NURS 6051 Discussion: Big Data Risks and Rewards Essay
When you wake up in the morning, you might grab your phone to respond to missed messages. During your commute to work, you may refuel your car. At your workplace, you likely swipe a key card to enter, and on your way to your desk, you might stop for coffee. From the moment you wake up, you’re constantly generating data. Your phone use, card transactions, and even entering your workplace create data. How much data do you produce daily? Studies indicate that nearly 1 million bytes of data are generated per second per person on Earth.
PSYC 6717 week 6 Discussion: Applications of Philosophical Underpinnings
As data volumes grow, information experts seek ways to harness big data, which are extensive datasets requiring special approaches to utilize effectively. Big data can bring substantial benefits and risks to healthcare. In this discussion, we’ll explore these potential advantages and challenges.
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To Prepare:
– Review the resources and contemplate the web article titled “Big Data Means Big Potential, Challenges for Nurse Execs.”
– Reflect on your experiences with complex health data access and management. Consider the challenges and risks you’ve encountered or observed.
By Day 3 of Week 5:
Share at least one potential advantage of integrating big data into clinical systems and explain why. Then, describe at least one potential challenge or risk of using big data in clinical systems and explain why. Suggest at least one strategy you’ve experienced, observed, or researched to effectively mitigate the challenges or risks associated with using big data. Be specific and provide examples.
By Day 6 of Week 5:
Respond to at least two of your colleagues on two different days. Offer one or more additional strategies for mitigating risks or provide further insights into your colleagues’ assessments of big data opportunities and risks.
In our daily lives, we interact with various data-collecting devices. When we use our debit cards, data is sent to the card company, tracking our spending habits, preferences, and dislikes. Similarly, in healthcare, electronic health records capture extensive patient data, including wound details, admission information, and discharge outcomes, which contribute to benchmarking standards. One notable example of big data collection in healthcare is companies like 23andMe, which collect DNA samples worldwide.
“23andMe offers a direct-to-consumer genetic testing service based on single-nucleotide polymorphisms (SNPs) to determine ancestry and identify genetic markers associated with diseases and conditions” (Stoeklé et al., 2016). This information has connected families and provided insights into ancestry. It also holds the potential to contribute to disease cures and genetic therapy. However, the vast amount of data collected comes with a price. Some data is sold to other companies, which can raise concerns about privacy and potential misuse.
For instance, imagine if your insurance company accessed your data and denied coverage due to underlying conditions, limiting your healthcare options. Additionally, some data uses, whether good or bad, may remain undisclosed. Genetic testing data has even been used to solve criminal cases without the explicit consent of those who submitted their DNA, raising ethical questions.
In healthcare, data protection is typically safeguarded by layers of protection and specific consents outlining data usage. However, the value of big data makes us vulnerable to ransomware attacks and data breaches. The use of our data can be both a boon and a challenge, and it necessitates careful consideration.
References:
– Brown, T. R. (2019). Why We Fear Genetic Informants: Using Genetic Genealogy to Catch Serial Killers. Columbia Sci Technol Law Rev., 21(1), 114–181.
– Khan, R., & Mittelman, D. (2018). Consumer Genomics Will Change Your Life, Whether You Get Tested or Not. Genome Biology, 19(1).
– Stoeklé, H.-C., Mamzer-Bruneel, M.-F., Vogt, G., & Hervé, C. (2016). 23andMe: A New Two-Sided Data-Banking Market Model. BMC Medical Ethics, 17(1).
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