpub/ckz168

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. https://doi.org/10.1016/j.techfore.2015.12.019

 

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.