Dialogue: Big Data Risks and Rewards
Whenever you wake within the morning, you might attain to your mobile phone to answer to some textual content or electronic mail messages that you simply missed in a single day. In your drive to work, you might cease to refuel your automobile. Upon your arrival, you may swipe a key card on the door to realize entrance to the power. And earlier than lastly reaching your workstation, you might cease by the cafeteria to buy a espresso.
From the second you wake, you might be in truth a data-generation machine. Every use of your cellphone, each transaction you make utilizing a debit or bank card, even your entrance to your place of job, creates knowledge. It begs the Question Assignment: How a lot knowledge do you generate every day? Many research have been carried out on this, and the numbers are staggering: Estimates recommend that almost 1 million bytes of knowledge are generated each second for each particular person on earth.
As the quantity of knowledge will increase, info professionals have seemed for tactics to make use of massive knowledge—massive, advanced units of knowledge that require specialised approaches to make use of successfully. Big knowledge has the potential for vital rewards—and vital dangers—to healthcare. On this Dialogue, you’ll take into account these dangers and rewards.
To Put together:
• Evaluate the Assets and replicate on the internet article Big Data Means Big Potential, Challenges for Nurse Execs.
• Mirror by yourself expertise with advanced well being info entry and administration and take into account potential challenges and dangers you’ll have skilled or noticed.
By Day three of Week 5
Submit an outline of at the very least one potential good thing about utilizing massive knowledge as a part of a scientific system and clarify why. Then, describe at the very least one potential problem or threat of utilizing massive knowledge as a part of a scientific system and clarify why. Suggest at the very least one technique you’ve skilled, noticed, or researched which will successfully mitigate the challenges or dangers of utilizing massive knowledge you described. Be particular and present examples.
Rubric Element
Choose Grid View or Listing View to alter the rubric’s structure.
Identify: NURS_5051_Module03_Week05_Discussion_Rubric
• Grid View
• Listing View
Wonderful Good Truthful Poor
Essential Posting 45 (45%) – 50 (50%)
Solutions all elements of the dialogue Question Assignment(s) expectations with reflective essential Assessment and synthesis of information gained from the course readings for the module and present credible sources.
Supported by at the very least three present, credible sources.
Written clearly and concisely with no grammatical or spelling errors and totally adheres to present APA guide writing guidelines and fashion. 40 (40%) – 44 (44%)
Responds to the dialogue Question Assignment(s) and is reflective with essential Assessment and synthesis of information gained from the course readings for the module.
A minimum of 75% of publish has distinctive depth and breadth.
Supported by at the very least three credible sources.
Written clearly and concisely with one or no grammatical or spelling errors and totally adheres to present APA guide writing guidelines and fashion. 35 (35%) – 39 (39%)
Responds to a few of the dialogue Question Assignment(s).
One or two standards usually are not addressed or are superficially addressed.
Is considerably missing reflection and essential Assessment and synthesis.
Considerably represents data gained from the course readings for the module.
Submit is cited with two credible sources.
Written considerably concisely; could comprise greater than two spelling or grammatical errors.
Accommodates some APA formatting errors. zero (zero%) – 34 (34%)
Doesn’t reply to the dialogue Question Assignment(s) adequately.
Lacks depth or superficially addresses standards.
Lacks reflection and essential Assessment and synthesis.
Doesn’t signify data gained from the course readings for the module.
Accommodates just one or no credible sources.
Not written clearly or concisely.
Accommodates greater than two spelling or grammatical errors.
Doesn’t adhere to present APA guide writing guidelines and fashion.
Essential Submit: Timeliness 10 (10%) – 10 (10%)
Posts important publish by day three. zero (zero%) – zero (zero%) zero (zero%) – zero (zero%) zero (zero%) – zero (zero%)
Doesn’t publish by day three.
First Response 17 (17%) – 18 (18%)
Response displays synthesis, essential pondering, and software to observe settings.
Responds totally to questions posed by school.
Gives clear, concise opinions and concepts which can be supported by at the very least two scholarly sources.
Demonstrates synthesis and understanding of studying goals.
Communication is skilled and respectful to colleagues.
Responses to school questions are totally answered, if posed.
Response is successfully written in normal, edited English. 15 (15%) – 16 (16%)
Response displays essential pondering and software to observe settings.
Communication is skilled and respectful to colleagues.
Responses to school questions are answered, if posed.
Gives clear, concise opinions and concepts which can be supported by two or extra credible sources.
Response is successfully written in normal, edited English. 13 (13%) – 14 (14%)
Response is on subject and could have some depth.
Responses posted within the dialogue could lack efficient skilled communication.
Responses to school questions are considerably answered, if posed.
Response could lack clear, concise opinions and concepts, and a couple of or no credible sources are cited. zero (zero%) – 12 (12%)
Response is probably not on subject and lacks depth.
Responses posted within the dialogue lack efficient skilled communication.
Responses to school questions are lacking.
No credible sources are cited.
Second Response 16 (16%) – 17 (17%)
Response displays synthesis, essential pondering, and software to observe settings.
Responds totally to questions posed by school.
Gives clear, concise opinions and concepts which can be supported by at the very least two scholarly sources.
Demonstrates synthesis and understanding of studying goals.
Communication is skilled and respectful to colleagues.
Responses to school questions are totally answered, if posed.
Response is successfully written in normal, edited English. 14 (14%) – 15 (15%)
Response displays essential pondering and software to observe settings.
Communication is skilled and respectful to colleagues.
Responses to school questions are answered, if posed.
Gives clear, concise opinions and concepts which can be supported by two or extra credible sources.
Response is successfully written in normal, edited English. 12 (12%) – 13 (13%)
Response is on subject and could have some depth.
Responses posted within the dialogue could lack efficient skilled communication.
Responses to school questions are considerably answered, if posed.
Response could lack clear, concise opinions and concepts, and a couple of or no credible sources are cited. zero (zero%) – 11 (11%)
Response is probably not on subject and lacks depth.
Responses posted within the dialogue lack efficient skilled communication.
Responses to school questions are lacking.
No credible sources are cited.
Participation 5 (5%) – 5 (5%)
Meets necessities for participation by posting on three completely different days. zero (zero%) – zero (zero%) zero (zero%) – zero (zero%) zero (zero%) – zero (zero%)
Doesn’t meet necessities for participation by posting on three completely different days.
Whole Factors: 100
Identify: NURS_5051_Module03_Week05_Discussion_Rubric
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Big Data Risks and Rewards
Pupil’s Identify
Institutional Affiliation
Course
Professor’s Identify
Date
Big Data Risks and Rewards
With the speedy tempo of change and complexity in well being care, now amplified by the pandemic, the caregivers want Help. That’s, they want well timed, insight-driven, and evidence-based knowledge to foster fast determination making in any respect factors of care. Environment friendly massive knowledge administration, Assessment, and interpretation can change the sport and open new avenues for contemporary well being care by offering superior affected person care (Murdoch & Detsky, 2013). For example, knowledge collected from a primary AI-enabled early warning affected person monitoring programs, cellular connectivity, scientific determination Help algorithm could be analyzed to Help well being care programs determine the affected person’s wants sooner and reply sooner (Bates, Saria, Ohno-Machado, Shah & Escobar, 2014). It has been recognized that the usage of early warning programs resulted in a discount of 35% in extreme instances of cardiac arrest(Bates et al., 2014).
Data standardization is among the challenges dealing with Big Data in well being. That’s, knowledge is saved in a fashion that isn’t interoperable with all functions and applied sciences. As knowledge is never standardized, restricted interrogability poses an enormous problem. This leaves massive knowledge to face points associated to buying and cleansing knowledge into an ordinary format for Assessment and international sharing of knowledge (Kruse, Goswamy, Raval & Marawi, 2016). Big knowledge must take care of completely different terminologies, demographic knowledge, requirements, and even language obstacles with the shift to knowledge globalization. For example, the affected person’s incorrect or incomplete demographic knowledge could be very detrimental to affected person matching and identification. This may create the danger of suppliers to affiliate two completely different sufferers with the identical file mistakenly.
Scientific managers ought to work collectively to re-engineer and standardize the Grasp Affected person Index(MPI) file. This may be executed by growing an intensive organization-wide knowledge cleansing technique of the MPI, particularly on areas duplicating affected person file discrepancies because of default or clean entries (Randall, Ferrante, Boyd & Semmens, 2013). This improves the standard of knowledge. That’s, an environment friendly data-driven scientific determination Help.
References
Bates, D. W., Saria, S., Ohno-Machado, L., Shah, A., & Escobar, G. (2014). Big knowledge in well being care: utilizing analytics to determine and handle high-risk and high-cost sufferers. Well being Affairs, 33(7), 1123-1131.
Kruse, C. S., Goswamy, R., Raval, Y. J., & Marawi, S. (2016). Challenges and alternatives of huge knowledge in well being care: a scientific evaluate. JMIR medical informatics, four(four), e38.
Murdoch, T. B., & Detsky, A. S. (2013). The inevitable software of huge knowledge to well being care. Jama, 309(13), 1351-1352.
Randall, S. M., Ferrante, A. M., Boyd, J. H., & Semmens, J. B. (2013). The impact of knowledge cleansing on file linkage high quality. BMC medical informatics and determination making, 13(1), 64.
Rn, Jennifer Thew. “Big Data Means Big Potential, Challenges for Nurse Execs.” BIG DATA MEANS BIG POTENTIAL, CHALLENGES FOR NURSE EXECS, 2016, www.healthleadersmedia.com/nursing/big-data-means-big-potential-challenges-nurse-execs.
