Discussion: Big Data Risks and Rewards
Discussion: Big Data Risks and Rewards
Benefits and Challenges of Big Data
All medical treatments and interventions emanated from research results. Irrespective of controlled experiments, large volume of data is generated from day to day health facility encounters, medical investigations, and prescriptions. These generated data form part of what is used to determine interventions. According to Pastorino et al. 2019, the healthcare environment is driven by data. In clinical settings, big data has a lot of advantages. Regardless of its advantages, there are also risks involved. As efficiency in healthcare has been enhanced by big data, access to information is also a great challenge.
The operational efficiency of healthcare systems is enhanced by use of big data which leads to positive patient outcomes. Data generated from the usage of equipment, the output from staff members, and patient outcome information are analyzed within healthcare institutions to identify gaps and opportunities for operational improvement (Adibuzzaman, DeLaurentis, Hill, & Benneyworth, 2018). Automation and utilization of resources available are evidence-based interventions. Data findings also helps to leverage possibilities that improves patient outcomes.
Big data have also enabled the understanding of translation causal effects of clinical problems and their corresponding treatments (Pastorino et al., 2019). Electronic health records data can be useful to perform random clinical trials. These data offer large sample sizes that would provide new perspective to disease risk factors. In diabetes monitoring for example, individualized interaction using mobile health devices capable of collecting high data volumes are used with patients for real-time analysis, this enables quick responses to behavior changes for positive health results.
The accessibility of patient data from devices to use for scientific research or reproduce has been a challenge due to the proprietary rights, share-ability, and privacy concerns involved, Thew (2016). The ownership of patient data uploaded in electronic health record systems has generated serious ongoing debate. It is presently considered that patients have rights to ownership of the data while the provider is only responsible for the data storage. In view of the above, it is difficult to access the information for the purpose of analysis unless authorized by the primary care provider. It is difficult to use the data even after it has been de-identified, there is also limitations in the ability to manipulate, use or share the data across various platforms. Data is collected in different formats by different systems, this makes the sharing process extremely complicating unless it is converted to formats which other systems can access. Patient privacy concerns guided by laws also affect accessibility of large data, providers are overly cautious of breach of patient’s privacy and this limits them from sharing patient information.
Through replicating the open-source technologies applied in other disciplines, the issue of data accessibility can be defeated. This will allow the protection of patient privacy and comply with regulations. Different systems can be mitigated through the use of hardware-software ecosystems that would facilitate distribution as exemplified in the Android or Apple app stores that enable access of de-identified data in compatible formats by authorized individuals (Pastorino et al., 2019).
The fact that the era of big data has opened opportunities in the clinical space cannot be over-emphasized, regardless that it comes with challenges for researchers. One of the enormous benefits include enhanced efficiency of healthcare while the major challenge is the accessibility of the data.
Adibuzzaman, M., DeLaurentis, P., Hill, J., & Benneyworth, B. D. (2018). Big data in healthcare – the promises, challenges and opportunities from a research perspective: A case study with a model database. AMIA … Annual Symposium proceedings. AMIA Symposium, 2017, 384–392.
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.
Thew, J. (2016). Big Data Means Big Potential, Challenges for Nurse Execs. HealthLeaders. https://www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs
Can you help me understand this Statistics question?
Discussion: Big Data Risks and Rewards
When you wake in the morning, you may reach for your cell phone to reply to a few text or email messages that you missed overnight. On your drive to work, you may stop to refuel your car. Upon your arrival, you might swipe a key card at the door to gain entrance to the facility. And before finally reaching your workstation, you may stop by the cafeteria to purchase a coffee.
From the moment you wake, you are in fact a data-generation machine. 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.
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 4
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 4
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.
SUBMISSION AND GRADING INFORMATION
To access your rubric:
Week 4 Discussion Rubric
You must proofread your paper. But do not strictly rely on your computer’s spell-checker and grammar-checker; failure to do so indicates a lack of effort on your part and you can expect your grade to suffer accordingly. Papers with numerous misspelled words and grammatical mistakes will be penalized. Read over your paper – in silence and then aloud – before handing it in and make corrections as necessary. Often it is advantageous to have a friend proofread your paper for obvious errors. Handwritten corrections are preferable to uncorrected mistakes.
Use a standard 10 to 12 point (10 to 12 characters per inch) typeface. Smaller or compressed type and papers with small margins or single-spacing are hard to read. It is better to let your essay run over the recommended number of pages than to try to compress it into fewer pages.
Likewise, large type, large margins, large indentations, triple-spacing, increased leading (space between lines), increased kerning (space between letters), and any other such attempts at “padding” to increase the length of a paper are unacceptable, wasteful of trees, and will not fool your professor.
The paper must be neatly formatted, double-spaced with a one-inch margin on the top, bottom, and sides of each page. When submitting hard copy, be sure to use white paper and print out using dark ink. If it is hard to read your essay, it will also be hard to follow your argument.
ADDITIONAL INSTRUCTIONS FOR THE CLASS
Discussion Questions (DQ)
Initial responses to the DQ should address all components of the questions asked, include a minimum of one scholarly source, and be at least 250 words.
Successful responses are substantive (i.e., add something new to the discussion, engage others in the discussion, well-developed idea) and include at least one scholarly source.
One or two sentence responses, simple statements of agreement or “good post,” and responses that are off-topic will not count as substantive. Substantive responses should be at least 150 words.
I encourage you to incorporate the readings from the week (as applicable) into your responses.
Your initial responses to the mandatory DQ do not count toward participation and are graded separately.
In addition to the DQ responses, you must post at least one reply to peers (or me) on three separate days, for a total of three replies.
Participation posts do not require a scholarly source/citation (unless you cite someone else’s work).
Part of your weekly participation includes viewing the weekly announcement and attesting to watching it in the comments. These announcements are made to ensure you understand everything that is due during the week.
APA Format and Writing Quality
Familiarize yourself with APA format and practice using it correctly. It is used for most writing assignments for your degree. Visit the Writing Center in the Student Success Center, under the Resources tab in LoudCloud for APA paper templates, citation examples, tips, etc. Points will be deducted for poor use of APA format or absence of APA format (if required).
Cite all sources of information! When in doubt, cite the source. Paraphrasing also requires a citation.
I highly recommend using the APA Publication Manual, 6th edition.
Use of Direct Quotes
I discourage overutilization of direct quotes in DQs and assignments at the Masters’ level and deduct points accordingly.
As Masters’ level students, it is important that you be able to critically analyze and interpret information from journal articles and other resources. Simply restating someone else’s words does not demonstrate an understanding of the content or critical analysis of the content.
It is best to paraphrase content and cite your source.
For assignments that need to be submitted to LopesWrite, please be sure you have received your report and Similarity Index (SI) percentage BEFORE you do a “final submit” to me.
Once you have received your report, please review it. This report will show you grammatical, punctuation, and spelling errors that can easily be fixed. Take the extra few minutes to review instead of getting counted off for these mistakes.
Review your similarities. Did you forget to cite something? Did you not paraphrase well enough? Is your paper made up of someone else’s thoughts more than your own?
Visit the Writing Center in the Student Success Center, under the Resources tab in LoudCloud for tips on improving your paper and SI score.
The university’s policy on late assignments is 10% penalty PER DAY LATE. This also applies to late DQ replies.
Please communicate with me if you anticipate having to submit an assignment late. I am happy to be flexible, with advance notice. We may be able to work out an extension based on extenuating circumstances.
If you do not communicate with me before submitting an assignment late, the GCU late policy will be in effect.
I do not accept assignments that are two or more weeks late unless we have worked out an extension.
As per policy, no assignments are accepted after the last day of class. Any assignment submitted after midnight on the last day of class will not be accepted for grading.
Communication is so very important. There are multiple ways to communicate with me:
Questions to Instructor Forum: This is a great place to ask course content or assignment questions. If you have a question, there is a good chance one of your peers does as well. This is a public forum for the class.
Individual Forum: This is a private forum to ask me questions or send me messages. This will be checked at least once every 24 hours.